Digital baseline estimation method for multi-channel pulse height analyzing

International Nuclear Information System (INIS)

Xiao Wuyun; Wei Yixiang; Ai Xianyun

2005-01-01

The basic features of digital baseline estimation for multi-channel pulse height analysis are introduced. The weight-function of minimum-noise baseline filter is deduced with functional variational calculus. The frequency response of this filter is also deduced with Fourier transformation, and the influence of parameters on amplitude frequency response characteristics is discussed. With MATLAB software, the noise voltage signal from the charge sensitive preamplifier is simulated, and the processing effect of minimum-noise digital baseline estimation is verified. According to the results of this research, digital baseline estimation method can estimate baseline optimally, and it is very suitable to be used in digital multi-channel pulse height analysis. (authors)

On the Masses of the quasi-stellar objects

International Nuclear Information System (INIS)

Burbidge, G.; Perry, J.

1976-01-01

If it is assumed that the gas giving rise to the emission and absorption lines in quasi-stellar objects has been driven out of the central object by radiation pressure, arguments based on the dynamics of radiation-driven gas flows enable us to establish limits on the central masses and the rates of mass loss. For QSOs at cosmological distances it is found that the masses of the central objects must lie in the range 5 x 10 7 M/sub sun/approximately-less-thanMapproximately-less-than2 x 10 9 m/sub sun/ and that the mass loss rates should be M/Mapprox. =10 -7 yr -1 . If the QSOs are local objects, the upper limits to the masses are about 2 x 10 7 M/sub sun/

SED Modeling of 20 Massive Young Stellar Objects

Science.gov (United States)

Tanti, Kamal Kumar

In this paper, we present the spectral energy distributions (SEDs) modeling of twenty massive young stellar objects (MYSOs) and subsequently estimated different physical and structural/geometrical parameters for each of the twenty central YSO outflow candidates, along with their associated circumstellar disks and infalling envelopes. The SEDs for each of the MYSOs been reconstructed by using 2MASS, MSX, IRAS, IRAC & MIPS, SCUBA, WISE, SPIRE and IRAM data, with the help of a SED Fitting Tool, that uses a grid of 2D radiative transfer models. Using the detailed analysis of SEDs and subsequent estimation of physical and geometrical parameters for the central YSO sources along with its circumstellar disks and envelopes, the cumulative distribution of the stellar, disk and envelope parameters can be analyzed. This leads to a better understanding of massive star formation processes in their respective star forming regions in different molecular clouds.

A plausible energy source and structure for quasi-stellar objects

Science.gov (United States)

Daltabuit, E.; Cox, D.

1972-01-01

If a collision of two large, massive, fast gas clouds occurs, their kinetic energy is converted to radiation in a pair of shock fronts at their interface. The resulting structure is described, and the relevance of this as a radiation source for quasi-stellar objects is considered.

Non-convex multi-objective optimization

CERN Document Server

Pardalos, Panos M; Žilinskas, Julius

2017-01-01

Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions. Multi-objective optimization methods facilitate designers, engineers, and researchers to make decisions on appropriate trade-offs between various conflicting goals. A variety of deterministic and stochastic multi-objective optimization methods are developed in this book. Beginning with basic concepts and a review of non-convex single-objective optimization problems; this book moves on to cover multi-objective branch and bound algorithms, worst-case optimal algorithms (for Lipschitz functions and bi-objective problems), statistical models based algorithms, and probabilistic branch and bound approach. Detailed descriptions of new algorithms for non-convex multi-objective optimization, their theoretical substantiation, and examples for practical applications to the cell formation problem in manufacturing engineering, the process design in...

Stellar observations with the Voyager EUV objective grating spectrograph

International Nuclear Information System (INIS)

Holberg, J.B.; Polidan, R.S.; Barry, D.C.

1986-01-01

During the periods of interplanetary cruise the Voyager ultraviolet spectrometers are used to provide unique and otherwise unobtainable observations in the extreme ultraviolet (EUV, 500 to 1200) and the far ultraviolet (FUV, 912 to 1220 A). These observations include the spectra of hot stellar sources as well as emission from the interplanetary medium. Recent results of note include: (1) extensive spectrophotometric coverage of a superoutburst of the dwarf nova VW Hydri, which showed a clear 1/2 day delay in the outburst at 1000 A relative to that observed in the optical and a curious dip in the FUV light curve near maximum light. The Voyager observations were part of a comprehensive and highly successful campaign involving EXOSAT, IUE and ground based observations of this dwarf nova; (2) a comprehensive study of Be star spectra and variability. These results show the critical importance of FUV observations in the study of the effects of stellar rotation in hot stars; (3) the detection of a strong O VI absorption feature in the spectrum of the PG 1159-like object H1504+65. This detection along with the optical identification of weak O IV lines was a key to the interpretation of this object; which is of extremely high (>150,000K) temperature and appears to be a unique example of a stellar atmosphere devoid of H and He; (4) an analysis of an extremely long duration spectrum of the EUV and FUV sky background, which establishes important new upper limits on both continuum and line emission. This result also provide the first detection of interplanetary Lyman gamma

Bandwidth Optimization of Normal Equation Matrix in Bundle Block Adjustment in Multi-baseline Rotational Photography

Directory of Open Access Journals (Sweden)

WANG Xiang

2016-02-01

Full Text Available A new bandwidth optimization method of normal equation matrix in bundle block adjustment in multi-baseline rotational close range photography by image index re-sorting is proposed. The equivalent exposure station of each image is calculated by its object space coverage and the relationship with other adjacent images. Then, according to the coordinate relations between equivalent exposure stations, new logical indices of all images are computed, based on which, the optimized bandwidth value can be obtained. Experimental results show that the bandwidth determined by our proposed method is significantly better than its original value, thus the operational efficiency, as well as the memory consumption of multi-baseline rotational close range photography in real-data applications, is optimized to a certain extent.

Influence of stellar multiplicity on planet formation. I. Evidence of suppressed planet formation due to stellar companions within 20 au and validation of four planets from the Kepler multiple planet candidates

International Nuclear Information System (INIS)

Wang, Ji; Fischer, Debra A.; Xie, Ji-Wei; Barclay, Thomas

2014-01-01

The planet occurrence rate for multiple stars is important in two aspects. First, almost half of stellar systems in the solar neighborhood are multiple systems. Second, the comparison of the planet occurrence rate for multiple stars to that for single stars sheds light on the influence of stellar multiplicity on planet formation and evolution. We developed a method of distinguishing planet occurrence rates for single and multiple stars. From a sample of 138 bright (K P < 13.5) Kepler multi-planet candidate systems, we compared the stellar multiplicity rate of these planet host stars to that of field stars. Using dynamical stability analyses and archival Doppler measurements, we find that the stellar multiplicity rate of planet host stars is significantly lower than field stars for semimajor axes less than 20 AU, suggesting that planet formation and evolution are suppressed by the presence of a close-in companion star at these separations. The influence of stellar multiplicity at larger separations is uncertain because of search incompleteness due to a limited Doppler observation time baseline and a lack of high-resolution imaging observation. We calculated the planet confidence for the sample of multi-planet candidates and find that the planet confidences for KOI 82.01, KOI 115.01, KOI 282.01, and KOI 1781.02 are higher than 99.7% and thus validate the planetary nature of these four planet candidates. This sample of bright Kepler multi-planet candidates with refined stellar and orbital parameters, planet confidence estimation, and nearby stellar companion identification offers a well-characterized sample for future theoretical and observational study.

77 FR 23318 - Culturally Significant Object Imported for Exhibition Determinations: “African Cosmos: Stellar Arts”

Science.gov (United States)

2012-04-18

... Determinations: ``African Cosmos: Stellar Arts'' SUMMARY: Notice is hereby given of the following determinations... the exhibition ``African Cosmos: Stellar Arts,'' imported from abroad for temporary exhibition within... object at the Smithsonian Institution's National Museum of African Arts, Washington, DC, from on or about...

Multi objective multi refinery optimization with environmental and catastrophic failure effects objectives

Science.gov (United States)

Khogeer, Ahmed Sirag

2005-11-01

Petroleum refining is a capital-intensive business. With stringent environmental regulations on the processing industry and declining refining margins, political instability, increased risk of war and terrorist attacks in which refineries and fuel transportation grids may be targeted, higher pressures are exerted on refiners to optimize performance and find the best combination of feed and processes to produce salable products that meet stricter product specifications, while at the same time meeting refinery supply commitments and of course making profit. This is done through multi objective optimization. For corporate refining companies and at the national level, Intea-Refinery and Inter-Refinery optimization is the second step in optimizing the operation of the whole refining chain as a single system. Most refinery-wide optimization methods do not cover multiple objectives such as minimizing environmental impact, avoiding catastrophic failures, or enhancing product spec upgrade effects. This work starts by carrying out a refinery-wide, single objective optimization, and then moves to multi objective-single refinery optimization. The last step is multi objective-multi refinery optimization, the objectives of which are analysis of the effects of economic, environmental, product spec, strategic, and catastrophic failure. Simulation runs were carried out using both MATLAB and ASPEN PIMS utilizing nonlinear techniques to solve the optimization problem. The results addressed the need to debottleneck some refineries or transportation media in order to meet the demand for essential products under partial or total failure scenarios. They also addressed how importing some high spec products can help recover some of the losses and what is needed in order to accomplish this. In addition, the results showed nonlinear relations among local and global objectives for some refineries. The results demonstrate that refineries can have a local multi objective optimum that does not

Tracking Non-stellar Objects on Ground and in Space

DEFF Research Database (Denmark)

Riis, Troels; Jørgensen, John Leif

1999-01-01

Many space exploration missions require a fast, early and accurate detection of a specific target. E.g. missions to asteroids, x-ray source missions or interplanetary missions.A second generation star tracker may be used for accurate detection of non-stellar objects of interest for such missions......, simply by listing all objects detected in an image not being identified as a star. Of course a lot of deep space objects will be listed too, especially if the detection threshold is set to let faint object pass through. Assuming a detection threshold of, say mv 7 (the Hipparcos catalogue is complete...... objects that do not move. For stationary objects no straightforward procedure exists to reduce the size of the list, but in the case the user has an approximate knowledge of which area to search the amount of data may be reduced substantially. In the case of a mission to an asteroid, the above described...

Imaging Young Stellar Objects with VLTi/PIONIER

Science.gov (United States)

Kluska, J.; Malbet, F.; Berger, J.-P.; Benisty, M.; Lazareff, B.; Le Bouquin, J.-B.; Baron, F.; Dominik, C.; Isella, A.; Juhasz, A.; Kraus, S.; Lachaume, R.; Ménard, F.; Millan-Gabet, R.; Monnier, J.; Pinte, C.; Soulez, F.; Tallon, M.; Thi, W.-F.; Thiébaut, É.; Zins, G.

2014-04-01

Optical interferometry imaging is designed to help us to reveal complex astronomical sources without a prior model. Among these complex objects are the young stars and their environments, which have a typical morphology with a point-like source, surrounded by circumstellar material with unknown morphology. To image them, we have developed a numerical method that removes completely the stellar point source and reconstructs the rest of the image, using the differences in the spectral behavior between the star and its circumstellar material. We aim to reveal the first Astronomical Units of these objects where many physical phenomena could interplay: the dust sublimation causing a puffed-up inner rim, a dusty halo, a dusty wind or an inner gaseous component. To investigate more deeply these regions, we carried out the first Large Program survey of HAeBe stars with two main goals: statistics on the geometry of these objects at the first astronomical unit scale and imaging their very close environment. The images reveal the environment, which is not polluted by the star and allows us to derive the best fit for the flux ratio and the spectral slope. We present the first images from this survey and the application of the imaging method on other astronomical objects.

MOONS: a multi-object optical and near-infrared spectrograph for the VLT

NARCIS (Netherlands)

Cirasuolo, M.; Afonso, J.; Bender, R.; Bonifacio, P.; Evans, C.; Kaper, L.; Oliva, Ernesto; Vanzi, Leonardo; Abreu, Manuel; Atad-Ettedgui, Eli; Babusiaux, Carine; Bauer, Franz E.; Best, Philip; Bezawada, Naidu; Bryson, Ian R.; Cabral, Alexandre; Caputi, Karina; Centrone, Mauro; Chemla, Fanny; Cimatti, Andrea; Cioni, Maria-Rosa; Clementini, Gisella; Coelho, João.; Daddi, Emanuele; Dunlop, James S.; Feltzing, Sofia; Ferguson, Annette; Flores, Hector; Fontana, Adriano; Fynbo, Johan; Garilli, Bianca; Glauser, Adrian M.; Guinouard, Isabelle; Hammer, Jean-François; Hastings, Peter R.; Hess, Hans-Joachim; Ivison, Rob J.; Jagourel, Pascal; Jarvis, Matt; Kauffman, G.; Lawrence, A.; Lee, D.; Li Causi, G.; Lilly, S.; Lorenzetti, D.; Maiolino, R.; Mannucci, F.; McLure, R.; Minniti, D.; Montgomery, D.; Muschielok, B.; Nandra, K.; Navarro, R.; Norberg, P.; Origlia, L.; Padilla, N.; Peacock, J.; Pedicini, F.; Pentericci, L.; Pragt, J.; Puech, M.; Randich, S.; Renzini, A.; Ryde, N.; Rodrigues, M.; Royer, F.; Saglia, R.; Sánchez, A.; Schnetler, H.; Sobral, D.; Speziali, R.; Todd, S.; Tolstoy, E.; Torres, M.; Venema, L.; Vitali, F.; Wegner, M.; Wells, M.; Wild, V.; Wright, G.

MOONS is a new conceptual design for a Multi-Object Optical and Near-infrared Spectrograph for the Very Large Telescope (VLT), selected by ESO for a Phase A study. The baseline design consists of ~1000 fibers deployable over a field of view of ~500 square arcmin, the largest patrol field offered by

Approximating multi-objective scheduling problems

NARCIS (Netherlands)

Dabia, S.; Talbi, El-Ghazali; Woensel, van T.; Kok, de A.G.

2013-01-01

In many practical situations, decisions are multi-objective by nature. In this paper, we propose a generic approach to deal with multi-objective scheduling problems (MOSPs). The aim is to determine the set of Pareto solutions that represent the interactions between the different objectives. Due to

High Energy Emissions from Young Stellar Objects A. C. Das1 ...

Indian Academy of Sciences (India)

... for the generation of emissions from a YSO on the basis of a simple interaction between the ... important role in generating intense radiation, bipolar flows, stellar winds and many ... Even in the case of a non-rotating compact object, the motion .... The change in energy of the particle due to this electric field is given by. 〈1.

Multi-band morpho-Spectral Component Analysis Deblending Tool (MuSCADeT): Deblending colourful objects

Science.gov (United States)

Joseph, R.; Courbin, F.; Starck, J.-L.

2016-05-01

We introduce a new algorithm for colour separation and deblending of multi-band astronomical images called MuSCADeT which is based on Morpho-spectral Component Analysis of multi-band images. The MuSCADeT algorithm takes advantage of the sparsity of astronomical objects in morphological dictionaries such as wavelets and their differences in spectral energy distribution (SED) across multi-band observations. This allows us to devise a model independent and automated approach to separate objects with different colours. We show with simulations that we are able to separate highly blended objects and that our algorithm is robust against SED variations of objects across the field of view. To confront our algorithm with real data, we use HST images of the strong lensing galaxy cluster MACS J1149+2223 and we show that MuSCADeT performs better than traditional profile-fitting techniques in deblending the foreground lensing galaxies from background lensed galaxies. Although the main driver for our work is the deblending of strong gravitational lenses, our method is fit to be used for any purpose related to deblending of objects in astronomical images. An example of such an application is the separation of the red and blue stellar populations of a spiral galaxy in the galaxy cluster Abell 2744. We provide a python package along with all simulations and routines used in this paper to contribute to reproducible research efforts. Codes can be found at http://lastro.epfl.ch/page-126973.html

The lick-index calibration of the Gemini multi-object spectrographs

International Nuclear Information System (INIS)

Puzia, Thomas H.; Miller, Bryan W.; Trancho, Gelys; Basarab, Brett; Mirocha, Jordan T.; Butler, Karen

2013-01-01

We present the calibration of the spectroscopic Lick/IDS standard line-index system for measurements obtained with the Gemini Multi-Object Spectrographs known as GMOS-North and GMOS-South. We provide linear correction functions for each of the 25 standard Lick line indices for the B600 grism and two instrumental setups, one with 0.''5 slit width and 1 × 1 CCD pixel binning (corresponding to ∼2.5 Å spectral resolution) and the other with 0.''75 slit width and 2 × 2 binning (∼4 Å). We find small and well-defined correction terms for the set of Balmer indices Hβ, Hγ A , and Hδ A along with the metallicity sensitive indices Fe5015, Fe5270, Fe5335, Fe5406, Mg 2 , and Mgb that are widely used for stellar population diagnostics of distant stellar systems. We find other indices that sample molecular absorption bands, such as TiO 1 and TiO 2 , with very wide wavelength coverage or indices that sample very weak molecular and atomic absorption features, such as Mg 1 , as well as indices with particularly narrow passband definitions, such as Fe4384, Ca4455, Fe4531, Ca4227, and Fe5782, which are less robustly calibrated. These indices should be used with caution.

Luminosity excesses in low-mass young stellar objects - a statistical study

International Nuclear Information System (INIS)

Strom, K.M.; Strom, S.E.; Kenyon, S.J.; Hartmann, L.

1988-01-01

This paper presents a statistical study in which the observed total luminosity is compared quantitatively with an estimate of the stellar luminosity for a sample of 59 low-mass young stellar objects (YSOs) in the Taurus-Auriga complex. In 13 of the analyzed YSOs, luminosity excesses greater than 0.20 are observed together with greater than 0.6 IR excesses, which typically contribute the bulk of the observed excess luminosity and are characterized by spectral energy distributions which are flat or rise toward long wavelengths. The analysis suggests that YSOs showing the largest luminosity excesses typically power optical jets and/or molecular outflows or have strong winds, as evidenced by the presence of O I emission, indicating a possible correlation between accretion and mass-outflow properties. 38 references

Automatic Multi-Level Thresholding Segmentation Based on Multi-Objective Optimization

Directory of Open Access Journals (Sweden)

L. DJEROU,

2012-01-01

Full Text Available In this paper, we present a new multi-level image thresholding technique, called Automatic Threshold based on Multi-objective Optimization "ATMO" that combines the flexibility of multi-objective fitness functions with the power of a Binary Particle Swarm Optimization algorithm "BPSO", for searching the "optimum" number of the thresholds and simultaneously the optimal thresholds of three criteria: the between-class variances criterion, the minimum error criterion and the entropy criterion. Some examples of test images are presented to compare our segmentation method, based on the multi-objective optimization approach with Otsu’s, Kapur’s and Kittler’s methods. Our experimental results show that the thresholding method based on multi-objective optimization is more efficient than the classical Otsu’s, Kapur’s and Kittler’s methods.

VLBA DETERMINATION OF THE DISTANCE TO NEARBY STAR-FORMING REGIONS. VI. THE DISTANCE TO THE YOUNG STELLAR OBJECT HW 9 IN CEPHEUS A

International Nuclear Information System (INIS)

Dzib, Sergio; Loinard, Laurent; RodrIguez, Luis F.; Mioduszewski, Amy J.; Torres, Rosa M.

2011-01-01

Using the Very Long Baseline Array (VLBA), we have observed the radio continuum emission from the young stellar object HW 9 in the Cepheus A star-forming region at 10 epochs between 2007 February and 2009 November. Due to its strong radio variability, the source was detected at only four of the ten epochs. From these observations, the trigonometric parallax of HW 9 was determined to be π = 1.43 ± 0.07 mas, in excellent agreement with a recent independent determination by Moscadelli et al. of the trigonometric parallax of a methanol maser associated with the nearby young stellar source HW 2 (π = 1.43 ± 0.08 mas). This concordance in results, obtained in one case from continuum and in the other from line observations, confirms the reliability of VLBA trigonometric parallax measurements. By combining the two results, we constrain the distance to Cepheus A to be 700 +31 - 28 pc, an uncertainty of 3.5%.

A MODEL FOR (QUASI-)PERIODIC MULTIWAVELENGTH PHOTOMETRIC VARIABILITY IN YOUNG STELLAR OBJECTS

Energy Technology Data Exchange (ETDEWEB)

Kesseli, Aurora Y. [Boston University, 725 Commonwealth Ave, Boston, MA 02215 (United States); Petkova, Maya A.; Wood, Kenneth; Gregory, Scott G. [SUPA, School of Physics and Astronomy, University of St Andrews, North Haugh, St Andrews, Fife, KY16 9AD (United Kingdom); Whitney, Barbara A. [Department of Astronomy, University of Wisconsin-Madison, 475 N. Charter St, Madison, WI 53706 (United States); Hillenbrand, L. A. [Astronomy Department, California Institute of Technology, Pasadena, CA 91125 (United States); Stauffer, J. R.; Morales-Calderon, M.; Rebull, L. [Spitzer Science Center, California Institute of Technology, CA 91125 (United States); Alencar, S. H. P., E-mail: aurorak@bu.com [Departamento de Física—ICEx—UFMG, Av. Antônio Carlos, 6627, 30270-901, Belo Horizonte, MG (Brazil)

2016-09-01

We present radiation transfer models of rotating young stellar objects (YSOs) with hot spots in their atmospheres, inner disk warps, and other three-dimensional effects in the nearby circumstellar environment. Our models are based on the geometry expected from magneto-accretion theory, where material moving inward in the disk flows along magnetic field lines to the star and creates stellar hot spots upon impact. Due to rotation of the star and magnetosphere, the disk is variably illuminated. We compare our model light curves to data from the Spitzer YSOVAR project to determine if these processes can explain the variability observed at optical and mid-infrared wavelengths in young stars. We focus on those variables exhibiting “dipper” behavior that may be periodic, quasi-periodic, or aperiodic. We find that the stellar hot-spot size and temperature affects the optical and near-infrared light curves, while the shape and vertical extent of the inner disk warp affects the mid-IR light curve variations. Clumpy disk distributions with non-uniform fractal density structure produce more stochastic light curves. We conclude that magneto-accretion theory is consistent with certain aspects of the multiwavelength photometric variability exhibited by low-mass YSOs. More detailed modeling of individual sources can be used to better determine the stellar hot-spot and inner disk geometries of particular sources.

Variability of Massive Young Stellar Objects in Cygnus-X

Science.gov (United States)

Thomas, Nancy H.; Hora, J. L.; Smith, H. A.

2013-01-01

Young stellar objects (YSOs) are stars in the process of formation. Several recent investigations have shown a high rate of photometric variability in YSOs at near- and mid-infrared wavelengths. Theoretical models for the formation of massive stars (1-10 solar masses) remain highly idealized, and little is known about the mechanisms that produce the variability. An ongoing Spitzer Space Telescope program is studying massive star formation in the Cygnus-X region. In conjunction with the Spitzer observations, we have conducted a ground-based near-infrared observing program of the Cygnus-X DR21 field using PAIRITEL, the automated infrared telescope at Whipple Observatory. Using the Stetson index for variability, we identified variable objects and a number of variable YSOs in our time-series PAIRITEL data of DR21. We have searched for periodicity among our variable objects using the Lomb-Scargle algorithm, and identified periodic variable objects with an average period of 8.07 days. Characterization of these variable and periodic objects will help constrain models of star formation present. This work is supported in part by the NSF REU and DOD ASSURE programs under NSF grant no. 0754568 and by the Smithsonian Institution.

Latest Results from the Multi-Object Keck Exoplanet Tracker

Science.gov (United States)

Van Eyken, Julian C.; Ge, J.; Wan, X.; Zhao, B.; Hariharan, A.; Mahadevan, S.; DeWitt, C.; Guo, P.; Cohen, R.; Fleming, S. W.; Crepp, J.; Warner, C.; Kane, S.; Leger, F.; Pan, K.

2006-12-01

The W. M. Keck Exoplanet Tracker is a precision Doppler radial velocity instrument based on dispersed fixed-delay interferometry (DFDI) which takes advantage of the new technique to allow multi-object RV surveying. Installed at the 2.5m Sloan telescope at Apache Point Observatory, the combination of Michelson interferometer and medium resolution spectrograph allows design for simultaneous Doppler measurements of up to 60 targets, while maintaining high instrument throughput. Using a single-object prototype of the instrument at the Kitt Peak National Observatory 2.1m telescope, we previously discovered a 0.49MJup planet, HD 102195b (ET-1), orbiting with a 4.11d period, and other interesting targets are being followed up. From recent trial observations, the Keck Exoplanet Tracker now yields 59 usable simultaneous fringing stellar spectra, of a quality sufficient to attempt to detect short period hot-Jupiter type planets. Recent engineering improvements reduced errors by a factor of 2, and typical photon limits for stellar data are now at the 30m/s level for magnitude V 10.5 (depending on spectral type and v sin i), with a best value of 6.9m/s at V=7.6. Preliminary RMS precisions from solar data (daytime sky) are around 10m/s over a few days, with some spectra reaching close to their photon limit of 6-7m/s on the short term ( 1 hour). A number of targets showing interesting RV variability are currently being followed up independently. Additional engineering work is planned which should make for further significant gains in Doppler precision. Here we present the latest results and updates from the most recent engineering and observing runs with the Keck ET.

Digital fabrication of multi-material biomedical objects

Energy Technology Data Exchange (ETDEWEB)

Cheung, H H; Choi, S H, E-mail: shchoi@hku.h [Department of Industrial and Manufacturing Systems Engineering, University of Hong Kong, Pokfulam Road (Hong Kong)

2009-12-15

This paper describes a multi-material virtual prototyping (MMVP) system for modelling and digital fabrication of discrete and functionally graded multi-material objects for biomedical applications. The MMVP system consists of a DMMVP module, an FGMVP module and a virtual reality (VR) simulation module. The DMMVP module is used to model discrete multi-material (DMM) objects, while the FGMVP module is for functionally graded multi-material (FGM) objects. The VR simulation module integrates these two modules to perform digital fabrication of multi-material objects, which can be subsequently visualized and analysed in a virtual environment to optimize MMLM processes for fabrication of product prototypes. Using the MMVP system, two biomedical objects, including a DMM human spine and an FGM intervertebral disc spacer are modelled and digitally fabricated for visualization and analysis in a VR environment. These studies show that the MMVP system is a practical tool for modelling, visualization, and subsequent fabrication of biomedical objects of discrete and functionally graded multi-materials for biomedical applications. The system may be adapted to control MMLM machines with appropriate hardware for physical fabrication of biomedical objects.

Digital fabrication of multi-material biomedical objects

International Nuclear Information System (INIS)

Cheung, H H; Choi, S H

2009-01-01

This paper describes a multi-material virtual prototyping (MMVP) system for modelling and digital fabrication of discrete and functionally graded multi-material objects for biomedical applications. The MMVP system consists of a DMMVP module, an FGMVP module and a virtual reality (VR) simulation module. The DMMVP module is used to model discrete multi-material (DMM) objects, while the FGMVP module is for functionally graded multi-material (FGM) objects. The VR simulation module integrates these two modules to perform digital fabrication of multi-material objects, which can be subsequently visualized and analysed in a virtual environment to optimize MMLM processes for fabrication of product prototypes. Using the MMVP system, two biomedical objects, including a DMM human spine and an FGM intervertebral disc spacer are modelled and digitally fabricated for visualization and analysis in a VR environment. These studies show that the MMVP system is a practical tool for modelling, visualization, and subsequent fabrication of biomedical objects of discrete and functionally graded multi-materials for biomedical applications. The system may be adapted to control MMLM machines with appropriate hardware for physical fabrication of biomedical objects.

Global shape optimization of airfoil using multi-objective genetic algorithm

International Nuclear Information System (INIS)

Lee, Ju Hee; Lee, Sang Hwan; Park, Kyoung Woo

2005-01-01

The shape optimization of an airfoil has been performed for an incompressible viscous flow. In this study, Pareto frontier sets, which are global and non-dominated solutions, can be obtained without various weighting factors by using the multi-objective genetic algorithm. An NACA0012 airfoil is considered as a baseline model, and the profile of the airfoil is parameterized and rebuilt with four Bezier curves. Two curves, from leading to maximum thickness, are composed of five control points and the rest, from maximum thickness to tailing edge, are composed of four control points. There are eighteen design variables and two objective functions such as the lift and drag coefficients. A generation is made up of forty-five individuals. After fifteenth evolutions, the Pareto individuals of twenty can be achieved. One Pareto, which is the best of the reduction of the drag force, improves its drag to 13% and lift-drag ratio to 2%. Another Pareto, however, which is focused on increasing the lift force, can improve its lift force to 61%, while sustaining its drag force, compared to those of the baseline model

Global shape optimization of airfoil using multi-objective genetic algorithm

Energy Technology Data Exchange (ETDEWEB)

Lee, Ju Hee; Lee, Sang Hwan [Hanyang Univ., Seoul (Korea, Republic of); Park, Kyoung Woo [Hoseo Univ., Asan (Korea, Republic of)

2005-10-01

The shape optimization of an airfoil has been performed for an incompressible viscous flow. In this study, Pareto frontier sets, which are global and non-dominated solutions, can be obtained without various weighting factors by using the multi-objective genetic algorithm. An NACA0012 airfoil is considered as a baseline model, and the profile of the airfoil is parameterized and rebuilt with four Bezier curves. Two curves, from leading to maximum thickness, are composed of five control points and the rest, from maximum thickness to tailing edge, are composed of four control points. There are eighteen design variables and two objective functions such as the lift and drag coefficients. A generation is made up of forty-five individuals. After fifteenth evolutions, the Pareto individuals of twenty can be achieved. One Pareto, which is the best of the reduction of the drag force, improves its drag to 13% and lift-drag ratio to 2%. Another Pareto, however, which is focused on increasing the lift force, can improve its lift force to 61%, while sustaining its drag force, compared to those of the baseline model.

Effect of objective function on multi-objective inverse planning of radiation therapy

International Nuclear Information System (INIS)

Li Guoli; Wu Yican; Song Gang; Wang Shifang

2006-01-01

There are two kinds of objective functions in radiotherapy inverse planning: dose distribution-based and Dose-Volume Histogram (DVH)-based functions. The treatment planning in our days is still a trial and error process because the multi-objective problem is solved by transforming it into a single objective problem using a specific set of weights for each object. This work investigates the problem of objective function setting based on Pareto multi-optimization theory, and compares the effect on multi-objective inverse planning of those two kinds of objective functions including calculation time, converge speed, etc. The basis of objective function setting on inverse planning is discussed. (authors)

A LARGE, MASSIVE, ROTATING DISK AROUND AN ISOLATED YOUNG STELLAR OBJECT

International Nuclear Information System (INIS)

Quanz, Sascha P.; Beuther, Henrik; Steinacker, Juergen; Linz, Hendrik; Krause, Oliver; Henning, Thomas; Birkmann, Stephan M.; Zhang Qizhou

2010-01-01

We present multi-wavelength observations and a radiative transfer model of a newly discovered massive circumstellar disk of gas and dust which is one of the largest disks known today. Seen almost edge-on, the disk is resolved in high-resolution near-infrared (NIR) images and appears as a dark lane of high opacity intersecting a bipolar reflection nebula. Based on molecular line observations, we estimate the distance to the object to be 3.5 kpc. This leads to a size for the dark lane of ∼10,500 AU but due to shadowing effects the true disk size could be smaller. In Spitzer/IRAC 3.6 μm images, the elongated shape of the bipolar reflection nebula is still preserved and the bulk of the flux seems to come from disk regions that can be detected due to the slight inclination of the disk. At longer IRAC wavelengths, the flux is mainly coming from the central regions penetrating directly through the dust lane. Interferometric observations of the dust continuum emission at millimeter wavelengths with the Submillimeter Array confirm this finding as the peak of the unresolved millimeter-emission coincides perfectly with the peak of the Spitzer/IRAC 5.8 μm flux and the center of the dark lane seen in the NIR images. Simultaneously acquired CO data reveal a molecular outflow along the northern part of the reflection nebula which seems to be the outflow cavity. An elongated gaseous disk component is also detected and shows signs of rotation. The emission is perpendicular to the molecular outflow and thus parallel to but even more extended than the dark lane in the NIR images. Based on the dust continuum and the CO observations, we estimate a disk mass of up to a few solar masses depending on the underlying assumptions. Whether the disk-like structure is an actual accretion disk or rather a larger-scale flattened envelope or pseudodisk is difficult to discriminate with the current data set. The existence of HCO + /H 13 CO + emission proves the presence of dense gas in the disk

The Origin of Stellar Species: constraining stellar evolution scenarios with Local Group galaxy surveys

Science.gov (United States)

Sarbadhicary, Sumit; Badenes, Carles; Chomiuk, Laura; Maldonado, Jessica; Caprioli, Damiano; Heger, Mairead; Huizenga, Daniel

2018-01-01

Our understanding of the progenitors of many stellar species, such as supernovae, massive and low-mass He-burning stars, is limited because of many poorly constrained aspects of stellar evolution theory. For my dissertation, I have focused on using Local Group galaxy surveys to constrain stellar evolution scenarios by measuring delay-time distributions (DTD). The DTD is the hypothetical occurrence rate of a stellar object per elapsed time after a brief burst of star formation. It is the measured distribution of timescales on which stars evolve, and therefore serves as a powerful observational constraint on theoretical progenitor models. The DTD can be measured from a survey of stellar objects and a set of star-formation histories of the host galaxy, and is particularly effective in the Local Group, where high-quality star-formation histories are available from resolved stellar populations. I am currently calculating a SN DTD with supernova remnants (SNRs) in order to provide the strongest constraints on the progenitors of thermonuclear and core-collapse supernovae. However, most SNRs do not have reliable age measurements and their evolution depends on the ambient environment. For this reason, I wrote a radio light curve model of an SNR population to extract the visibility times and rates of supernovae - crucial ingredients for the DTD - from an SNR survey. The model uses observational constraints on the local environments from multi-wavelength surveys, accounts for missing SNRs and employs the latest models of shock-driven particle acceleration. The final calculation of the SN DTD in the Local Group is awaiting completion of a systematic SNR catalog from deep radio-continuum images, now in preparation by a group led by Dr. Laura Chomiuk. I have also calculated DTDs for the LMC population of RR Lyrae and Cepheid variables, which serve as important distance calibrators and stellar population tracers. We find that Cepheids can have delay-times between 10 Myrs - 1 Gyr

ESTIMATION OF DISTANCES TO STARS WITH STELLAR PARAMETERS FROM LAMOST

Energy Technology Data Exchange (ETDEWEB)

Carlin, Jeffrey L.; Newberg, Heidi Jo [Department of Physics, Applied Physics and Astronomy, Rensselaer Polytechnic Institute, Troy, NY 12180 (United States); Liu, Chao; Deng, Licai; Li, Guangwei; Luo, A-Li; Wu, Yue; Yang, Ming; Zhang, Haotong [Key Lab of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012 (China); Beers, Timothy C. [Department of Physics and JINA: Joint Institute for Nuclear Astrophysics, University of Notre Dame, 225 Nieuwland Science Hall, Notre Dame, IN 46556 (United States); Chen, Li; Hou, Jinliang; Smith, Martin C. [Shanghai Astronomical Observatory, 80 Nandan Road, Shanghai 200030 (China); Guhathakurta, Puragra [UCO/Lick Observatory, Department of Astronomy and Astrophysics, University of California, Santa Cruz, CA 95064 (United States); Hou, Yonghui [Nanjing Institute of Astronomical Optics and Technology, National Astronomical Observatories, Chinese Academy of Sciences, Nanjing 210042 (China); Lépine, Sébastien [Department of Physics and Astronomy, Georgia State University, 25 Park Place, Suite 605, Atlanta, GA 30303 (United States); Yanny, Brian [Fermi National Accelerator Laboratory, P.O. Box 500, Batavia, IL 60510 (United States); Zheng, Zheng, E-mail: jeffreylcarlin@gmail.com [Department of Physics and Astronomy, University of Utah, UT 84112 (United States)

2015-07-15

We present a method to estimate distances to stars with spectroscopically derived stellar parameters. The technique is a Bayesian approach with likelihood estimated via comparison of measured parameters to a grid of stellar isochrones, and returns a posterior probability density function for each star’s absolute magnitude. This technique is tailored specifically to data from the Large Sky Area Multi-object Fiber Spectroscopic Telescope (LAMOST) survey. Because LAMOST obtains roughly 3000 stellar spectra simultaneously within each ∼5° diameter “plate” that is observed, we can use the stellar parameters of the observed stars to account for the stellar luminosity function and target selection effects. This removes biasing assumptions about the underlying populations, both due to predictions of the luminosity function from stellar evolution modeling, and from Galactic models of stellar populations along each line of sight. Using calibration data of stars with known distances and stellar parameters, we show that our method recovers distances for most stars within ∼20%, but with some systematic overestimation of distances to halo giants. We apply our code to the LAMOST database, and show that the current precision of LAMOST stellar parameters permits measurements of distances with ∼40% error bars. This precision should improve as the LAMOST data pipelines continue to be refined.

A relation between the characteristic stellar ages of galaxies and their intrinsic shapes

Science.gov (United States)

van de Sande, Jesse; Scott, Nicholas; Bland-Hawthorn, Joss; Brough, Sarah; Bryant, Julia J.; Colless, Matthew; Cortese, Luca; Croom, Scott M.; d'Eugenio, Francesco; Foster, Caroline; Goodwin, Michael; Konstantopoulos, Iraklis S.; Lawrence, Jon S.; McDermid, Richard M.; Medling, Anne M.; Owers, Matt S.; Richards, Samuel N.; Sharp, Rob

2018-04-01

Stellar population and stellar kinematic studies provide unique but complementary insights into how galaxies build-up their stellar mass and angular momentum1-3. A galaxy's mean stellar age reveals when stars were formed, but provides little constraint on how the galaxy's mass was assembled. Resolved stellar dynamics4 trace the change in angular momentum due to mergers, but major mergers tend to obscure the effect of earlier interactions5. With the rise of large multi-object integral field spectroscopic surveys, such as SAMI6 and MaNGA7, and single-object integral field spectroscopic surveys (for example, ATLAS3D (ref. 8), CALIFA9, MASSIVE10), it is now feasible to connect a galaxy's star formation and merger history on the same resolved physical scales, over a large range in galaxy mass, morphology and environment4,11,12. Using the SAMI Galaxy Survey, here we present a combined study of spatially resolved stellar kinematics and global stellar populations. We find a strong correlation of stellar population age with location in the (V/σ, ɛe) diagram that links the ratio of ordered rotation to random motions in a galaxy to its observed ellipticity. For the large majority of galaxies that are oblate rotating spheroids, we find that characteristic stellar age follows the intrinsic ellipticity of galaxies remarkably well.

A relation between the characteristic stellar ages of galaxies and their intrinsic shapes

Science.gov (United States)

van de Sande, Jesse; Scott, Nicholas; Bland-Hawthorn, Joss; Brough, Sarah; Bryant, Julia J.; Colless, Matthew; Cortese, Luca; Croom, Scott M.; d'Eugenio, Francesco; Foster, Caroline; Goodwin, Michael; Konstantopoulos, Iraklis S.; Lawrence, Jon S.; McDermid, Richard M.; Medling, Anne M.; Owers, Matt S.; Richards, Samuel N.; Sharp, Rob

2018-06-01

Stellar population and stellar kinematic studies provide unique but complementary insights into how galaxies build-up their stellar mass and angular momentum1-3. A galaxy's mean stellar age reveals when stars were formed, but provides little constraint on how the galaxy's mass was assembled. Resolved stellar dynamics4 trace the change in angular momentum due to mergers, but major mergers tend to obscure the effect of earlier interactions5. With the rise of large multi-object integral field spectroscopic surveys, such as SAMI6 and MaNGA7, and single-object integral field spectroscopic surveys (for example, ATLAS3D (ref. 8), CALIFA9, MASSIVE10), it is now feasible to connect a galaxy's star formation and merger history on the same resolved physical scales, over a large range in galaxy mass, morphology and environment4,11,12. Using the SAMI Galaxy Survey, here we present a combined study of spatially resolved stellar kinematics and global stellar populations. We find a strong correlation of stellar population age with location in the (V/σ, ɛe) diagram that links the ratio of ordered rotation to random motions in a galaxy to its observed ellipticity. For the large majority of galaxies that are oblate rotating spheroids, we find that characteristic stellar age follows the intrinsic ellipticity of galaxies remarkably well.

Fast imaging by photon counting application to long-baseline optical stellar interferometry

International Nuclear Information System (INIS)

Morel, Sebastien

1998-01-01

Image acquisition by photon counting in the visible spectrum with a high precision on photo-events dating is especially useful for ground-based observations. In the first part of this thesis, and after a review of several techniques for photon acquisition and processing, I introduce a new type of photon counting camera, noticeable for its high temporal resolution and its high maximum counting rate: the DELTA (Detector Enhancement by Linear-projections on Three Axes) camera. I describe the concept of this camera, and the engineering solutions (optics, electronics, computing) that could be used for its construction. The second part of my work regards fringe detection and tracking in ground-based and long- baseline optical stellar interferometry. After a statistical approach of the issue, I describe methods introducing a priori information in the data, in order to have a better detection efficiency. One of the proposed methods, using a priori information on the atmospheric piston, requires a precise photo-event dating, and therefore uses methods described in the first part. (author) [fr

Wireless Sensor Network Optimization: Multi-Objective Paradigm.

Science.gov (United States)

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-07-20

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.

Wireless Sensor Network Optimization: Multi-Objective Paradigm

Science.gov (United States)

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-01-01

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks. PMID:26205271

Science case and requirements for the MOSAIC concept for a multi-object spectrograph for the European extremely large telescope

International Nuclear Information System (INIS)

Evans, C.J.; Puech, M.; Bonifacio, P.; Hammer, F.; Jagourel, P.; Caffau, E.; Disseau, K.; Flores, H.; Huertas-Company, M.; Mei, S.; Aussel, H.

2014-01-01

Over the past 18 months we have revisited the science requirements for a multi-object spectrograph (MOS) for the European Extremely Large Telescope (E-ELT). These efforts span the full range of E-ELT science and include input from a broad cross-section of astronomers across the ESO partner countries. In this contribution we summarise the key cases relating to studies of high-redshift galaxies, galaxy evolution, and stellar populations, with a more expansive presentation of a new case relating to detection of exoplanets in stellar clusters. A general requirement is the need for two observational modes to best exploit the large (=40 arcmin 2 ) patrol field of the E-ELT. The first mode ('high multiplex') requires integrated-light (or coarsely resolved) optical/near-IR spectroscopy of ≥100 objects simultaneously. The second ('high definition'), enabled by wide-field adaptive optics, requires spatially-resolved, near-IR of ≥10 objects/sub-fields. Within the context of the conceptual study for an ELT-MOS called MOSAIC, we summarise the top level requirements from each case and introduce the next steps in the design process. (authors)

Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

Directory of Open Access Journals (Sweden)

Kaveh Khalili-Damghani

2017-07-01

Full Text Available In this paper a multi-period multi-product multi-objective aggregate production planning (APP model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method.

Multi-objective optimization of linear multi-state multiple sliding window system

International Nuclear Information System (INIS)

Konak, Abdullah; Kulturel-Konak, Sadan; Levitin, Gregory

2012-01-01

This paper considers the optimal element sequencing in a linear multi-state multiple sliding window system that consists of n linearly ordered multi-state elements. Each multi-state element can have different states: from complete failure up to perfect functioning. A performance rate is associated with each state. The failure of type i in the system occurs if for any i (1≤i≤I) the cumulative performance of any r i consecutive elements is lower than w i . The element sequence strongly affects the probability of any type of system failure. The sequence that minimizes the probability of certain type of failure can provide high probability of other types of failures. Therefore the optimization problem for the multiple sliding window system is essentially multi-objective. The paper formulates and solves the multi-objective optimization problem for the multiple sliding window systems. A multi-objective Genetic Algorithm is used as the optimization engine. Illustrative examples are presented.

Imaging of Stellar Surfacess Using Radio Facilities Including ALMA

Science.gov (United States)

O'Gorman, Eamon

2018-04-01

Until very recently, studies focusing on imaging stars at continuum radio wavelengths (here defined as submillimeter, millimeter, and centimeter wavelengths) has been scarce. These studies have mainly been carried out with the Very Large Array on a handful of evolved stars (i.e., Asymptotic Giant Branch and Red Supergiant stars) whereby their stellar disks have just about been spatially resolved. Some of these results however, have challenged our historical views on the nature of evolved star atmospheres. Now, the very long baselines of the Atacama Large Millimeter/submillimeter Array and the newly upgraded Karl G. Jansky Very Large Array provide a new opportunity to image these atmospheres at unprecedented spatial resolution and sensitivity across a much wider portion of the radio spectrum. In this talk I will first provide a history of stellar radio imaging and then discuss some recent exciting ALMA results. Finally I will present some brand new multi-wavelength ALMA and VLA results for the famous red supergiant Antares.

Forest Structure Characterization Using Jpl's UAVSAR Multi-Baseline Polarimetric SAR Interferometry and Tomography

Science.gov (United States)

Neumann, Maxim; Hensley, Scott; Lavalle, Marco; Ahmed, Razi

2013-01-01

This paper concerns forest remote sensing using JPL's multi-baseline polarimetric interferometric UAVSAR data. It presents exemplary results and analyzes the possibilities and limitations of using SAR Tomography and Polarimetric SAR Interferometry (PolInSAR) techniques for the estimation of forest structure. Performance and error indicators for the applicability and reliability of the used multi-baseline (MB) multi-temporal (MT) PolInSAR random volume over ground (RVoG) model are discussed. Experimental results are presented based on JPL's L-band repeat-pass polarimetric interferometric UAVSAR data over temperate and tropical forest biomes in the Harvard Forest, Massachusetts, and in the La Amistad Park, Panama and Costa Rica. The results are partially compared with ground field measurements and with air-borne LVIS lidar data.

Optimizing Stellarators for Turbulent Transport

International Nuclear Information System (INIS)

Mynick, H.E.; Pomphrey, N.; Xanthopoulos, P.

2010-01-01

Up to now, the term 'transport-optimized' stellarators has meant optimized to minimize neoclassical transport, while the task of also mitigating turbulent transport, usually the dominant transport channel in such designs, has not been addressed, due to the complexity of plasma turbulence in stellarators. Here, we demonstrate that stellarators can also be designed to mitigate their turbulent transport, by making use of two powerful numerical tools not available until recently, namely gyrokinetic codes valid for 3D nonlinear simulations, and stellarator optimization codes. A first proof-of-principle configuration is obtained, reducing the level of ion temperature gradient turbulent transport from the NCSX baseline design by a factor of about 2.5.

Multi-Objective Nonlinear Model Predictive Control: Lexicographic Method

OpenAIRE

Zheng, Tao; Wu, Gang; Liu, Guang-Hong; Ling, Qing

2010-01-01

In this chapter, to avoid the disadvantages of weight coefficients in multi-objective dynamic optimization, lexicographic (completely stratified) and partially stratified frameworks of multi-objective controller are proposed. The lexicographic framework is absolutely prioritydriven and the partially stratified framework is a modification of it, they both can solve the multi-objective control problem with the concept of priority for objective’s relative importance, while the latter one is mo...

Constraining Stellar Coronal Mass Ejections through Multi-wavelength Analysis of the Active M Dwarf EQ Peg

Science.gov (United States)

Crosley, M. K.; Osten, R. A.

2018-03-01

Stellar coronal mass ejections remain experimentally unconstrained, unlike their stellar flare counterparts, which are observed ubiquitously across the electromagnetic spectrum. Low-frequency radio bursts in the form of a type II burst offer the best means of identifying and constraining the rate and properties of stellar CMEs. CME properties can be further improved through the use of proposed solar-stellar scaling relations and multi-wavelength observations of CMEs through the use of type II bursts and the associated flares expected to occur alongside them. We report on 20 hr of observation of the nearby, magnetically active, and well-characterized M dwarf star EQ Peg. The observations are simultaneously observed with the Jansky Very Large Array at their P-band (230–470 MHz) and at the Apache Point observatory in the SDSS u‧ filter (λ = 3557 Å). Dynamic spectra of the P-band data, constructed to search for signals in the frequency-time domains, did not reveal evidence of drifting radio bursts that could be ascribed to type II bursts. Given the sensitivity of our observations, we are able to place limits on the brightness temperature and source size of any bursts that may have occurred. Using solar scaling rations on four observed stellar flares, we predict CME parameters. Given the constraints on coronal density and photospheric field strength, our models suggest that the observed flares would have been insufficient to produce detectable type II bursts at our observed frequencies. We consider the implications of these results, and other recent findings, on stellar mass loss.

Multi-objective Transmission Planning Paper

DEFF Research Database (Denmark)

Xu, Zhao; Dong, Zhao Yang; Wong, Kit Po

2009-01-01

This paper describes a transmission expansion planning method based on multi-objective optimization (MOOP). The method starts with constructing a candidate pool of feasible expansion plans, followed by selection of the best candidates through MOOP, of which multiple objectives are tackled...

Fuzzy Multi-objective Linear Programming Approach

Directory of Open Access Journals (Sweden)

Amna Rehmat

2007-07-01

Full Text Available Traveling salesman problem (TSP is one of the challenging real-life problems, attracting researchers of many fields including Artificial Intelligence, Operations Research, and Algorithm Design and Analysis. The problem has been well studied till now under different headings and has been solved with different approaches including genetic algorithms and linear programming. Conventional linear programming is designed to deal with crisp parameters, but information about real life systems is often available in the form of vague descriptions. Fuzzy methods are designed to handle vague terms, and are most suited to finding optimal solutions to problems with vague parameters. Fuzzy multi-objective linear programming, an amalgamation of fuzzy logic and multi-objective linear programming, deals with flexible aspiration levels or goals and fuzzy constraints with acceptable deviations. In this paper, a methodology, for solving a TSP with imprecise parameters, is deployed using fuzzy multi-objective linear programming. An example of TSP with multiple objectives and vague parameters is discussed.

Interactive Approach for Multi-Level Multi-Objective Fractional Programming Problems with Fuzzy Parameters

Directory of Open Access Journals (Sweden)

M.S. Osman

2018-03-01

Full Text Available In this paper, an interactive approach for solving multi-level multi-objective fractional programming (ML-MOFP problems with fuzzy parameters is presented. The proposed interactive approach makes an extended work of Shi and Xia (1997. In the first phase, the numerical crisp model of the ML-MOFP problem has been developed at a confidence level without changing the fuzzy gist of the problem. Then, the linear model for the ML-MOFP problem is formulated. In the second phase, the interactive approach simplifies the linear multi-level multi-objective model by converting it into separate multi-objective programming problems. Also, each separate multi-objective programming problem of the linear model is solved by the ∊-constraint method and the concept of satisfactoriness. Finally, illustrative examples and comparisons with the previous approaches are utilized to evince the feasibility of the proposed approach.

Multi-Objective Optimization of Hybrid Renewable Energy System Using an Enhanced Multi-Objective Evolutionary Algorithm

Directory of Open Access Journals (Sweden)

Mengjun Ming

2017-05-01

Full Text Available Due to the scarcity of conventional energy resources and the greenhouse effect, renewable energies have gained more attention. This paper proposes methods for multi-objective optimal design of hybrid renewable energy system (HRES in both isolated-island and grid-connected modes. In each mode, the optimal design aims to find suitable configurations of photovoltaic (PV panels, wind turbines, batteries and diesel generators in HRES such that the system cost and the fuel emission are minimized, and the system reliability/renewable ability (corresponding to different modes is maximized. To effectively solve this multi-objective problem (MOP, the multi-objective evolutionary algorithm based on decomposition (MOEA/D using localized penalty-based boundary intersection (LPBI method is proposed. The algorithm denoted as MOEA/D-LPBI is demonstrated to outperform its competitors on the HRES model as well as a set of benchmarks. Moreover, it effectively obtains a good approximation of Pareto optimal HRES configurations. By further considering a decision maker’s preference, the most satisfied configuration of the HRES can be identified.

Multi Camera Multi Object Tracking using Block Search over Epipolar Geometry

Directory of Open Access Journals (Sweden)

Saman Sargolzaei

2000-01-01

Full Text Available We present strategy for multi-objects tracking in multi camera environment for the surveillance and security application where tracking multitude subjects are of utmost importance in a crowded scene. Our technique assumes partially overlapped multi-camera setup where cameras share common view from different angle to assess positions and activities of subjects under suspicion. To establish spatial correspondence between camera views we employ an epipolar geometry technique. We propose an overlapped block search method to find the interested pattern (target in new frames. Color pattern update scheme has been considered to further optimize the efficiency of the object tracking when object pattern changes due to object motion in the field of views of the cameras. Evaluation of our approach is presented with the results on PETS2007 dataset..

Object-Location-Aware Hashing for Multi-Label Image Retrieval via Automatic Mask Learning.

Science.gov (United States)

Huang, Chang-Qin; Yang, Shang-Ming; Pan, Yan; Lai, Han-Jiang

2018-09-01

Learning-based hashing is a leading approach of approximate nearest neighbor search for large-scale image retrieval. In this paper, we develop a deep supervised hashing method for multi-label image retrieval, in which we propose to learn a binary "mask" map that can identify the approximate locations of objects in an image, so that we use this binary "mask" map to obtain length-limited hash codes which mainly focus on an image's objects but ignore the background. The proposed deep architecture consists of four parts: 1) a convolutional sub-network to generate effective image features; 2) a binary "mask" sub-network to identify image objects' approximate locations; 3) a weighted average pooling operation based on the binary "mask" to obtain feature representations and hash codes that pay most attention to foreground objects but ignore the background; and 4) the combination of a triplet ranking loss designed to preserve relative similarities among images and a cross entropy loss defined on image labels. We conduct comprehensive evaluations on four multi-label image data sets. The results indicate that the proposed hashing method achieves superior performance gains over the state-of-the-art supervised or unsupervised hashing baselines.

Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

Science.gov (United States)

Lin, Jian-Fu; Xu, You-Lin; Law, Siu-Seong

2018-05-01

A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

Benchmarks for dynamic multi-objective optimisation

CSIR Research Space (South Africa)

Helbig, M

2013-06-01

Full Text Available When algorithms solve dynamic multi-objective optimisation problems (DMOOPs), benchmark functions should be used to determine whether the algorithm can overcome specific difficulties that can occur in real-world problems. However, for dynamic multi...

The Intermediate-mass Young Stellar Object 08576nr292: Discovery of A Disk-Jet System

NARCIS (Netherlands)

Ellerbroek, L.E.; Kaper, L.; Bik, A.; de Koter, A.; Horrobin, M.; Puga, E.; Sana, H.; Waters, L.B.F.M.

2011-01-01

We present observations of the embedded massive young stellar object (YSO) candidate 08576nr292, obtained with X-shooter and SINFONI on the ESO Very Large Telescope (VLT). The flux-calibrated, medium-resolution X-shooter spectrum (300–2500 nm) includes over 300 emission lines, but no (photospheric)

Cosmic-Ray Propagation in Turbulent Spiral Magnetic Fields Associated with Young Stellar Objects

Science.gov (United States)

Fatuzzo, Marco; Adams, Fred C.

2018-04-01

External cosmic rays impinging upon circumstellar disks associated with young stellar objects provide an important source of ionization, and, as such, play an important role in disk evolution and planet formation. However, these incoming cosmic rays are affected by a variety of physical processes internal to stellar/disk systems, including modulation by turbulent magnetic fields. Globally, these fields naturally provide both a funneling effect, where cosmic rays from larger volumes are focused into the disk region, and a magnetic mirroring effect, where cosmic rays are repelled due to the increasing field strength. This paper considers cosmic-ray propagation in the presence of a turbulent spiral magnetic field, analogous to that produced by the solar wind. The interaction of this wind with the interstellar medium defines a transition radius, analogous to the heliopause, which provides the outer boundary to this problem. We construct a new coordinate system where one coordinate follows the spiral magnetic field lines and consider magnetic perturbations to the field in the perpendicular directions. The presence of magnetic turbulence replaces the mirroring points with a distribution of values and moves the mean location outward. Our results thus help quantify the degree to which cosmic-ray fluxes are reduced in circumstellar disks by the presence of magnetic field structures that are shaped by stellar winds. The new coordinate system constructed herein should also be useful in other astronomical applications.

The LAMOST stellar parameter pipeline at Peking University - LSP3

Science.gov (United States)

Xiang, M. S.; Liu, X. W.; Yuan, H. B.; Huang, Y.; Huo, Z. Y.; Zhang, H. W.; Chen, B. Q.; Zhang, H. H.; Sun, N. C.; Wang, C.; Zhao, Y. H.; Shi, J. R.; Luo, A. L.; Li, G. P.; Wu, Y.; Bai, Z. R.; Zhang, Y.; Hou, Y. H.; Yuan, H. L.; Li, G. W.; Wei, Z.

2015-03-01

We introduce the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) stellar parameter pipeline at Peking University - LSP3, developed and implemented for the determinations of radial velocity Vr and stellar atmospheric parameters (effective temperature Teff, surface gravity log g, metallicity [Fe/H]) for the LAMOST Spectroscopic Survey of the Galactic Anticentre (LSS-GAC). We describe the algorithms of LSP3 and examine the accuracy of parameters yielded by it. The precision and accuracy of parameters yielded are investigated by comparing results of multi-epoch observations and of candidate members of open and globular clusters, with photometric calibration, as well as with independent determinations available from a number of external data bases, including the PASTEL archive, the APOGEE, SDSS and RAVE surveys, as well as those released in the LAMOST DR1. The uncertainties of LSP3 parameters are characterized and quantified as a function of the spectral signal-to-noise ratio (SNR) and stellar atmospheric parameters. We conclude that the current implementation of LSP3 has achieved an accuracy of 5.0 km s-1, 150 K, 0.25 dex, 0.15 dex for the radial velocity, effective temperature, surface gravity and metallicity, respectively, for LSS-GAC spectra of FGK stars of SNRs per pixel higher than 10. The LSP3 has been applied to over a million LSS-GAC spectra collected hitherto. Stellar parameters yielded by the LSP3 will be released to the general public following the data policy of LAMOST, together with estimates of the interstellar extinction E(B - V) and stellar distances, deduced by combining spectroscopic and multiband photometric measurements using a variety of techniques.

Multi-sensors multi-baseline mapping system for mobile robot using stereovision camera and laser-range device

Directory of Open Access Journals (Sweden)

Mohammed Faisal

2016-06-01

Full Text Available Countless applications today are using mobile robots, including autonomous navigation, security patrolling, housework, search-and-rescue operations, material handling, manufacturing, and automated transportation systems. Regardless of the application, a mobile robot must use a robust autonomous navigation system. Autonomous navigation remains one of the primary challenges in the mobile-robot industry; many control algorithms and techniques have been recently developed that aim to overcome this challenge. Among autonomous navigation methods, vision-based systems have been growing in recent years due to rapid gains in computational power and the reliability of visual sensors. The primary focus of research into vision-based navigation is to allow a mobile robot to navigate in an unstructured environment without collision. In recent years, several researchers have looked at methods for setting up autonomous mobile robots for navigational tasks. Among these methods, stereovision-based navigation is a promising approach for reliable and efficient navigation. In this article, we create and develop a novel mapping system for a robust autonomous navigation system. The main contribution of this article is the fuse of the multi-baseline stereovision (narrow and wide baselines and laser-range reading data to enhance the accuracy of the point cloud, to reduce the ambiguity of correspondence matching, and to extend the field of view of the proposed mapping system to 180°. Another contribution is the pruning the region of interest of the three-dimensional point clouds to reduce the computational burden involved in the stereo process. Therefore, we called the proposed system multi-sensors multi-baseline mapping system. The experimental results illustrate the robustness and accuracy of the proposed system.

Power magnetic devices a multi-objective design approach

CERN Document Server

Sudhoff, Scott D

2014-01-01

Presents a multi-objective design approach to the many power magnetic devices in use today Power Magnetic Devices: A Multi-Objective Design Approach addresses the design of power magnetic devices-including inductors, transformers, electromagnets, and rotating electric machinery-using a structured design approach based on formal single- and multi-objective optimization. The book opens with a discussion of evolutionary-computing-based optimization. Magnetic analysis techniques useful to the design of all the devices considered in the book are then set forth. This material is then used for ind

YOUNG STELLAR OBJECTS IN THE GOULD BELT

Energy Technology Data Exchange (ETDEWEB)

Dunham, Michael M. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, MS 78, Cambridge, MA 02138 (United States); Allen, Lori E. [National Optical Astronomy Observatories, Tucson, AZ (United States); Evans II, Neal J.; Harvey, Paul M. [Department of Astronomy, The University of Texas at Austin, 2515 Speedway, Stop C1400, Austin, TX 78712-1205 (United States); Broekhoven-Fiene, Hannah [Department of Physics and Astronomy, University of Victoria, Victoria, BC, V8W 3P6 (Canada); Cieza, Lucas A. [Núcleo de Astronomía de la Facultad de Ingeniería, Universidad Diego Portales, Av. Ejército 441, Santiago (Chile); Di Francesco, James; Johnstone, Doug; Matthews, Brenda C. [National Research Council of Canada, Herzberg Astronomy and Astrophysics Programs, 5071 West Saanich Road, Victoria, BC, V9E 2E7 (Canada); Gutermuth, Robert A. [Department of Astronomy, University of Massachusetts, Amherst, MA 01003 (United States); Hatchell, Jennifer [Physics and Astronomy, University of Exeter, Stocker Road, Exeter EX4 4QL (United Kingdom); Heiderman, Amanda [Department of Astronomy, University of Virginia, P.O. Box 400325, Charlottesville, VA 22904 (United States); Huard, Tracy L. [Department of Astronomy, University of Maryland, College Park, MD 20742 (United States); Kirk, Jason M. [Jeremiah Horrocks Institute, University of Central Lancashire, Preston, PR1 2HE (United Kingdom); Miller, Jennifer F. [Gemini Observatory, 670 N. A’ohoku Place, Hilo, HI 96720 (United States); Peterson, Dawn E. [Space Science Institute, 4750 Walnut Street, Suite 205, Boulder, CO 80301 (United States); Young, Kaisa E., E-mail: mdunham@cfa.harvard.edu [Department of Physical Sciences, Nicholls State University, P.O. Box 2022, Thibodaux, LA 70310 (United States)

2015-09-15

We present the full catalog of Young Stellar Objects (YSOs) identified in the 18 molecular clouds surveyed by the Spitzer Space Telescope “cores to disks” (c2d) and “Gould Belt” (GB) Legacy surveys. Using standard techniques developed by the c2d project, we identify 3239 candidate YSOs in the 18 clouds, 2966 of which survive visual inspection and form our final catalog of YSOs in the GB. We compile extinction corrected spectral energy distributions for all 2966 YSOs and calculate and tabulate the infrared spectral index, bolometric luminosity, and bolometric temperature for each object. We find that 326 (11%), 210 (7%), 1248 (42%), and 1182 (40%) are classified as Class 0 + I, Flat-spectrum, Class II, and Class III, respectively, and show that the Class III sample suffers from an overall contamination rate by background Asymptotic Giant Branch stars between 25% and 90%. Adopting standard assumptions, we derive durations of 0.40–0.78 Myr for Class 0 + I YSOs and 0.26–0.50 Myr for Flat-spectrum YSOs, where the ranges encompass uncertainties in the adopted assumptions. Including information from (sub)millimeter wavelengths, one-third of the Class 0 + I sample is classified as Class 0, leading to durations of 0.13–0.26 Myr (Class 0) and 0.27–0.52 Myr (Class I). We revisit infrared color–color diagrams used in the literature to classify YSOs and propose minor revisions to classification boundaries in these diagrams. Finally, we show that the bolometric temperature is a poor discriminator between Class II and Class III YSOs.

YOUNG STELLAR OBJECTS IN THE GOULD BELT

International Nuclear Information System (INIS)

Dunham, Michael M.; Allen, Lori E.; Evans II, Neal J.; Harvey, Paul M.; Broekhoven-Fiene, Hannah; Cieza, Lucas A.; Di Francesco, James; Johnstone, Doug; Matthews, Brenda C.; Gutermuth, Robert A.; Hatchell, Jennifer; Heiderman, Amanda; Huard, Tracy L.; Kirk, Jason M.; Miller, Jennifer F.; Peterson, Dawn E.; Young, Kaisa E.

2015-01-01

We present the full catalog of Young Stellar Objects (YSOs) identified in the 18 molecular clouds surveyed by the Spitzer Space Telescope “cores to disks” (c2d) and “Gould Belt” (GB) Legacy surveys. Using standard techniques developed by the c2d project, we identify 3239 candidate YSOs in the 18 clouds, 2966 of which survive visual inspection and form our final catalog of YSOs in the GB. We compile extinction corrected spectral energy distributions for all 2966 YSOs and calculate and tabulate the infrared spectral index, bolometric luminosity, and bolometric temperature for each object. We find that 326 (11%), 210 (7%), 1248 (42%), and 1182 (40%) are classified as Class 0 + I, Flat-spectrum, Class II, and Class III, respectively, and show that the Class III sample suffers from an overall contamination rate by background Asymptotic Giant Branch stars between 25% and 90%. Adopting standard assumptions, we derive durations of 0.40–0.78 Myr for Class 0 + I YSOs and 0.26–0.50 Myr for Flat-spectrum YSOs, where the ranges encompass uncertainties in the adopted assumptions. Including information from (sub)millimeter wavelengths, one-third of the Class 0 + I sample is classified as Class 0, leading to durations of 0.13–0.26 Myr (Class 0) and 0.27–0.52 Myr (Class I). We revisit infrared color–color diagrams used in the literature to classify YSOs and propose minor revisions to classification boundaries in these diagrams. Finally, we show that the bolometric temperature is a poor discriminator between Class II and Class III YSOs

Stellar structure and compact objects before 1940: Towards relativistic astrophysics

Science.gov (United States)

Bonolis, Luisa

2017-06-01

Since the mid-1920s, different strands of research used stars as "physics laboratories" for investigating the nature of matter under extreme densities and pressures, impossible to realize on Earth. To trace this process this paper is following the evolution of the concept of a dense core in stars, which was important both for an understanding of stellar evolution and as a testing ground for the fast-evolving field of nuclear physics. In spite of the divide between physicists and astrophysicists, some key actors working in the cross-fertilized soil of overlapping but different scientific cultures formulated models and tentative theories that gradually evolved into more realistic and structured astrophysical objects. These investigations culminated in the first contact with general relativity in 1939, when J. Robert Oppenheimer and his students George Volkoff and Hartland Snyder systematically applied the theory to the dense core of a collapsing neutron star. This pioneering application of Einstein's theory to an astrophysical compact object can be regarded as a milestone in the path eventually leading to the emergence of relativistic astrophysics in the early 1960s.

Distribution Network Expansion Planning Based on Multi-objective PSO Algorithm

DEFF Research Database (Denmark)

Zhang, Chunyu; Ding, Yi; Wu, Qiuwei

2013-01-01

This paper presents a novel approach for electrical distribution network expansion planning using multi-objective particle swarm optimization (PSO). The optimization objectives are: investment and operation cost, energy losses cost, and power congestion cost. A two-phase multi-objective PSO...... algorithm was proposed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of both the proposed multi-objective planning approach and the improved multi-objective PSO have been verified...

Interaction effects on galaxy pairs with Gemini/GMOS- III: stellar population synthesis

Science.gov (United States)

Krabbe, A. C.; Rosa, D. A.; Pastoriza, M. G.; Hägele, G. F.; Cardaci, M. V.; Dors, O. L., Jr.; Winge, C.

2017-05-01

We present an observational study of the impacts of interactions on the stellar population in a sample of galaxy pairs. Long-slit spectra in the wavelength range 3440-7300 Å obtained with the Gemini Multi-Object Spectrograph (GMOS) at Gemini South for 15 galaxies in nine close pairs were used. The spatial distributions of the stellar population contributions were obtained using the stellar population synthesis code starlight. Taking into account the different contributions to the emitted light, we found that most of the galaxies in our sample are dominated by young/intermediate stellar populations. This result differs from the one derived for isolated galaxies, where the old stellar population dominates the disc surface brightness. We interpreted such different behaviour as being due to the effect of gas inflows along the discs of interacting galaxies on the star formation over a time-scale of the order of about 2 Gyr. We also found that, in general, the secondary galaxy of a pair has a higher contribution from the young stellar population than the primary one. We compared the estimated values of stellar and nebular extinction derived from the synthesis method and the Hα/Hβ emission-line ratio, finding that nebular extinctions are systematically higher than stellar ones by about a factor of 2. We did not find any correlation between nebular and stellar metallicities. Neither did we find a correlation between stellar metallicities and ages, while a positive correlation between nebular metallicities and stellar ages was obtained, with older regions being the most metal-rich.

Multi-objective congestion management by modified augmented ε-constraint method

International Nuclear Information System (INIS)

Esmaili, Masoud; Shayanfar, Heidar Ali; Amjady, Nima

2011-01-01

Congestion management is a vital part of power system operations in recent deregulated electricity markets. However, after relieving congestion, power systems may be operated with a reduced voltage or transient stability margin because of hitting security limits or increasing the contribution of risky participants. Therefore, power system stability margins should be considered within the congestion management framework. The multi-objective congestion management provides not only more security but also more flexibility than single-objective methods. In this paper, a multi-objective congestion management framework is presented while simultaneously optimizing the competing objective functions of congestion management cost, voltage security, and dynamic security. The proposed multi-objective framework, called modified augmented ε-constraint method, is based on the augmented ε-constraint technique hybridized by the weighting method. The proposed framework generates candidate solutions for the multi-objective problem including only efficient Pareto surface enhancing the competitiveness and economic effectiveness of the power market. Besides, the relative importance of the objective functions is explicitly modeled in the proposed framework. Results of testing the proposed multi-objective congestion management method on the New-England test system are presented and compared with those of the previous single objective and multi-objective techniques in detail. These comparisons confirm the efficiency of the developed method. (author)

Multi-objective compared to single-objective optimization with application to model validation and uncertainty quantification

Energy Technology Data Exchange (ETDEWEB)

Schulze-Riegert, R.; Krosche, M.; Stekolschikov, K. [Scandpower Petroleum Technology GmbH, Hamburg (Germany); Fahimuddin, A. [Technische Univ. Braunschweig (Germany)

2007-09-13

History Matching in Reservoir Simulation, well location and production optimization etc. is generally a multi-objective optimization problem. The problem statement of history matching for a realistic field case includes many field and well measurements in time and type, e.g. pressure measurements, fluid rates, events such as water and gas break-throughs, etc. Uncertainty parameters modified as part of the history matching process have varying impact on the improvement of the match criteria. Competing match criteria often reduce the likelihood of finding an acceptable history match. It is an engineering challenge in manual history matching processes to identify competing objectives and to implement the changes required in the simulation model. In production optimization or scenario optimization the focus on one key optimization criterion such as NPV limits the identification of alternatives and potential opportunities, since multiple objectives are summarized in a predefined global objective formulation. Previous works primarily focus on a specific optimization method. Few works actually concentrate on the objective formulation and multi-objective optimization schemes have not yet been applied to reservoir simulations. This paper presents a multi-objective optimization approach applicable to reservoir simulation. It addresses the problem of multi-objective criteria in a history matching study and presents analysis techniques identifying competing match criteria. A Pareto-Optimizer is discussed and the implementation of that multi-objective optimization scheme is applied to a case study. Results are compared to a single-objective optimization method. (orig.)

Aerodynamic multi-objective integrated optimization based on principal component analysis

Directory of Open Access Journals (Sweden)

Jiangtao HUANG

2017-08-01

Full Text Available Based on improved multi-objective particle swarm optimization (MOPSO algorithm with principal component analysis (PCA methodology, an efficient high-dimension multi-objective optimization method is proposed, which, as the purpose of this paper, aims to improve the convergence of Pareto front in multi-objective optimization design. The mathematical efficiency, the physical reasonableness and the reliability in dealing with redundant objectives of PCA are verified by typical DTLZ5 test function and multi-objective correlation analysis of supercritical airfoil, and the proposed method is integrated into aircraft multi-disciplinary design (AMDEsign platform, which contains aerodynamics, stealth and structure weight analysis and optimization module. Then the proposed method is used for the multi-point integrated aerodynamic optimization of a wide-body passenger aircraft, in which the redundant objectives identified by PCA are transformed to optimization constraints, and several design methods are compared. The design results illustrate that the strategy used in this paper is sufficient and multi-point design requirements of the passenger aircraft are reached. The visualization level of non-dominant Pareto set is improved by effectively reducing the dimension without losing the primary feature of the problem.

Multi-objective optimization using genetic algorithms: A tutorial

International Nuclear Information System (INIS)

Konak, Abdullah; Coit, David W.; Smith, Alice E.

2006-01-01

Multi-objective formulations are realistic models for many complex engineering optimization problems. In many real-life problems, objectives under consideration conflict with each other, and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other objectives. A reasonable solution to a multi-objective problem is to investigate a set of solutions, each of which satisfies the objectives at an acceptable level without being dominated by any other solution. In this paper, an overview and tutorial is presented describing genetic algorithms (GA) developed specifically for problems with multiple objectives. They differ primarily from traditional GA by using specialized fitness functions and introducing methods to promote solution diversity

THE ENVIRONMENTS OF HIGH-REDSHIFT QUASI-STELLAR OBJECTS

International Nuclear Information System (INIS)

Kim, Soyoung; Stiavelli, Massimo; Trenti, M.; Pavlovsky, C. M.; Djorgovski, S. G.; Scarlata, C.; Stern, D.; Mahabal, A.; Thompson, D.; Panagia, N.; Dickinson, M.; Meylan, G.

2009-01-01

We present a sample of i 775 -dropout candidates identified in five Hubble Advanced Camera for Surveys (ACS) fields centered on Sloan Digital Sky Survey quasi-stellar objects (QSOs) at redshift z ∼ 6. Our fields are as deep as the GOODS ACS images, which are used as a reference field sample. We find them to be overdense in two fields, underdense in two fields, and as dense as the average density of GOODS in one field. The two excess fields show significantly different color distributions from that of GOODS at the 99% confidence level, strengthening the idea that the excess objects are indeed associated with the QSO. The distribution of i 775 -dropout counts in the five fields is broader than that derived from GOODS at the 80%-96% confidence level, depending on which selection criteria were adopted to identify i 775 -dropouts; its width cannot be explained by cosmic variance alone. Thus, QSOs seem to affect their environments in complex ways. We suggest the picture where the highest redshift QSOs are located in very massive overdensities and are therefore surrounded by an overdensity of lower mass halos. Radiative feedback by the QSO can in some cases prevent halos from becoming galaxies, thereby generating in extreme cases an underdensity of galaxies. The presence of both enhancement and suppression is compatible with the expected differences between lines of sight at the end of reionization as the presence of residual diffuse neutral hydrogen would provide young galaxies with shielding from the radiative effects of the QSO.

A publication database for optical long baseline interferometry

Science.gov (United States)

Malbet, Fabien; Mella, Guillaume; Lawson, Peter; Taillifet, Esther; Lafrasse, Sylvain

2010-07-01

Optical long baseline interferometry is a technique that has generated almost 850 refereed papers to date. The targets span a large variety of objects from planetary systems to extragalactic studies and all branches of stellar physics. We have created a database hosted by the JMMC and connected to the Optical Long Baseline Interferometry Newsletter (OLBIN) web site using MySQL and a collection of XML or PHP scripts in order to store and classify these publications. Each entry is defined by its ADS bibcode, includes basic ADS informations and metadata. The metadata are specified by tags sorted in categories: interferometric facilities, instrumentation, wavelength of operation, spectral resolution, type of measurement, target type, and paper category, for example. The whole OLBIN publication list has been processed and we present how the database is organized and can be accessed. We use this tool to generate statistical plots of interest for the community in optical long baseline interferometry.

Future prospects for stellar intensity interferometry

International Nuclear Information System (INIS)

Lake, R.J.W.

2002-01-01

Full text: The technique of Stellar Intensity lnterferometry (SII) was first successfully demonstrated by Hanbury-Brown in 1956 at Jodrell Bank. SII uses the correlation in intensity fluctuations of starlight as a function of observational baseline to determine angular diameters and other gross features of main sequence stars. In 1962 an observatory was established by Hanbury-Brown in Narrabri NSW. Between 1965 and 1972 the angular diameters of 32 stars covering the spectral range O to F were measured. Orbital parameters of several unresolved binary stars were also determined and attempts were made by the author to directly measure the limb darkening of Sirius and the rotational distortion of Altair. Following the success of the Narrabri SII the Australian Federal Government provided a grant to Sydney University to develop a Very Large SII capable of making observational measurements on about a thousand stars. The development of this VLSII was however shelved in preference to the development of a potentially more sensitive long baseline Michelson Stellar Interferometer. This latter instrument known as SUSI (Sydney University Stellar Interferometer) has been in operation at Narrabri since 1995. Encouraged by the early results of SUSI and their own efforts in the use of active optics to reduce the effects of atmospheric scintillation a number of international observatories are now active in the development of long baseline or large aperture Michelson Stellar Interferometers. However SII while sacrificing sensitivity has a number of technical advantages over MSI as SII is far less sensitive to atmospheric effects and can be readily developed to work over very long baselines. This paper through technical review and theoretical modeling examines how a modern VLSII could be constructed and operated and addresses the limitations to its sensitivity. In particular it examines how existing Australian industry could contribute to the development of a VLSII with sufficient

Multi-criteria objective based climate change impact assessment for multi-purpose multi-reservoir systems

Science.gov (United States)

Müller, Ruben; Schütze, Niels

2014-05-01

Water resources systems with reservoirs are expected to be sensitive to climate change. Assessment studies that analyze the impact of climate change on the performance of reservoirs can be divided in two groups: (1) Studies that simulate the operation under projected inflows with the current set of operational rules. Due to non adapted operational rules the future performance of these reservoirs can be underestimated and the impact overestimated. (2) Studies that optimize the operational rules for best adaption of the system to the projected conditions before the assessment of the impact. The latter allows for estimating more realistically future performance and adaption strategies based on new operation rules are available if required. Multi-purpose reservoirs serve various, often conflicting functions. If all functions cannot be served simultaneously at a maximum level, an effective compromise between multiple objectives of the reservoir operation has to be provided. Yet under climate change the historically preferenced compromise may no longer be the most suitable compromise in the future. Therefore a multi-objective based climate change impact assessment approach for multi-purpose multi-reservoir systems is proposed in the study. Projected inflows are provided in a first step using a physically based rainfall-runoff model. In a second step, a time series model is applied to generate long-term inflow time series. Finally, the long-term inflow series are used as driving variables for a simulation-based multi-objective optimization of the reservoir system in order to derive optimal operation rules. As a result, the adapted Pareto-optimal set of diverse best compromise solutions can be presented to the decision maker in order to assist him in assessing climate change adaption measures with respect to the future performance of the multi-purpose reservoir system. The approach is tested on a multi-purpose multi-reservoir system in a mountainous catchment in Germany. A

Multi-objective differential evolution with adaptive Cauchy mutation for short-term multi-objective optimal hydro-thermal scheduling

Energy Technology Data Exchange (ETDEWEB)

Qin Hui [College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China); Zhou Jianzhong, E-mail: jz.zhou@hust.edu.c [College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China); Lu Youlin; Wang Ying; Zhang Yongchuan [College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China)

2010-04-15

A new multi-objective optimization method based on differential evolution with adaptive Cauchy mutation (MODE-ACM) is presented to solve short-term multi-objective optimal hydro-thermal scheduling (MOOHS) problem. Besides fuel cost, the pollutant gas emission is also optimized as an objective. The water transport delay between connected reservoirs and the effect of valve-point loading of thermal units are also taken into account in the presented problem formulation. The proposed algorithm adopts an elitist archive to retain non-dominated solutions obtained during the evolutionary process. It modifies the DE's operators to make it suit for multi-objective optimization (MOO) problems and improve its performance. Furthermore, to avoid premature convergence, an adaptive Cauchy mutation is proposed to preserve the diversity of population. An effective constraints handling method is utilized to handle the complex equality and inequality constraints. The effectiveness of the proposed algorithm is tested on a hydro-thermal system consisting of four cascaded hydro plants and three thermal units. The results obtained by MODE-ACM are compared with several previous studies. It is found that the results obtained by MODE-ACM are superior in terms of fuel cost as well as emission output, consuming a shorter time. Thus it can be a viable alternative to generate optimal trade-offs for short-term MOOHS problem.

Multi-objective optimization of inverse planning for accurate radiotherapy

International Nuclear Information System (INIS)

Cao Ruifen; Pei Xi; Cheng Mengyun; Li Gui; Hu Liqin; Wu Yican; Jing Jia; Li Guoli

2011-01-01

The multi-objective optimization of inverse planning based on the Pareto solution set, according to the multi-objective character of inverse planning in accurate radiotherapy, was studied in this paper. Firstly, the clinical requirements of a treatment plan were transformed into a multi-objective optimization problem with multiple constraints. Then, the fast and elitist multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) was introduced to optimize the problem. A clinical example was tested using this method. The results show that an obtained set of non-dominated solutions were uniformly distributed and the corresponding dose distribution of each solution not only approached the expected dose distribution, but also met the dose-volume constraints. It was indicated that the clinical requirements were better satisfied using the method and the planner could select the optimal treatment plan from the non-dominated solution set. (authors)

QUASI-STELLAR OBJECT SELECTION ALGORITHM USING TIME VARIABILITY AND MACHINE LEARNING: SELECTION OF 1620 QUASI-STELLAR OBJECT CANDIDATES FROM MACHO LARGE MAGELLANIC CLOUD DATABASE

International Nuclear Information System (INIS)

Kim, Dae-Won; Protopapas, Pavlos; Alcock, Charles; Trichas, Markos; Byun, Yong-Ik; Khardon, Roni

2011-01-01

We present a new quasi-stellar object (QSO) selection algorithm using a Support Vector Machine, a supervised classification method, on a set of extracted time series features including period, amplitude, color, and autocorrelation value. We train a model that separates QSOs from variable stars, non-variable stars, and microlensing events using 58 known QSOs, 1629 variable stars, and 4288 non-variables in the MAssive Compact Halo Object (MACHO) database as a training set. To estimate the efficiency and the accuracy of the model, we perform a cross-validation test using the training set. The test shows that the model correctly identifies ∼80% of known QSOs with a 25% false-positive rate. The majority of the false positives are Be stars. We applied the trained model to the MACHO Large Magellanic Cloud (LMC) data set, which consists of 40 million light curves, and found 1620 QSO candidates. During the selection none of the 33,242 known MACHO variables were misclassified as QSO candidates. In order to estimate the true false-positive rate, we crossmatched the candidates with astronomical catalogs including the Spitzer Surveying the Agents of a Galaxy's Evolution LMC catalog and a few X-ray catalogs. The results further suggest that the majority of the candidates, more than 70%, are QSOs.

The Stellar Imager (SI) Project: Resolving Stellar Surfaces, Interiors, and Magnetic Activity

Science.gov (United States)

Carpenter, Kenneth G.; Schrijver, K.; Karovska, M.

2007-01-01

The Stellar Imager (SI) is a UV/Optical. Space-Based Interferometer designed to enable 0.1 milli-arcsec (mas) spectral imaging of stellar surfaces and, via asteroseismology, stellar interiors and of the Universe in general. The ultra-sharp images of SI will revolutionize our view of many dynamic astrophysical processes by transforming point sources into extended sources, and snapshots into evolving views. The science of SI focuses on the role of magnetism in the Universe, particularly on magnetic activity on the surfaces of stars like the Sun. Its prime goal is to enable long-term forecasting of solar activity and the space weather that it drives. SI will also revolutionize our understanding of the formation of planetary systems, of the habitability and climatology of distant planets, and of many magneto-hydrodynamically controlled processes in the Universe. In this paper we discuss the science goals, technology needs, and baseline design of the SI mission.

YOUNG STELLAR OBJECTS IN THE MASSIVE STAR-FORMING REGION W49

Energy Technology Data Exchange (ETDEWEB)

Saral, G.; Hora, J. L.; Willis, S. E. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Koenig, X. P. [Yale University, Department of Astronomy, 208101, New Haven, CT 06520-8101 (United States); Gutermuth, R. A. [University of Massachusetts, Department of Astronomy, Amherst, MA 01003 (United States); Saygac, A. T., E-mail: gsaral@cfa.harvard.edu [Istanbul University, Faculty of Science, Astronomy and Space Sciences Department, Istanbul-Turkey (Turkey)

2015-11-01

We present the initial results of our investigation of the star-forming complex W49, one of the youngest and most luminous massive star-forming regions in our Galaxy. We used Spitzer/Infrared Array Camera (IRAC) data to investigate massive star formation with the primary objective of locating a representative set of protostars and the clusters of young stars that are forming around them. We present our source catalog with the mosaics from the IRAC data. In this study we used a combination of IRAC, MIPS, Two Micron All Sky Survey, and UKIRT Deep Infrared Sky Survey (UKIDSS) data to identify and classify the young stellar objects (YSOs). We identified 232 Class 0/I YSOs, 907 Class II YSOs, and 74 transition disk candidate objects using color–color and color–magnitude diagrams. In addition, to understand the evolution of star formation in W49, we analyzed the distribution of YSOs in the region to identify clusters using a minimal spanning tree method. The fraction of YSOs that belong to clusters with ≥7 members is found to be 52% for a cutoff distance of 96″, and the ratio of Class II/I objects is 2.1. We compared the W49 region to the G305 and G333 star-forming regions and concluded that W49 has the richest population, with seven subclusters of YSOs.

Convex hull ranking algorithm for multi-objective evolutionary algorithms

NARCIS (Netherlands)

Davoodi Monfrared, M.; Mohades, A.; Rezaei, J.

2012-01-01

Due to many applications of multi-objective evolutionary algorithms in real world optimization problems, several studies have been done to improve these algorithms in recent years. Since most multi-objective evolutionary algorithms are based on the non-dominated principle, and their complexity

HUBBLE SPACE TELESCOPE NICMOS POLARIZATION OBSERVATIONS OF THREE EDGE-ON MASSIVE YOUNG STELLAR OBJECTS

International Nuclear Information System (INIS)

Simpson, Janet P.; Colgan, Sean W. J.; Erickson, Edwin F.; Burton, Michael G.; Cotera, Angela S.; Hines, Dean C.; Whitney, Barbara A.

2009-01-01

Massive young stellar objects (YSOs), like low-mass YSOs, appear to be surrounded by optically thick envelopes and/or disks and have regions, often bipolar, that are seen in polarized scattered light at near-infrared wavelengths. We are using the 0.''2 spatial resolution of the Near Infrared Camera and Multi-Object Spectrometer (NICMOS) on Hubble Space Telescope to examine the structure of the disks and outflow regions of massive YSOs in star-forming regions within a few kpc of the Sun. Here we report on 2 μm polarimetry of NGC 6334 V and S255 IRS1. NGC 6334 V consists of a double-lobed bright reflection nebula seen against a dark region, probably an optically thick molecular cloud. Our polarization measurements show that the illuminating star lies ∼2'' south of the line connecting the two lobes; we do not detect this star at 2 μm, but there are a small radio source and a mid-infrared source at this location. S255 IRS1 consists of two YSOs (NIRS1 and NIRS3) with overlapping scattered light lobes and luminosities corresponding to early B stars. Included in IRS1 is a cluster of stars from whose polarization we determine the local magnetic field direction. Neither of the YSOs has its scattered light lobes aligned with this magnetic field. The line connecting the scattered light lobes of NIRS1 is twisted symmetrically around the star; the best explanation is that the star is part of a close binary and the outflow axis of NIRS1 is precessing as a result of non-coplanar disk and orbit. The star NIRS3 is also offset from the line connecting its two scattered light lobes. We suggest that all three YSOs show evidence of episodic ejection of material as they accrete from dense, optically thick envelopes.

Enhanced Multi-Objective Energy Optimization by a Signaling Method

OpenAIRE

Soares, João; Borges, Nuno; Vale, Zita; Oliveira, P.B.

2016-01-01

In this paper three metaheuristics are used to solve a smart grid multi-objective energy management problem with conflictive design: how to maximize profits and minimize carbon dioxide (CO2) emissions, and the results compared. The metaheuristics implemented are: weighted particle swarm optimization (W-PSO), multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II). The performance of these methods with the use of multi-dimensi...

Complex organic molecules in organic-poor massive young stellar objects

DEFF Research Database (Denmark)

Fayolle, Edith C.; Öberg, Karin I.; Garrod, Robin T.

2015-01-01

to search for complex organic molecules over 8-16 GHz in the 1 mm atmospheric window toward three MYSOs with known ice abundances, but without luminous molecular hot cores. Results. Complex molecules are detected toward all three sources at comparable abundances with respect to CH3OH to classical hot core......Context. Massive young stellar objects (MYSOs) with hot cores are classic sources of complex organic molecules. The origins of these molecules in such sources, as well as the small-and large-scale differentiation between nitrogen-and oxygen-bearing complex species, are poorly understood. Aims. We...... aim to use complex molecule abundances toward a chemically less explored class of MYSOs with weak hot organic emission lines to constrain the impact of hot molecular cores and initial ice conditions on the chemical composition toward MYSOs. Methods. We use the IRAM 30 m and the Submillimeter Array...

MOPSO-based multi-objective TSO planning considering uncertainties

DEFF Research Database (Denmark)

Wang, Qi; Zhang, Chunyu; Ding, Yi

2014-01-01

factors, i.e. load growth, generation capacity and line faults, and aims to enhance the transmission system via the multi-objective TSO planning (MOTP) approach. The proposed MOTP approach optimizes three objectives simultaneously, namely the probabilistic available transfer capability (PATC), investment...... cost and power outage cost. A two-phase MOPSO algorithm is employed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity ofPareto-optimal front set as well. The feasibility and effectiveness of both the proposed multi-objective planning approach...

A procedure for multi-objective optimization of tire design parameters

Directory of Open Access Journals (Sweden)

Nikola Korunović

2015-04-01

Full Text Available The identification of optimal tire design parameters for satisfying different requirements, i.e. tire performance characteristics, plays an essential role in tire design. In order to improve tire performance characteristics, formulation and solving of multi-objective optimization problem must be performed. This paper presents a multi-objective optimization procedure for determination of optimal tire design parameters for simultaneous minimization of strain energy density at two distinctive zones inside the tire. It consists of four main stages: pre-analysis, design of experiment, mathematical modeling and multi-objective optimization. Advantage of the proposed procedure is reflected in the fact that multi-objective optimization is based on the Pareto concept, which enables design engineers to obtain a complete set of optimization solutions and choose a suitable tire design. Furthermore, modeling of the relationships between tire design parameters and objective functions based on multiple regression analysis minimizes computational and modeling effort. The adequacy of the proposed tire design multi-objective optimization procedure has been validated by performing experimental trials based on finite element method.

Connected Component Model for Multi-Object Tracking.

Science.gov (United States)

He, Zhenyu; Li, Xin; You, Xinge; Tao, Dacheng; Tang, Yuan Yan

2016-08-01

In multi-object tracking, it is critical to explore the data associations by exploiting the temporal information from a sequence of frames rather than the information from the adjacent two frames. Since straightforwardly obtaining data associations from multi-frames is an NP-hard multi-dimensional assignment (MDA) problem, most existing methods solve this MDA problem by either developing complicated approximate algorithms, or simplifying MDA as a 2D assignment problem based upon the information extracted only from adjacent frames. In this paper, we show that the relation between associations of two observations is the equivalence relation in the data association problem, based on the spatial-temporal constraint that the trajectories of different objects must be disjoint. Therefore, the MDA problem can be equivalently divided into independent subproblems by equivalence partitioning. In contrast to existing works for solving the MDA problem, we develop a connected component model (CCM) by exploiting the constraints of the data association and the equivalence relation on the constraints. Based upon CCM, we can efficiently obtain the global solution of the MDA problem for multi-object tracking by optimizing a sequence of independent data association subproblems. Experiments on challenging public data sets demonstrate that our algorithm outperforms the state-of-the-art approaches.

New approach for solving intuitionistic fuzzy multi-objective ...

Indian Academy of Sciences (India)

SANKAR KUMAR ROY

2018-02-07

Feb 7, 2018 ... Transportation problem; multi-objective decision making; intuitionistic fuzzy programming; interval programming ... MOTP under multi-choice environment using utility func- ... theory is an intuitionistic fuzzy set (IFS), which was.

Multiple utility constrained multi-objective programs using Bayesian theory

Science.gov (United States)

Abbasian, Pooneh; Mahdavi-Amiri, Nezam; Fazlollahtabar, Hamed

2018-03-01

A utility function is an important tool for representing a DM's preference. We adjoin utility functions to multi-objective optimization problems. In current studies, usually one utility function is used for each objective function. Situations may arise for a goal to have multiple utility functions. Here, we consider a constrained multi-objective problem with each objective having multiple utility functions. We induce the probability of the utilities for each objective function using Bayesian theory. Illustrative examples considering dependence and independence of variables are worked through to demonstrate the usefulness of the proposed model.

Warm gas towards young stellar objects in Corona Australis. Herschel/PACS observations from the DIGIT key programme

Science.gov (United States)

Lindberg, Johan E.; Jørgensen, Jes K.; Green, Joel D.; Herczeg, Gregory J.; Dionatos, Odysseas; Evans, Neal J.; Karska, Agata; Wampfler, Susanne F.

2014-05-01

Context. The effects of external irradiation on the chemistry and physics in the protostellar envelope around low-mass young stellar objects are poorly understood. The Corona Australis star-forming region contains the R CrA dark cloud, comprising several low-mass protostellar cores irradiated by an intermediate-mass young star. Aims: We study the effects of the irradiation coming from the young luminous Herbig Be star R CrA on the warm gas and dust in a group of low-mass young stellar objects. Methods: Herschel/PACS far-infrared datacubes of two low-mass star-forming regions in the R CrA dark cloud are presented. The distributions of CO, OH, H2O, [C ii], [O i], and continuum emission are investigated. We have developed a deconvolution algorithm which we use to deconvolve the maps, separating the point-source emission from the extended emission. We also construct rotational diagrams of the molecular species. Results: By deconvolution of the Herschel data, we find large-scale (several thousand AU) dust continuum and spectral line emission not associated with the point sources. Similar rotational temperatures are found for the warm CO (282 ± 4 K), hot CO (890 ± 84 K), OH (79 ± 4 K), and H2O (197 ± 7 K) emission in the point sources and the extended emission. The rotational temperatures are also similar to those found in other more isolated cores. The extended dust continuum emission is found in two ridges similar in extent and temperature to molecular millimetre emission, indicative of external heating from the Herbig Be star R CrA. Conclusions: Our results show that nearby luminous stars do not increase the molecular excitation temperatures of the warm gas around young stellar objects (YSOs). However, the emission from photodissociation products of H2O, such as OH and O, is enhanced in the warm gas associated with these protostars and their surroundings compared to similar objects not subjected to external irradiation. Table 9 and appendices are available in

A FEATURE MOVIE OF SiO EMISSION 20-100 AU FROM THE MASSIVE YOUNG STELLAR OBJECT ORION SOURCE I

International Nuclear Information System (INIS)

Matthews, L. D.; Greenhill, L. J.; Goddi, C.; Humphreys, E. M. L.; Chandler, C. J.; Kunz, M. W.

2010-01-01

We present multi-epoch Very Long Baseline Array imaging of the 28 SiO v = 1 and v = 2, J = 1-0 maser emission toward the massive young stellar object (YSO) Orion Source I. Both SiO transitions were observed simultaneously with an angular resolution of ∼0.5 mas (∼0.2 AU for d = 414 pc) and a spectral resolution of ∼0.2 km s -1 . Here we explore the global properties and kinematics of the emission through two 19-epoch animated movies spanning 21 months (from 2001 March 19 to 2002 December 10). These movies provide the most detailed view to date of the dynamics and temporal evolution of molecular material within ∼20-100 AU of a massive (∼>8 M sun ) YSO. As in previous studies, we find that the bulk of the SiO masers surrounding Source I lie in an X-shaped locus; the emission in the south and east arms is predominantly blueshifted, and emission in the north and west is predominantly redshifted. In addition, bridges of intermediate-velocity emission are observed connecting the red and blue sides of the emission distribution. We have measured proper motions of over 1000 individual maser features and found that these motions are characterized by a combination of radially outward migrations along the four main maser-emitting arms and motions tangent to the intermediate-velocity bridges. We interpret the SiO masers as arising from a wide-angle bipolar wind emanating from a rotating, edge-on disk. The detection of maser features along extended, curved filaments suggests that magnetic fields may play a role in launching and/or shaping the wind. Our observations appear to support a picture in which stars with masses as high as at least 8 M sun form via disk-mediated accretion. However, we cannot yet rule out that the Source I disk may have been formed or altered following a recent close encounter.

Multi-Objective Optimization of Start-up Strategy for Pumped Storage Units

Directory of Open Access Journals (Sweden)

Jinjiao Hou

2018-05-01

Full Text Available This paper proposes a multi-objective optimization method for the start-up strategy of pumped storage units (PSU for the first time. In the multi-objective optimization method, the speed rise time and the overshoot during the process of the start-up are taken as the objectives. A precise simulation platform is built for simulating the transient process of start-up, and for calculating the objectives based on the process. The Multi-objective Particle Swarm Optimization algorithm (MOPSO is adopted to optimize the widely applied start-up strategies based on one-stage direct guide vane control (DGVC, and two-stage DGVC. Based on the Pareto Front obtained, a multi-objective decision-making method based on the relative objective proximity is used to sort the solutions in the Pareto Front. Start-up strategy optimization for a PSU of a pumped storage power station in Jiangxi Province in China is conducted in experiments. The results show that: (1 compared with the single objective optimization, the proposed multi-objective optimization of start-up strategy not only greatly shortens the speed rise time and the speed overshoot, but also makes the speed curve quickly stabilize; (2 multi-objective optimization of strategy based on two-stage DGVC achieves better solution for a quick and smooth start-up of PSU than that of the strategy based on one-stage DGVC.

Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics.

Science.gov (United States)

Trianni, Vito; López-Ibáñez, Manuel

2015-01-01

The application of multi-objective optimisation to evolutionary robotics is receiving increasing attention. A survey of the literature reveals the different possibilities it offers to improve the automatic design of efficient and adaptive robotic systems, and points to the successful demonstrations available for both task-specific and task-agnostic approaches (i.e., with or without reference to the specific design problem to be tackled). However, the advantages of multi-objective approaches over single-objective ones have not been clearly spelled out and experimentally demonstrated. This paper fills this gap for task-specific approaches: starting from well-known results in multi-objective optimisation, we discuss how to tackle commonly recognised problems in evolutionary robotics. In particular, we show that multi-objective optimisation (i) allows evolving a more varied set of behaviours by exploring multiple trade-offs of the objectives to optimise, (ii) supports the evolution of the desired behaviour through the introduction of objectives as proxies, (iii) avoids the premature convergence to local optima possibly introduced by multi-component fitness functions, and (iv) solves the bootstrap problem exploiting ancillary objectives to guide evolution in the early phases. We present an experimental demonstration of these benefits in three different case studies: maze navigation in a single robot domain, flocking in a swarm robotics context, and a strictly collaborative task in collective robotics.

Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics.

Directory of Open Access Journals (Sweden)

Vito Trianni

Full Text Available The application of multi-objective optimisation to evolutionary robotics is receiving increasing attention. A survey of the literature reveals the different possibilities it offers to improve the automatic design of efficient and adaptive robotic systems, and points to the successful demonstrations available for both task-specific and task-agnostic approaches (i.e., with or without reference to the specific design problem to be tackled. However, the advantages of multi-objective approaches over single-objective ones have not been clearly spelled out and experimentally demonstrated. This paper fills this gap for task-specific approaches: starting from well-known results in multi-objective optimisation, we discuss how to tackle commonly recognised problems in evolutionary robotics. In particular, we show that multi-objective optimisation (i allows evolving a more varied set of behaviours by exploring multiple trade-offs of the objectives to optimise, (ii supports the evolution of the desired behaviour through the introduction of objectives as proxies, (iii avoids the premature convergence to local optima possibly introduced by multi-component fitness functions, and (iv solves the bootstrap problem exploiting ancillary objectives to guide evolution in the early phases. We present an experimental demonstration of these benefits in three different case studies: maze navigation in a single robot domain, flocking in a swarm robotics context, and a strictly collaborative task in collective robotics.

The Environments of High-Redshift Quasi-Stellar Objects

Science.gov (United States)

Kim, Soyoung; Stiavelli, Massimo; Trenti, M.; Pavlovsky, C. M.; Djorgovski, S. G.; Scarlata, C.; Stern, D.; Mahabal, A.; Thompson, D.; Dickinson, M.; Panagia, N.; Meylan, G.

2009-04-01

We present a sample of i 775-dropout candidates identified in five Hubble Advanced Camera for Surveys (ACS) fields centered on Sloan Digital Sky Survey quasi-stellar objects (QSOs) at redshift z ~ 6. Our fields are as deep as the GOODS ACS images, which are used as a reference field sample. We find them to be overdense in two fields, underdense in two fields, and as dense as the average density of GOODS in one field. The two excess fields show significantly different color distributions from that of GOODS at the 99% confidence level, strengthening the idea that the excess objects are indeed associated with the QSO. The distribution of i 775-dropout counts in the five fields is broader than that derived from GOODS at the 80%-96% confidence level, depending on which selection criteria were adopted to identify i 775-dropouts; its width cannot be explained by cosmic variance alone. Thus, QSOs seem to affect their environments in complex ways. We suggest the picture where the highest redshift QSOs are located in very massive overdensities and are therefore surrounded by an overdensity of lower mass halos. Radiative feedback by the QSO can in some cases prevent halos from becoming galaxies, thereby generating in extreme cases an underdensity of galaxies. The presence of both enhancement and suppression is compatible with the expected differences between lines of sight at the end of reionization as the presence of residual diffuse neutral hydrogen would provide young galaxies with shielding from the radiative effects of the QSO. Based on observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities of Research in Astronomy, Inc., under NASA contract NAS5-26555.

Multi-Label Object Categorization Using Histograms of Global Relations

DEFF Research Database (Denmark)

Mustafa, Wail; Xiong, Hanchen; Kraft, Dirk

2015-01-01

In this paper, we present an object categorization system capable of assigning multiple and related categories for novel objects using multi-label learning. In this system, objects are described using global geometric relations of 3D features. We propose using the Joint SVM method for learning......). The experiments are carried out on a dataset of 100 objects belonging to 13 visual and action-related categories. The results indicate that multi-label methods are able to identify the relation between the dependent categories and hence perform categorization accordingly. It is also found that extracting...

Multi-objective optimization in computer networks using metaheuristics

CERN Document Server

Donoso, Yezid

2007-01-01

Metaheuristics are widely used to solve important practical combinatorial optimization problems. Many new multicast applications emerging from the Internet-such as TV over the Internet, radio over the Internet, and multipoint video streaming-require reduced bandwidth consumption, end-to-end delay, and packet loss ratio. It is necessary to design and to provide for these kinds of applications as well as for those resources necessary for functionality. Multi-Objective Optimization in Computer Networks Using Metaheuristics provides a solution to the multi-objective problem in routing computer networks. It analyzes layer 3 (IP), layer 2 (MPLS), and layer 1 (GMPLS and wireless functions). In particular, it assesses basic optimization concepts, as well as several techniques and algorithms for the search of minimals; examines the basic multi-objective optimization concepts and the way to solve them through traditional techniques and through several metaheuristics; and demonstrates how to analytically model the compu...

Multi-objective convex programming problem arising in multivariate ...

African Journals Online (AJOL)

user

Multi-objective convex programming problem arising in ... However, although the consideration of multiple objectives may seem a novel concept, virtually any nontrivial ..... Solving multiobjective programming problems by discrete optimization.

X-shooter spectroscopy of young stellar objects in Lupus. Atmospheric parameters, membership, and activity diagnostics

Science.gov (United States)

Frasca, A.; Biazzo, K.; Alcalá, J. M.; Manara, C. F.; Stelzer, B.; Covino, E.; Antoniucci, S.

2017-06-01

Aims: A homogeneous determination of basic stellar parameters of young stellar object (YSO) candidates is needed to confirm their pre-main sequence evolutionary stage and membership to star forming regions (SFRs), and to get reliable values of the quantities related to chromospheric activity and accretion. Methods: We used the code ROTFIT and synthetic BT-Settl spectra for the determination of the atmospheric parameters (Teff and log g), veiling (r), radial (RV), and projected rotational velocity (vsini) from X-shooter spectra of 102 YSO candidates (95 of infrared Class II and seven Class III) in the Lupus SFR. The spectral subtraction of inactive templates, rotationally broadened to match the vsini of the targets, enabled us to measure the line fluxes for several diagnostics of both chromospheric activity and accretion, such as Hα, Hβ, Ca II, and Na I lines. Results: We have shown that 13 candidates can be rejected as Lupus members based on their discrepant RV with respect to Lupus and/or the very low log g values. At least 11 of them are background giants, two of which turned out to be lithium-rich giants. Regarding the members, we found that all Class III sources have Hα fluxes that are compatible with a pure chromospheric activity, while objects with disks lie mostly above the boundary between chromospheres and accretion. Young stellar objects with transitional disks display both high and low Hα fluxes. We found that the line fluxes per unit surface are tightly correlated with the accretion luminosity (Lacc) derived from the Balmer continuum excess. This rules out that the relationships between Lacc and line luminosities found in previous works are simply due to calibration effects. We also found that the Ca II-IRT flux ratio, FCaII8542/FCaII8498, is always small, indicating an optically thick emission source. The latter can be identified with the accretion shock near the stellar photosphere. The Balmer decrement reaches instead, for several accretors, high

Recent advances in evolutionary multi-objective optimization

CERN Document Server

Datta, Rituparna; Gupta, Abhishek

2017-01-01

This book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-andcoming scientists towards exciting prospects at the forefront of computational intelligence, the authors have made an effort to ensure that the ideas conveyed herein are accessible to the widest audience. The book begins with a summary of the basic concepts in multi-objective optimization. This is followed by brief discussions on various algorithms that have been proposed over the years for solving such problems, ranging from classical (mathematical) approaches to sophisticated evolutionary ones that are capable of seamlessly tackling practical challenges such as non-convexity, multi-modality, the presence of multiple constraints, etc. Thereafter, some of the key emerging aspects that are likely to shape future research directions in the field are presented. These include:< optimization in dynamic environments, multi-objective bilevel programming, handling high ...

A Search for Water Maser Emission from Brown Dwarfs and Low-luminosity Young Stellar Objects

Energy Technology Data Exchange (ETDEWEB)

Gómez, José F.; Manjarrez, Guillermo [Instituto de Astrofísica de Andalucía, CSIC, Glorieta de la Astronomía s/n, E-18008 Granada (Spain); Palau, Aina [Instituto de Radioastronomía y Astrofísica, UNAM, P.O. Box 3-72, 58090, Morelia, Michoacán, México (Mexico); Uscanga, Lucero [Departamento de Astronomía, Universidad de Guanajuato, A.P. 144, 36000 Guanajuato, Gto., México (Mexico); Barrado, David, E-mail: jfg@iaa.es [Centro de Astrobiología, INTA-CSIC, PO BOX 28692, ESAC Campus, E-208691 Villanueva de la Cañada, Madrid (Spain)

2017-05-01

We present a survey for water maser emission toward a sample of 44 low-luminosity young objects, comprising (proto-)brown dwarfs, first hydrostatic cores (FHCs), and other young stellar objects (YSOs) with bolometric luminosities lower than 0.4 L {sub ⊙}. Water maser emission is a good tracer of energetic processes, such as mass-loss and/or accretion, and is a useful tool to study these processes with very high angular resolution. This type of emission has been confirmed in objects with L {sub bol} ≳ 1 L {sub ⊙}. Objects with lower luminosities also undergo mass-loss and accretion, and thus, are prospective sites of maser emission. Our sensitive single-dish observations provided a single detection when pointing toward the FHC L1448 IRS 2E. However, follow-up interferometric observations showed water maser emission associated with the nearby YSO L1448 IRS 2 (a Class 0 protostar of L {sub bol} ≃ 3.6–5.3 L {sub ⊙}) and did not find any emission toward L1448 IRS 2E. The upper limits for water maser emission determined by our observations are one order of magnitude lower than expected from the correlation between water maser luminosities and bolometric luminosities found for YSOs. This suggests that this correlation does not hold at the lower end of the (sub)stellar mass spectrum. Possible reasons are that the slope of this correlation is steeper at L {sub bol} ≤ 1 L {sub ⊙} or that there is an absolute luminosity threshold below which water maser emission cannot be produced. Alternatively, if the correlation still stands at low luminosity, the detection rates of masers would be significantly lower than the values obtained in higher-luminosity Class 0 protostars.

Searching for the Pareto frontier in multi-objective protein design.

Science.gov (United States)

Nanda, Vikas; Belure, Sandeep V; Shir, Ofer M

2017-08-01

The goal of protein engineering and design is to identify sequences that adopt three-dimensional structures of desired function. Often, this is treated as a single-objective optimization problem, identifying the sequence-structure solution with the lowest computed free energy of folding. However, many design problems are multi-state, multi-specificity, or otherwise require concurrent optimization of multiple objectives. There may be tradeoffs among objectives, where improving one feature requires compromising another. The challenge lies in determining solutions that are part of the Pareto optimal set-designs where no further improvement can be achieved in any of the objectives without degrading one of the others. Pareto optimality problems are found in all areas of study, from economics to engineering to biology, and computational methods have been developed specifically to identify the Pareto frontier. We review progress in multi-objective protein design, the development of Pareto optimization methods, and present a specific case study using multi-objective optimization methods to model the tradeoff between three parameters, stability, specificity, and complexity, of a set of interacting synthetic collagen peptides.

Observations of Young Stellar Objects with Infrared Interferometry: Recent Results from PTI, KI and IOTA

Science.gov (United States)

Akeson, Rachel

Young stellar objects have been one of the favorite targets of infrared interferometers for many years. In this contribution I will briefly review some of the first results and their contributions to the field and then describe some of the recent results from the Keck Interferometer (KI), the Palomar Testbed Interferometer (PTI) and the Infrared-Optical Telescope Array (IOTA). This conference also saw many exciting new results from the VLTI at both near and mid-infrared wavelengths that are covered by other contributions.

Surveying the agents of galaxy evolution in the tidally stripped, low metallicity small Magellanic Cloud (SAGE-SMC). III. Young stellar objects

International Nuclear Information System (INIS)

Sewiło, M.; Carlson, L. R.; Seale, J. P.; Meixner, M.; Gordon, K.; Shiao, B.

2013-01-01

The Spitzer Space Telescope Legacy Program SAGE-SMC allows global studies of resolved stellar populations in the SMC in a different environment than our Galaxy. Using the SAGE-SMC IRAC (3.6-8.0 μm) and MIPS (24 and 70 μm) catalogs and images combined with near-infrared (JHK s ) and optical (UBVI) data, we identified a population of ∼1000 intermediate- to high-mass young stellar objects (YSOs) in the SMC (three times more than previously known). Our method of identifying YSO candidates builds on the method developed for the Large Magellanic Cloud by Whitney et al. with improvements based on what we learned from our subsequent studies and techniques described in the literature. We perform (1) color-magnitude cuts based on five color-magnitude diagrams (CMDs), (2) visual inspection of multi-wavelength images, and (3) spectral energy distribution (SED) fitting with YSO models. For each YSO candidate, we use its photometry to calculate a measure of our confidence that the source is not a non-YSO contaminant, but rather a true YSO, based on the source's location in the color-magnitude space with respect to non-YSOs. We use this CMD score and the SED fitting results to define two classes of sources: high-reliability YSO candidates and possible YSO candidates. We found that, due to polycyclic aromatic hydrocarbon emission, about half of our sources have [3.6]-[4.5] and [4.5]-[5.8] colors not predicted by previous YSO models. The YSO candidates are spatially correlated with gas tracers.

Surveying the agents of galaxy evolution in the tidally stripped, low metallicity small Magellanic Cloud (SAGE-SMC). III. Young stellar objects

Energy Technology Data Exchange (ETDEWEB)

Sewiło, M. [The Johns Hopkins University, Department of Physics and Astronomy, 366 Bloomberg Center, 3400 N. Charles Street, Baltimore, MD 21218 (United States); Carlson, L. R. [Sterrewacht Leiden, Leiden University, P.O. Box 9513, 2300 RA Leiden (Netherlands); Seale, J. P.; Meixner, M.; Gordon, K.; Shiao, B., E-mail: mmsewilo@pha.jhu.edu, E-mail: carlson@strw.leidenuniv.nl, E-mail: seale@stsci.edu, E-mail: meixner@stsci.edu, E-mail: kgordon@stsci.edu, E-mail: shiao@stsci.edu [Space Telescope Science Institute, 3700 San Martin Dr., Baltimore, MD 21218 (United States); and others

2013-11-20

The Spitzer Space Telescope Legacy Program SAGE-SMC allows global studies of resolved stellar populations in the SMC in a different environment than our Galaxy. Using the SAGE-SMC IRAC (3.6-8.0 μm) and MIPS (24 and 70 μm) catalogs and images combined with near-infrared (JHK {sub s}) and optical (UBVI) data, we identified a population of ∼1000 intermediate- to high-mass young stellar objects (YSOs) in the SMC (three times more than previously known). Our method of identifying YSO candidates builds on the method developed for the Large Magellanic Cloud by Whitney et al. with improvements based on what we learned from our subsequent studies and techniques described in the literature. We perform (1) color-magnitude cuts based on five color-magnitude diagrams (CMDs), (2) visual inspection of multi-wavelength images, and (3) spectral energy distribution (SED) fitting with YSO models. For each YSO candidate, we use its photometry to calculate a measure of our confidence that the source is not a non-YSO contaminant, but rather a true YSO, based on the source's location in the color-magnitude space with respect to non-YSOs. We use this CMD score and the SED fitting results to define two classes of sources: high-reliability YSO candidates and possible YSO candidates. We found that, due to polycyclic aromatic hydrocarbon emission, about half of our sources have [3.6]-[4.5] and [4.5]-[5.8] colors not predicted by previous YSO models. The YSO candidates are spatially correlated with gas tracers.

A Spectroscopic Study of Young Stellar Objects in the Serpens Cloud Core and NGC 1333

Science.gov (United States)

Winston, E.; Megeath, S. T.; Wolk, S. J.; Hernandez, J.; Gutermuth, R.; Muzerolle, J.; Hora, J. L.; Covey, K.; Allen, L. E.; Spitzbart, B.; Peterson, D.; Myers, P.; Fazio, G. G.

2009-06-01

We present spectral observations of 130 young stellar objects (YSOs) in the Serpens Cloud Core and NGC 1333 embedded clusters. The observations consist of near-IR spectra in the H and K bands from SpeX on the IRTF and far-red spectra (6000-9000 Å) from Hectospec on the Multi-Mirror Telescope. These YSOs were identified in previous Spitzer and Chandra observations, and the evolutionary classes of the YSOs were determined from the Spitzer mid-IR photometry. With these spectra we search for corroborating evidence for the pre-main-sequence nature of the objects, study the properties of the detected emission lines as a function of evolutionary class, and obtain spectral types for the observed YSOs. The temperatures implied by the spectral types are combined with luminosities determined from the near-IR photometry to construct Hertzsprung-Russell (H-R) diagrams for the clusters. By comparing the positions of the YSOs in the H-R diagrams with the pre-main-sequence tracks of Baraffe (1998), we determine the ages of the embedded sources and study the relative ages of the YSOs with and without optically thick circumstellar disks. The apparent isochronal ages of the YSOs in both clusters range from less than 1 Myr to 10 Myr, with most objects below 3 Myr. The observed distributions of ages for the Class II and Class III objects are statistically indistinguishable. We examine the spatial distribution and extinction of the YSOs as a function of their isochronal ages. We find the sources dispersed and are not deeply embedded. Nonetheless, the sources with isochronal ages >3 Myr show all the characteristics of YSOs in their spectra, their IR spectral energy distributions, and their X-ray emission; we find no evidence that they are contaminating background giants or foreground dwarfs. However, we find no corresponding decrease in the fraction of sources with infrared excess with isochronal age; this suggests that the older isochronal ages may not measure the true age of the >3

DiFX: A software correlator for very long baseline interferometry using multi-processor computing environments

OpenAIRE

Deller, A. T.; Tingay, S. J.; Bailes, M.; West, C.

2007-01-01

We describe the development of an FX style correlator for Very Long Baseline Interferometry (VLBI), implemented in software and intended to run in multi-processor computing environments, such as large clusters of commodity machines (Beowulf clusters) or computers specifically designed for high performance computing, such as multi-processor shared-memory machines. We outline the scientific and practical benefits for VLBI correlation, these chiefly being due to the inherent flexibility of softw...

EIT image regularization by a new Multi-Objective Simulated Annealing algorithm.

Science.gov (United States)

Castro Martins, Thiago; Sales Guerra Tsuzuki, Marcos

2015-01-01

Multi-Objective Optimization can be used to produce regularized Electrical Impedance Tomography (EIT) images where the weight of the regularization term is not known a priori. This paper proposes a novel Multi-Objective Optimization algorithm based on Simulated Annealing tailored for EIT image reconstruction. Images are reconstructed from experimental data and compared with images from other Multi and Single Objective optimization methods. A significant performance enhancement from traditional techniques can be inferred from the results.

Recent advances in non-LTE stellar atmosphere models

Science.gov (United States)

Sander, Andreas A. C.

2017-11-01

In the last decades, stellar atmosphere models have become a key tool in understanding massive stars. Applied for spectroscopic analysis, these models provide quantitative information on stellar wind properties as well as fundamental stellar parameters. The intricate non-LTE conditions in stellar winds dictate the development of adequate sophisticated model atmosphere codes. The increase in both, the computational power and our understanding of physical processes in stellar atmospheres, led to an increasing complexity in the models. As a result, codes emerged that can tackle a wide range of stellar and wind parameters. After a brief address of the fundamentals of stellar atmosphere modeling, the current stage of clumped and line-blanketed model atmospheres will be discussed. Finally, the path for the next generation of stellar atmosphere models will be outlined. Apart from discussing multi-dimensional approaches, I will emphasize on the coupling of hydrodynamics with a sophisticated treatment of the radiative transfer. This next generation of models will be able to predict wind parameters from first principles, which could open new doors for our understanding of the various facets of massive star physics, evolution, and death.

The “Building Blocks” of Stellar Halos

Directory of Open Access Journals (Sweden)

Kyle A. Oman

2017-08-01

Full Text Available The stellar halos of galaxies encode their accretion histories. In particular, the median metallicity of a halo is determined primarily by the mass of the most massive accreted object. We use hydrodynamical cosmological simulations from the apostle project to study the connection between the stellar mass, the metallicity distribution, and the stellar age distribution of a halo and the identity of its most massive progenitor. We find that the stellar populations in an accreted halo typically resemble the old stellar populations in a present-day dwarf galaxy with a stellar mass ∼0.2–0.5 dex greater than that of the stellar halo. This suggests that had they not been accreted, the primary progenitors of stellar halos would have evolved to resemble typical nearby dwarf irregulars.

Stellar Absorption Line Analysis of Local Star-forming Galaxies: The Relation between Stellar Mass, Metallicity, Dust Attenuation, and Star Formation Rate

Energy Technology Data Exchange (ETDEWEB)

Jabran Zahid, H. [Smithsonian Astrophysical Observatory, Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Kudritzki, Rolf-Peter; Ho, I-Ting [University of Hawaii at Manoa, Institute for Astronomy, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States); Conroy, Charlie [Department of Astronomy, Harvard University, Cambridge, MA, 02138 (United States); Andrews, Brett, E-mail: zahid@cfa.harvard.edu [PITT PACC, Department of Physics and Astronomy, University of Pittsburgh, 3941 O’Hara Street, Pittsburgh, PA 15260 (United States)

2017-09-20

We analyze the optical continuum of star-forming galaxies in the Sloan Digital Sky Survey by fitting stacked spectra with stellar population synthesis models to investigate the relation between stellar mass, stellar metallicity, dust attenuation, and star formation rate. We fit models calculated with star formation and chemical evolution histories that are derived empirically from multi-epoch observations of the stellar mass–star formation rate and the stellar mass–gas-phase metallicity relations, respectively. We also fit linear combinations of single-burst models with a range of metallicities and ages. Star formation and chemical evolution histories are unconstrained for these models. The stellar mass–stellar metallicity relations obtained from the two methods agree with the relation measured from individual supergiant stars in nearby galaxies. These relations are also consistent with the relation obtained from emission-line analysis of gas-phase metallicity after accounting for systematic offsets in the gas-phase metallicity. We measure dust attenuation of the stellar continuum and show that its dependence on stellar mass and star formation rate is consistent with previously reported results derived from nebular emission lines. However, stellar continuum attenuation is smaller than nebular emission line attenuation. The continuum-to-nebular attenuation ratio depends on stellar mass and is smaller in more massive galaxies. Our consistent analysis of stellar continuum and nebular emission lines paves the way for a comprehensive investigation of stellar metallicities of star-forming and quiescent galaxies.

Stellar Absorption Line Analysis of Local Star-forming Galaxies: The Relation between Stellar Mass, Metallicity, Dust Attenuation, and Star Formation Rate

International Nuclear Information System (INIS)

Jabran Zahid, H.; Kudritzki, Rolf-Peter; Ho, I-Ting; Conroy, Charlie; Andrews, Brett

2017-01-01

We analyze the optical continuum of star-forming galaxies in the Sloan Digital Sky Survey by fitting stacked spectra with stellar population synthesis models to investigate the relation between stellar mass, stellar metallicity, dust attenuation, and star formation rate. We fit models calculated with star formation and chemical evolution histories that are derived empirically from multi-epoch observations of the stellar mass–star formation rate and the stellar mass–gas-phase metallicity relations, respectively. We also fit linear combinations of single-burst models with a range of metallicities and ages. Star formation and chemical evolution histories are unconstrained for these models. The stellar mass–stellar metallicity relations obtained from the two methods agree with the relation measured from individual supergiant stars in nearby galaxies. These relations are also consistent with the relation obtained from emission-line analysis of gas-phase metallicity after accounting for systematic offsets in the gas-phase metallicity. We measure dust attenuation of the stellar continuum and show that its dependence on stellar mass and star formation rate is consistent with previously reported results derived from nebular emission lines. However, stellar continuum attenuation is smaller than nebular emission line attenuation. The continuum-to-nebular attenuation ratio depends on stellar mass and is smaller in more massive galaxies. Our consistent analysis of stellar continuum and nebular emission lines paves the way for a comprehensive investigation of stellar metallicities of star-forming and quiescent galaxies.

The Dynamic Multi-objective Multi-vehicle Covering Tour Problem

Science.gov (United States)

2013-06-01

144 [38] Coello, Carlos A. Coello, Gary B Lamont, and David A Van Veldhuizen . Evolutionary Algorithms for Solving Multi-Objective Problems. Springer...Traveling Repairperson Problem (DTRP) Policies Proposed by Bertsimas and Van Ryzin. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.3...queuing theory perspective. Table 3.2: DTRP Policies Proposed by Bertsimas and Van Ryzin. Name Description First Come First Serve (FCFS) vehicles

Stellar remnants

CERN Document Server

Kawaler, S D; Srinivasan, G

1997-01-01

This volume examines the internal structure, origin and evolution of white dwarfs, neutron stars and black holes, all objects at the final stage of stellar evolution. It covers topics such as: pulsation of white dwarfs; millisecond pulsars; and the dynamics around black holes.

Multi-objective Optimization of Departure Procedures at Gimpo International Airport

Science.gov (United States)

Kim, Junghyun; Lim, Dongwook; Monteiro, Dylan Jonathan; Kirby, Michelle; Mavris, Dimitri

2018-04-01

Most aviation communities have increasing concerns about the environmental impacts, which are directly linked to health issues for local residents near the airport. In this study, the environmental impact of different departure procedures using the Aviation Environmental Design Tool (AEDT) was analyzed. First, actual operational data were compiled at Gimpo International Airport (March 20, 2017) from an open source. Two modifications were made in the AEDT to model the operational circumstances better and the preliminary AEDT simulations were performed according to the acquired operational procedures. Simulated noise results showed good agreements with noise measurement data at specific locations. Second, a multi-objective optimization of departure procedures was performed for the Boeing 737-800. Four design variables were selected and AEDT was linked to a variety of advanced design methods. The results showed that takeoff thrust had the greatest influence and it was found that fuel burn and noise had an inverse relationship. Two points representing each fuel burn and noise optimum on the Pareto front were parsed and run in AEDT to compare with the baseline. The results showed that the noise optimum case reduced Sound Exposure Level 80-dB noise exposure area by approximately 5% while the fuel burn optimum case reduced total fuel burn by 1% relative to the baseline for aircraft-level analysis.

Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

Energy Technology Data Exchange (ETDEWEB)

Kumar, Ranjan [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: ranjan.k@ks3.ecs.kyoto-u.ac.jp; Izui, Kazuhiro [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: izui@prec.kyoto-u.ac.jp; Yoshimura, Masataka [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: yoshimura@prec.kyoto-u.ac.jp; Nishiwaki, Shinji [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: shinji@prec.kyoto-u.ac.jp

2009-04-15

Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets.

Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

International Nuclear Information System (INIS)

Kumar, Ranjan; Izui, Kazuhiro; Yoshimura, Masataka; Nishiwaki, Shinji

2009-01-01

Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets

Interactive Preference Learning of Utility Functions for Multi-Objective Optimization

OpenAIRE

Dewancker, Ian; McCourt, Michael; Ainsworth, Samuel

2016-01-01

Real-world engineering systems are typically compared and contrasted using multiple metrics. For practical machine learning systems, performance tuning is often more nuanced than minimizing a single expected loss objective, and it may be more realistically discussed as a multi-objective optimization problem. We propose a novel generative model for scalar-valued utility functions to capture human preferences in a multi-objective optimization setting. We also outline an interactive active learn...

Multi-objective evolutionary algorithms for fuzzy classification in survival prediction.

Science.gov (United States)

Jiménez, Fernando; Sánchez, Gracia; Juárez, José M

2014-03-01

This paper presents a novel rule-based fuzzy classification methodology for survival/mortality prediction in severe burnt patients. Due to the ethical aspects involved in this medical scenario, physicians tend not to accept a computer-based evaluation unless they understand why and how such a recommendation is given. Therefore, any fuzzy classifier model must be both accurate and interpretable. The proposed methodology is a three-step process: (1) multi-objective constrained optimization of a patient's data set, using Pareto-based elitist multi-objective evolutionary algorithms to maximize accuracy and minimize the complexity (number of rules) of classifiers, subject to interpretability constraints; this step produces a set of alternative (Pareto) classifiers; (2) linguistic labeling, which assigns a linguistic label to each fuzzy set of the classifiers; this step is essential to the interpretability of the classifiers; (3) decision making, whereby a classifier is chosen, if it is satisfactory, according to the preferences of the decision maker. If no classifier is satisfactory for the decision maker, the process starts again in step (1) with a different input parameter set. The performance of three multi-objective evolutionary algorithms, niched pre-selection multi-objective algorithm, elitist Pareto-based multi-objective evolutionary algorithm for diversity reinforcement (ENORA) and the non-dominated sorting genetic algorithm (NSGA-II), was tested using a patient's data set from an intensive care burn unit and a standard machine learning data set from an standard machine learning repository. The results are compared using the hypervolume multi-objective metric. Besides, the results have been compared with other non-evolutionary techniques and validated with a multi-objective cross-validation technique. Our proposal improves the classification rate obtained by other non-evolutionary techniques (decision trees, artificial neural networks, Naive Bayes, and case

Stellar oscillations in planet-hosting giant stars

Energy Technology Data Exchange (ETDEWEB)

Hatzes, Artie P; Zechmeister, Mathias [Thueringer Landessternwarte, Sternwarte 5, D-07778 (Germany)], E-mail: artie@tls-tautenburg.de

2008-10-15

Recently a number of giant extrasolar planets have been discovered around giant stars. These discoveries are important because many of these giant stars have intermediate masses in the range 1.2-3 Msun. Early-type main sequence stars of this mass range have been avoided by radial velocity planet search surveys due the difficulty of getting the requisite radial velocity precision needed for planet discoveries. Thus, giant stars can tell us about planet formation for stars more massive than the sun. However, the determination of stellar masses for giant stars is difficult due to the fact that evolutionary tracks for stars covering a wide range of masses converge to the same region of the H-R diagram. We report here on stellar oscillations in three planet-hosting giant stars: HD 13189, {beta} Gem, and {iota} Dra. Precise stellar radial velocity measurements for these stars show variations whose periods and amplitudes are consistent with solar-like p-mode oscillations. The implied stellar masses for these objects based on the characteristics of the stellar oscillations are consistent with the predictions of stellar isochrones. An investigation of stellar oscillations in planet hosting giant stars offers us the possibility of getting an independent determination of the stellar mass for these objects which is of crucial importance for extrasolar planet studies.

Baseline process description for simulating plutonium oxide production for precalc project

Energy Technology Data Exchange (ETDEWEB)

Pike, J. A. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

2017-10-26

Savannah River National Laboratory (SRNL) started a multi-year project, the PreCalc Project, to develop a computational simulation of a plutonium oxide (PuO₂) production facility with the objective to study the fundamental relationships between morphological and physicochemical properties. This report provides a detailed baseline process description to be used by SRNL personnel and collaborators to facilitate the initial design and construction of the simulation. The PreCalc Project team selected the HB-Line Plutonium Finishing Facility as the basis for a nominal baseline process since the facility is operational and significant model validation data can be obtained. The process boundary as well as process and facility design details necessary for multi-scale, multi-physics models are provided.

Stable numerical method in computation of stellar evolution

International Nuclear Information System (INIS)

Sugimoto, Daiichiro; Eriguchi, Yoshiharu; Nomoto, Ken-ichi.

1982-01-01

To compute the stellar structure and evolution in different stages, such as (1) red-giant stars in which the density and density gradient change over quite wide ranges, (2) rapid evolution with neutrino loss or unstable nuclear flashes, (3) hydrodynamical stages of star formation or supernova explosion, (4) transition phases from quasi-static to dynamical evolutions, (5) mass-accreting or losing stars in binary-star systems, and (6) evolution of stellar core whose mass is increasing by shell burning or decreasing by penetration of convective envelope into the core, we face ''multi-timescale problems'' which can neither be treated by simple-minded explicit scheme nor implicit one. This problem has been resolved by three prescriptions; one by introducing the hybrid scheme suitable for the multi-timescale problems of quasi-static evolution with heat transport, another by introducing also the hybrid scheme suitable for the multi-timescale problems of hydrodynamic evolution, and the other by introducing the Eulerian or, in other words, the mass fraction coordinate for evolution with changing mass. When all of them are combined in a single computer code, we can compute numerically stably any phase of stellar evolution including transition phases, as far as the star is spherically symmetric. (author)

A Bayesian alternative for multi-objective ecohydrological model specification

Science.gov (United States)

Tang, Yating; Marshall, Lucy; Sharma, Ashish; Ajami, Hoori

2018-01-01

Recent studies have identified the importance of vegetation processes in terrestrial hydrologic systems. Process-based ecohydrological models combine hydrological, physical, biochemical and ecological processes of the catchments, and as such are generally more complex and parametric than conceptual hydrological models. Thus, appropriate calibration objectives and model uncertainty analysis are essential for ecohydrological modeling. In recent years, Bayesian inference has become one of the most popular tools for quantifying the uncertainties in hydrological modeling with the development of Markov chain Monte Carlo (MCMC) techniques. The Bayesian approach offers an appealing alternative to traditional multi-objective hydrologic model calibrations by defining proper prior distributions that can be considered analogous to the ad-hoc weighting often prescribed in multi-objective calibration. Our study aims to develop appropriate prior distributions and likelihood functions that minimize the model uncertainties and bias within a Bayesian ecohydrological modeling framework based on a traditional Pareto-based model calibration technique. In our study, a Pareto-based multi-objective optimization and a formal Bayesian framework are implemented in a conceptual ecohydrological model that combines a hydrological model (HYMOD) and a modified Bucket Grassland Model (BGM). Simulations focused on one objective (streamflow/LAI) and multiple objectives (streamflow and LAI) with different emphasis defined via the prior distribution of the model error parameters. Results show more reliable outputs for both predicted streamflow and LAI using Bayesian multi-objective calibration with specified prior distributions for error parameters based on results from the Pareto front in the ecohydrological modeling. The methodology implemented here provides insight into the usefulness of multiobjective Bayesian calibration for ecohydrologic systems and the importance of appropriate prior

Optimization of multi-objective micro-grid based on improved particle swarm optimization algorithm

Science.gov (United States)

Zhang, Jian; Gan, Yang

2018-04-01

The paper presents a multi-objective optimal configuration model for independent micro-grid with the aim of economy and environmental protection. The Pareto solution set can be obtained by solving the multi-objective optimization configuration model of micro-grid with the improved particle swarm algorithm. The feasibility of the improved particle swarm optimization algorithm for multi-objective model is verified, which provides an important reference for multi-objective optimization of independent micro-grid.

Application of Multi-Objective Human Learning Optimization Method to Solve AC/DC Multi-Objective Optimal Power Flow Problem

Science.gov (United States)

Cao, Jia; Yan, Zheng; He, Guangyu

2016-06-01

This paper introduces an efficient algorithm, multi-objective human learning optimization method (MOHLO), to solve AC/DC multi-objective optimal power flow problem (MOPF). Firstly, the model of AC/DC MOPF including wind farms is constructed, where includes three objective functions, operating cost, power loss, and pollutant emission. Combining the non-dominated sorting technique and the crowding distance index, the MOHLO method can be derived, which involves individual learning operator, social learning operator, random exploration learning operator and adaptive strategies. Both the proposed MOHLO method and non-dominated sorting genetic algorithm II (NSGAII) are tested on an improved IEEE 30-bus AC/DC hybrid system. Simulation results show that MOHLO method has excellent search efficiency and the powerful ability of searching optimal. Above all, MOHLO method can obtain more complete pareto front than that by NSGAII method. However, how to choose the optimal solution from pareto front depends mainly on the decision makers who stand from the economic point of view or from the energy saving and emission reduction point of view.

An improved fast and elitist multi-objective genetic algorithm-ANSGA-II for multi-objective optimization of inverse radiotherapy treatment planning

International Nuclear Information System (INIS)

Cao Ruifen; Li Guoli; Song Gang; Zhao Pan; Lin Hui; Wu Aidong; Huang Chenyu; Wu Yican

2007-01-01

Objective: To provide a fast and effective multi-objective optimization algorithm for inverse radiotherapy treatment planning system. Methods: Non-dominated Sorting Genetic Algorithm-NSGA-II is a representative of multi-objective evolutionary optimization algorithms and excels the others. The paper produces ANSGA-II that makes use of advantage of NSGA-II, and uses adaptive crossover and mutation to improve its flexibility; according the character of inverse radiotherapy treatment planning, the paper uses the pre-known knowledge to generate individuals of every generation in the course of optimization, which enhances the convergent speed and improves efficiency. Results: The example of optimizing average dose of a sheet of CT, including PTV, OAR, NT, proves the algorithm could find satisfied solutions in several minutes. Conclusions: The algorithm could provide clinic inverse radiotherapy treatment planning system with selection of optimization algorithms. (authors)

Stellar Streams Discovered in the Dark Energy Survey

Energy Technology Data Exchange (ETDEWEB)

Shipp, N.; et al.

2018-01-09

We perform a search for stellar streams around the Milky Way using the first three years of multi-band optical imaging data from the Dark Energy Survey (DES). We use DES data covering $\\sim 5000$ sq. deg. to a depth of $g > 23.5$ with a relative photometric calibration uncertainty of $< 1 \\%$. This data set yields unprecedented sensitivity to the stellar density field in the southern celestial hemisphere, enabling the detection of faint stellar streams to a heliocentric distance of $\\sim 50$ kpc. We search for stellar streams using a matched-filter in color-magnitude space derived from a synthetic isochrone of an old, metal-poor stellar population. Our detection technique recovers four previously known thin stellar streams: Phoenix, ATLAS, Tucana III, and a possible extension of Molonglo. In addition, we report the discovery of eleven new stellar streams. In general, the new streams detected by DES are fainter, more distant, and lower surface brightness than streams detected by similar techniques in previous photometric surveys. As a by-product of our stellar stream search, we find evidence for extra-tidal stellar structure associated with four globular clusters: NGC 288, NGC 1261, NGC 1851, and NGC 1904. The ever-growing sample of stellar streams will provide insight into the formation of the Galactic stellar halo, the Milky Way gravitational potential, as well as the large- and small-scale distribution of dark matter around the Milky Way.

Scalable and practical multi-objective distribution network expansion planning

NARCIS (Netherlands)

Luong, N.H.; Grond, M.O.W.; Poutré, La J.A.; Bosman, P.A.N.

2015-01-01

We formulate the distribution network expansion planning (DNEP) problem as a multi-objective optimization (MOO) problem with different objectives that distribution network operators (DNOs) would typically like to consider during decision making processes for expanding their networks. Objectives are

OBJECT-SPACE MULTI-IMAGE MATCHING OF MOBILE-MAPPING-SYSTEM IMAGE SEQUENCES

Directory of Open Access Journals (Sweden)

Y. C. Chen

2012-07-01

Full Text Available This paper proposes an object-space multi-image matching procedure of terrestrial MMS (Mobile Mapping System image sequences to determine the coordinates of an object point automatically and reliably. This image matching procedure can be applied to find conjugate points of MMS image sequences efficiently. Conventional area-based image matching methods are not reliable to deliver accurate matching results for this application due to image scale variations, viewing angle variations, and object occlusions. In order to deal with these three matching problems, an object space multi-image matching is proposed. A modified NCC (Normalized Cross Correlation coefficient is proposed to measure the similarity of image patches. A modified multi-window matching procedure will also be introduced to solve the problem of object occlusion. A coarse-to-fine procedure with a combination of object-space multi-image matching and multi-window matching is adopted. The proposed procedure has been implemented for the purpose of matching terrestrial MMS image sequences. The ratio of correct matches of this experiment was about 80 %. By providing an approximate conjugate point in an overlapping image manually, most of the incorrect matches could be fixed properly and the ratio of correct matches was improved up to 98 %.

The FALCON Concept: Multi-Object Spectroscopy Combined with MCAO in Near-IR

Science.gov (United States)

Hammer, François; Sayède, Frédéric; Gendron, Eric; Fusco, Thierry; Burgarella, Denis; Cayatte, Véronique; Conan, Jean-Marc; Courbin, Frédéric; Flores, Hector; Guinouard, Isabelle; Jocou, Laurent; Lançon, Ariane; Monnet, Guy; Mouhcine, Mustapha; Rigaud, François; Rouan, Daniel; Rousset, Gérard; Buat, Véronique; Zamkotsian, Frédéric

A large fraction of the present-day stellar mass was formed between z=0.5 and z˜ 3 and our understanding of the formation mechanisms at work at these epochs requires both high spatial and high spectral resolution: one shall simultaneously obtain images of objects with typical sizes as small as 1-2 kpc (˜ 0".1), while achieving 20-50 km/s (R≥ 5000) spectral resolution. In addition, the redshift range to be considered implies that most important spectral features are redshifted in the near-infrared. The obvious instrumental solution to adopt in order to tackle the science goal is therefore a combination of multi-object 3D spectrograph with multi-conjugate adaptive optics in large fields. A very promising way to achieve such a technically challenging goal is to relax the conditions of the traditional full adaptive optics correction. A partial, but still competitive correction shall be prefered, over a much wider field of view. This can be done by estimating the turbulent volume from sets of natural guide stars, by optimizing the correction to several and discrete small areas of few arcsec 2 selected in a large field (Nasmyth field of 25 arcmin) and by correcting up to the 6th, and eventually, up to the 60 th Zernike modes. Simulations on real extragalactic fields, show that for most sources (> 80%), the recovered resolution could reach 0".15-0".25 in the J and H bands. Detection of point-like objects is improved by factors from 3 to ≥10, when compared with an instrument without adaptive correction. The proposed instrument concept, FALCON, is equipped with deployable mini-integral field units (IFUs), achieving spectral resolutions between R=5000 and 20000. Its multiplex capability, combined with high spatial and spectral resolution characteristics, is a natural ground based complement to the next generation of space telescopes. Galaxy formation in the early Universe is certainly a main science driver. We describe here how FALCON shall allow to answer puzzling

Multi-objective evacuation routing optimization for toxic cloud releases

International Nuclear Information System (INIS)

Gai, Wen-mei; Deng, Yun-feng; Jiang, Zhong-an; Li, Jing; Du, Yan

2017-01-01

This paper develops a model for assessing the risks associated with the evacuation process in response to potential chemical accidents, based on which a multi-objective evacuation routing model for toxic cloud releases is proposed taking into account that the travel speed on each arc will be affected by disaster extension. The objectives of the evacuation routing model are to minimize travel time and individual evacuation risk along a path respectively. Two heuristic algorithms are proposed to solve the multi-objective evacuation routing model. Simulation results show the effectiveness and feasibility of the model and algorithms presented in this paper. And, the methodology with appropriate modification is suitable for supporting decisions in assessing emergency route selection in other cases (fires, nuclear accidents). - Highlights: • A model for assessing and visualizing the risks is developed. • A multi-objective evacuation routing model is proposed for toxic cloud releases. • A modified Dijkstra algorithm is designed to obtain an solution of the model. • Two heuristic algorithms have been developed as the optimization tool.

Pipelining Computational Stages of the Tomographic Reconstructor for Multi-Object Adaptive Optics on a Multi-GPU System

KAUST Repository

Charara, Ali; Ltaief, Hatem; Gratadour, Damien; Keyes, David E.; Sevin, Arnaud; Abdelfattah, Ahmad; Gendron, Eric; Morel, Carine; Vidal, Fabrice

2014-01-01

called MOSAIC has been proposed to perform multi-object spectroscopy using the Multi-Object Adaptive Optics (MOAO) technique. The core implementation of the simulation lies in the intensive computation of a tomographic reconstruct or (TR), which is used

A multi-objective decision framework for lifecycle investment

NARCIS (Netherlands)

Timmermans, S.H.J.T.; Schumacher, J.M.; Ponds, E.H.M.

2017-01-01

In this paper we propose a multi-objective decision framework for lifecycle investment choice. Instead of optimizing individual strategies with respect to a single-valued objective, we suggest evaluation of classes of strategies in terms of the quality of the tradeoffs that they provide. The

Multi-objective possibilistic model for portfolio selection with transaction cost

Science.gov (United States)

Jana, P.; Roy, T. K.; Mazumder, S. K.

2009-06-01

In this paper, we introduce the possibilistic mean value and variance of continuous distribution, rather than probability distributions. We propose a multi-objective Portfolio based model and added another entropy objective function to generate a well diversified asset portfolio within optimal asset allocation. For quantifying any potential return and risk, portfolio liquidity is taken into account and a multi-objective non-linear programming model for portfolio rebalancing with transaction cost is proposed. The models are illustrated with numerical examples.

An Evolutionary Approach for Bilevel Multi-objective Problems

Science.gov (United States)

Deb, Kalyanmoy; Sinha, Ankur

Evolutionary multi-objective optimization (EMO) algorithms have been extensively applied to find multiple near Pareto-optimal solutions over the past 15 years or so. However, EMO algorithms for solving bilevel multi-objective optimization problems have not received adequate attention yet. These problems appear in many applications in practice and involve two levels, each comprising of multiple conflicting objectives. These problems require every feasible upper-level solution to satisfy optimality of a lower-level optimization problem, thereby making them difficult to solve. In this paper, we discuss a recently proposed bilevel EMO procedure and show its working principle on a couple of test problems and on a business decision-making problem. This paper should motivate other EMO researchers to engage more into this important optimization task of practical importance.

Conflicting Multi-Objective Compatible Optimization Control

OpenAIRE

Xu, Lihong; Hu, Qingsong; Hu, Haigen; Goodman, Erik

2010-01-01

Based on ideas developed in addressing practical greenhouse environmental control, we propose a new multi-objective compatible control method. Several detailed algorithms are proposed to meet the requirements of different kinds of problem: 1) A two-layer MOCC framework is presented for problems with a precise model; 2) To deal with situations

Close stellar encounters in globular clusters

International Nuclear Information System (INIS)

Bailyn, C.D.

1989-01-01

Stellar encounters are expected to produce a variety of interesting objects in the cores of globular clusters, either through the formation of binaries by tidal capture, or direct collisions. Here, I describe several attempts to observe the products of stellar encounters. In particular, the use of color maps has demonstrated the existence of a color gradient in the core of M15, which seems to be caused by a population of faint blue objects concentrated towards the cluster center. (author)

Engineering aspects of compact stellarators

International Nuclear Information System (INIS)

Nelson, B.E.; Benson, R.D.; Brooks, A.

2003-01-01

Compact stellarators could combine the good confinement and high beta of a tokamak with the inherently steady state, disruption-free characteristics of a stellarator. Two U.S. compact stellarator facilities are now in the conceptual design phase: the National Compact Stellarator Experiment (NCSX) and the Quasi- Poloidal Stellarator (QPS). NCSX has a major radius of 1.4 m and a toroidal field up to 2 T. The primary feature of both NCSX and QPS is the set of modular coils that provide the basic magnetic configuration. These coils represent a major engineering challenge due to the complex shape, precise geometric accuracy, and high current density of the windings. The winding geometry is too complex for conventional hollow copper conductor construction. Instead, the modular coils will be wound with flexible, multi strand cable conductor that has been compacted to a 75% copper packing fraction. Inside the NCSX coil set and surrounding the plasma is a highly contoured vacuum vessel. The vessel consists of three identical, 120 deg. segments that are bolted together at double sealed joints. The QPS device has a major radius of 0.9 m, a toroidal field of 1 T, and an aspect ratio of only 2.7. Instead of an internal vacuum vessel, the QPS modular coils will operate in an external vacuum tank. (author)

Uncertain and multi-objective programming models for crop planting structure optimization

Directory of Open Access Journals (Sweden)

Mo LI,Ping GUO,Liudong ZHANG,Chenglong ZHANG

2016-03-01

Full Text Available Crop planting structure optimization is a significant way to increase agricultural economic benefits and improve agricultural water management. The complexities of fluctuating stream conditions, varying economic profits, and uncertainties and errors in estimated modeling parameters, as well as the complexities among economic, social, natural resources and environmental aspects, have led to the necessity of developing optimization models for crop planting structure which consider uncertainty and multi-objectives elements. In this study, three single-objective programming models under uncertainty for crop planting structure optimization were developed, including an interval linear programming model, an inexact fuzzy chance-constrained programming (IFCCP model and an inexact fuzzy linear programming (IFLP model. Each of the three models takes grayness into account. Moreover, the IFCCP model considers fuzzy uncertainty of parameters/variables and stochastic characteristics of constraints, while the IFLP model takes into account the fuzzy uncertainty of both constraints and objective functions. To satisfy the sustainable development of crop planting structure planning, a fuzzy-optimization-theory-based fuzzy linear multi-objective programming model was developed, which is capable of reflecting both uncertainties and multi-objective. In addition, a multi-objective fractional programming model for crop structure optimization was also developed to quantitatively express the multi-objective in one optimization model with the numerator representing maximum economic benefits and the denominator representing minimum crop planting area allocation. These models better reflect actual situations, considering the uncertainties and multi-objectives of crop planting structure optimization systems. The five models developed were then applied to a real case study in Minqin County, north-west China. The advantages, the applicable conditions and the solution methods

Multi-objective optimal power flow with FACTS devices

International Nuclear Information System (INIS)

Basu, M.

2011-01-01

This paper presents multi-objective differential evolution to optimize cost of generation, emission and active power transmission loss of flexible ac transmission systems (FACTS) device-equipped power systems. In the proposed approach, optimal power flow problem is formulated as a multi-objective optimization problem. FACTS devices considered include thyristor controlled series capacitor (TCSC) and thyristor controlled phase shifter (TCPS). The proposed approach has been examined and tested on the modified IEEE 30-bus and 57-bus test systems. The results obtained from the proposed approach have been compared with those obtained from nondominated sorting genetic algorithm-II, strength pareto evolutionary algorithm 2 and pareto differential evolution.

Multi-objective engineering design using preferences

Science.gov (United States)

Sanchis, J.; Martinez, M.; Blasco, X.

2008-03-01

System design is a complex task when design parameters have to satisy a number of specifications and objectives which often conflict with those of others. This challenging problem is called multi-objective optimization (MOO). The most common approximation consists in optimizing a single cost index with a weighted sum of objectives. However, once weights are chosen the solution does not guarantee the best compromise among specifications, because there is an infinite number of solutions. A new approach can be stated, based on the designer's experience regarding the required specifications and the associated problems. This valuable information can be translated into preferences for design objectives, and will lead the search process to the best solution in terms of these preferences. This article presents a new method, which enumerates these a priori objective preferences. As a result, a single objective is built automatically and no weight selection need be performed. Problems occuring because of the multimodal nature of the generated single cost index are managed with genetic algorithms (GAs).

PARETO OPTIMAL SOLUTIONS FOR MULTI-OBJECTIVE GENERALIZED ASSIGNMENT PROBLEM

Directory of Open Access Journals (Sweden)

S. Prakash

2012-01-01

Full Text Available

ENGLISH ABSTRACT: The Multi-Objective Generalized Assignment Problem (MGAP with two objectives, where one objective is linear and the other one is non-linear, has been considered, with the constraints that a job is assigned to only one worker – though he may be assigned more than one job, depending upon the time available to him. An algorithm is proposed to find the set of Pareto optimal solutions of the problem, determining assignments of jobs to workers with two objectives without setting priorities for them. The two objectives are to minimise the total cost of the assignment and to reduce the time taken to complete all the jobs.

AFRIKAANSE OPSOMMING: ‘n Multi-doelwit veralgemeende toekenningsprobleem (“multi-objective generalised assignment problem – MGAP” met twee doelwitte, waar die een lineêr en die ander nielineêr is nie, word bestudeer, met die randvoorwaarde dat ‘n taak slegs toegedeel word aan een werker – alhoewel meer as een taak aan hom toegedeel kan word sou die tyd beskikbaar wees. ‘n Algoritme word voorgestel om die stel Pareto-optimale oplossings te vind wat die taaktoedelings aan werkers onderhewig aan die twee doelwitte doen sonder dat prioriteite toegeken word. Die twee doelwitte is om die totale koste van die opdrag te minimiseer en om die tyd te verminder om al die take te voltooi.

The Stellar Imager (SI) Mission Concept

Science.gov (United States)

Carpenter, Kenneth G.; Schrijver, Carolus J.; Lyon, Richard G.; Mundy, Lee G.; Allen, Ronald J.; Armstrong, Thomas; Danchi, William C.; Karovska, Margarita; Marzouk, Joe; Mazzuca, Lisa M.;

Joint Conditional Random Field Filter for Multi-Object Tracking

Directory of Open Access Journals (Sweden)

Luo Ronghua

2011-03-01

Full Text Available Object tracking can improve the performance of mobile robot especially in populated dynamic environments. A novel joint conditional random field Filter (JCRFF based on conditional random field with hierarchical structure is proposed for multi-object tracking by abstracting the data associations between objects and measurements to be a sequence of labels. Since the conditional random field makes no assumptions about the dependency structure between the observations and it allows non-local dependencies between the state and the observations, the proposed method can not only fuse multiple cues including shape information and motion information to improve the stability of tracking, but also integrate moving object detection and object tracking quite well. At the same time, implementation of multi-object tracking based on JCRFF with measurements from the laser range finder on a mobile robot is studied. Experimental results with the mobile robot developed in our lab show that the proposed method has higher precision and better stability than joint probabilities data association filter (JPDAF.

A procedure for multi-objective optimization of tire design parameters

OpenAIRE

Nikola Korunović; Miloš Madić; Miroslav Trajanović; Miroslav Radovanović

2015-01-01

The identification of optimal tire design parameters for satisfying different requirements, i.e. tire performance characteristics, plays an essential role in tire design. In order to improve tire performance characteristics, formulation and solving of multi-objective optimization problem must be performed. This paper presents a multi-objective optimization procedure for determination of optimal tire design parameters for simultaneous minimization of strain energy density at two distinctive zo...

Ionised Jets Associated With Massive Young Stellar Objects

Science.gov (United States)

Purser, Simon John Derek

2017-09-01

This thesis focuses on the phenomena of ionised jets associated with massive young stellar objects. Firstly a study was conducted with the aim to establish a statistical sample of such objects. Radio observations towards a sample of 49 MYSOs resulted in the detection of 28 objects classified as ionised jets. The jets’ radio luminosities scaled with their MYSOs’ bolometric luminosities in the same way as for low-mass examples. This infers that the jet launching and collimation mechanisms of high-mass jets are very similar to that in their low-mass counterparts and they are ejected for the last ≤65000 yr of the MYSO phase. Interestingly non-thermal emission was regularly detected towards spatially distinct radio lobes (associated with ˜50% of the jets), suggesting the presence of synchrotron emission and therefore, magnetic fields. With an average spectral index of ¯α=‑0. 55 (indicative of the 1st order Fermi acceleration mechanism) it is concluded these lobes are the result of shocks in the jets’ stream. My second science chapter is a study of radio variability, precession and proper motions towards a subset of objects from the first chapter. Over a two year time period, no significant variability and only one example of proper motion (1800±600 km s‑1) was detected. Precession was found to be commonplace however and if it arises as the result of binary interactions, we infer orbital radii between 30 and 1800 au for the binary companions. Lastly, high-resolution, VLA observations at C and Q-bands were analysed to extend the known sample of MYSOs harbouring ionised jets into the northern hemisphere. Only 3 radio sources were detected possessing jet-like characteristics towards the work’s sub-sample of 8 IRDCs containing 44 mm-cores (in our field of view), highlighting the radio-quiet (≳30μJy) nature of this early phase in massive star formation. Towards the RMS survey derived sample of 48 MYSOs, a total of 38 radio sources with jet

Geometric phase modulation for stellar interferometry

International Nuclear Information System (INIS)

Roy, M.; Boschung, B.; Tango, W.J.; Davis, J.

2002-01-01

Full text: In a long baseline optical interferometer, the fringe visibility is normally measured by modulation of the optical path difference between the two arms of the instruments. To obtain accurate measurements, the spectral bandwidth must be narrow, limiting the sensitivity of the technique. The application of geometric phase modulation technique to stellar interferometry has been proposed by Tango and Davis. Modulation of the geometric phase has the potential for improving the sensitivity of optical interferometers, and specially the Sydney University Stellar Interferometer (SUSI), by allowing broad band modulation of the light signals. This is because a modulator that changes the geometric phase of the signal is, in principle, achromatic. Another advantage of using such a phase modulator is that it can be placed in the common path traversed by the two orthogonally polarized beams emerging from the beam combiner in a stellar interferometer. Thus the optical components of the modulator do not have to be interferometric quality and could be relatively easily introduced into SUSI. We have investigated the proposed application in a laboratory-based experiment using a Mach-Zehnder interferometer with white-light source. This can be seen as a small model of an amplitude stellar interferometer where the light source takes the place of the distant star and two corner mirrors replaces the entrance pupils of the stellar interferometer

A Survey of Multi-Objective Sequential Decision-Making

OpenAIRE

Roijers, D.M.; Vamplew, P.; Whiteson, S.; Dazeley, R.

2013-01-01

Sequential decision-making problems with multiple objectives arise naturally in practice and pose unique challenges for research in decision-theoretic planning and learning, which has largely focused on single-objective settings. This article surveys algorithms designed for sequential decision-making problems with multiple objectives. Though there is a growing body of literature on this subject, little of it makes explicit under what circumstances special methods are needed to solve multi-obj...

The Effects of Stellar Dynamics on the Evolution of Young, Dense Stellar Systems

Science.gov (United States)

Belkus, H.; van Bever, J.; Vanbeveren, D.

In this paper, we report on first results of a project in Brussels in which we study the effects of stellar dynamics on the evolution of young dense stellar systems using 3 decades of expertise in massive-star evolution and our population (number and spectral) synthesis code. We highlight an unconventionally formed object scenario (UFO-scenario) for Wolf Rayet binaries and study the effects of a luminous blue variable-type instability wind mass-loss formalism on the formation of intermediate-mass black holes.

Compact stellarator coils

International Nuclear Information System (INIS)

Pomphrey, N.; Berry, L.A.; Boozer, A.H.

2001-01-01

Experimental devices to study the physics of high-beta (β>∼4%), low aspect ratio (A<∼4.5) stellarator plasmas require coils that will produce plasmas satisfying a set of physics goals, provide experimental flexibility, and be practical to construct. In the course of designing a flexible coil set for the National Compact Stellarator Experiment, we have made several innovations that may be useful in future stellarator design efforts. These include: the use of Singular Value Decomposition methods for obtaining families of smooth current potentials on distant coil winding surfaces from which low current density solutions may be identified; the use of a Control Matrix Method for identifying which few of the many detailed elements of the stellarator boundary must be targeted if a coil set is to provide fields to control the essential physics of the plasma; the use of Genetic Algorithms for choosing an optimal set of discrete coils from a continuum of potential contours; the evaluation of alternate coil topologies for balancing the tradeoff between physics objective and engineering constraints; the development of a new coil optimization code for designing modular coils, and the identification of a 'natural' basis for describing current sheet distributions. (author)

Irrigation water allocation optimization using multi-objective evolutionary algorithm (MOEA) - a review

Science.gov (United States)

Fanuel, Ibrahim Mwita; Mushi, Allen; Kajunguri, Damian

2018-03-01

This paper analyzes more than 40 papers with a restricted area of application of Multi-Objective Genetic Algorithm, Non-Dominated Sorting Genetic Algorithm-II and Multi-Objective Differential Evolution (MODE) to solve the multi-objective problem in agricultural water management. The paper focused on different application aspects which include water allocation, irrigation planning, crop pattern and allocation of available land. The performance and results of these techniques are discussed. The review finds that there is a potential to use MODE to analyzed the multi-objective problem, the application is more significance due to its advantage of being simple and powerful technique than any Evolutionary Algorithm. The paper concludes with the hopeful new trend of research that demand effective use of MODE; inclusion of benefits derived from farm byproducts and production costs into the model.

Multi-Objective Weather Routing of Sailing Vessels

Directory of Open Access Journals (Sweden)

Życzkowski Marcin

2017-12-01

Full Text Available The paper presents a multi-objective deterministic method of weather routing for sailing vessels. Depending on a particular purpose of sailboat weather routing, the presented method makes it possible to customize the criteria and constraints so as to fit a particular user’s needs. Apart from a typical shortest time criterion, safety and comfort can also be taken into account. Additionally, the method supports dynamic weather data: in its present version short-term, mid-term and long-term term weather forecasts are used during optimization process. In the paper the multi-objective optimization problem is first defined and analysed. Following this, the proposed method solving this problem is described in detail. The method has been implemented as an online SailAssistance application. Some representative examples solutions are presented, emphasizing the effects of applying different criteria or different values of customized parameters.

IRAS 20050+2720: ANATOMY OF A YOUNG STELLAR CLUSTER

International Nuclear Information System (INIS)

Günther, H. M.; Wolk, S. J.; Spitzbart, B.; Forbrich, J.; Wright, N. J.; Bourke, T. L.; Gutermuth, R. A.; Allen, L.; Megeath, S. T.; Pipher, J. L.

2012-01-01

IRAS 20050+2720 is young star-forming region at a distance of 700 pc without apparent high-mass stars. We present results of our multi-wavelength study of IRAS 20050+2720 which includes observations by Chandra and Spitzer, and Two Micron All Sky Survey and UBVRI photometry. In total, about 300 young stellar objects (YSOs) in different evolutionary stages are found. We characterize the distribution of YSOs in this region using a minimum spanning tree analysis. We newly identify a second cluster core, which consists mostly of class II objects, about 10' from the center of the cloud. YSOs of earlier evolutionary stages are more clustered than more evolved objects. The X-ray luminosity function (XLF) of IRAS 20050+2720 is roughly lognormal, but steeper than the XLF of the more massive Orion Nebula complex. IRAS 20050+2720 shows a lower N H /A K ratio compared with the diffuse interstellar medium.

IRAS 20050+2720: ANATOMY OF A YOUNG STELLAR CLUSTER

Energy Technology Data Exchange (ETDEWEB)

Guenther, H. M.; Wolk, S. J.; Spitzbart, B.; Forbrich, J.; Wright, N. J.; Bourke, T. L. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Gutermuth, R. A. [Department of Astronomy, University of Massachusetts, Amherst, MA 01003 (United States); Allen, L. [National Optical Astronomy Observatory, 950 North Cherry Avenue, Tucson, AZ 85719 (United States); Megeath, S. T. [Department of Physics and Astronomy, MS-113, University of Toledo, 2801 W. Bancroft St., Toledo, OH 43606 (United States); Pipher, J. L., E-mail: hguenther@cfa.harvard.edu [Department of Physics and Astronomy, University of Rochester, 500 Wilson Boulevard, Rochester, NY 14627 (United States)

2012-10-01

IRAS 20050+2720 is young star-forming region at a distance of 700 pc without apparent high-mass stars. We present results of our multi-wavelength study of IRAS 20050+2720 which includes observations by Chandra and Spitzer, and Two Micron All Sky Survey and UBVRI photometry. In total, about 300 young stellar objects (YSOs) in different evolutionary stages are found. We characterize the distribution of YSOs in this region using a minimum spanning tree analysis. We newly identify a second cluster core, which consists mostly of class II objects, about 10' from the center of the cloud. YSOs of earlier evolutionary stages are more clustered than more evolved objects. The X-ray luminosity function (XLF) of IRAS 20050+2720 is roughly lognormal, but steeper than the XLF of the more massive Orion Nebula complex. IRAS 20050+2720 shows a lower N{sub H}/A{sub K} ratio compared with the diffuse interstellar medium.

Space Weather: Linking Stellar Explosions to the Human Endeavor

Science.gov (United States)

Knipp, Delores

2017-06-01

Arguably humans have flourished as a result of stellar explosions; we are, after all, stardust. Nonetheless, rapid technology advances of the last 200 years sometimes put society and individuals on a collision course with the natural variability of stellar and solar atmospheres. Human space exploration, routine satellite navigation system applications, aviation safety, and electric power grids are examples of such vulnerable endeavors. In this presentation I will outline how global society relies on ‘normal’ solar and stellar emissions, yet becomes susceptible to extremes of these emissions. The imprints of these astronomical-terrestrial interactions abound. In particular, I will highlight ways in which stellar/solar bursts link with our space-atmosphere-interaction region, producing multi-year patterns in cosmic ray detection, gorgeous aurora, and deep concern for good order and function of global community.

Design of a centrifugal compressor impeller using multi-objective optimization algorithm

International Nuclear Information System (INIS)

Kim, Jin Hyuk; Husain, Afzal; Kim, Kwang Yong; Choi, Jae Ho

2009-01-01

This paper presents a design optimization of a centrifugal compressor impeller with hybrid multi-objective evolutionary algorithm (hybrid MOEA). Reynolds-averaged Navier-Stokes equations with shear stress transport turbulence model are discretized by finite volume approximations and solved on hexahedral grids for flow analyses. Two objectives, i.e., isentropic efficiency and total pressure ratio are selected with four design variables defining impeller hub and shroud contours in meridional contours to optimize the system. Non-dominated Sorting of Genetic Algorithm (NSGA-II) with ε-constraint strategy for local search coupled with Radial Basis Neural Network model is used for multi-objective optimization. The optimization results show that isentropic efficiencies and total pressure ratios of the five cluster points at the Pareto-optimal solutions are enhanced by multi-objective optimization.

Design of a centrifugal compressor impeller using multi-objective optimization algorithm

Energy Technology Data Exchange (ETDEWEB)

Kim, Jin Hyuk; Husain, Afzal; Kim, Kwang Yong [Inha University, Incheon (Korea, Republic of); Choi, Jae Ho [Samsung Techwin Co., Ltd., Changwon (Korea, Republic of)

2009-07-01

This paper presents a design optimization of a centrifugal compressor impeller with hybrid multi-objective evolutionary algorithm (hybrid MOEA). Reynolds-averaged Navier-Stokes equations with shear stress transport turbulence model are discretized by finite volume approximations and solved on hexahedral grids for flow analyses. Two objectives, i.e., isentropic efficiency and total pressure ratio are selected with four design variables defining impeller hub and shroud contours in meridional contours to optimize the system. Non-dominated Sorting of Genetic Algorithm (NSGA-II) with {epsilon}-constraint strategy for local search coupled with Radial Basis Neural Network model is used for multi-objective optimization. The optimization results show that isentropic efficiencies and total pressure ratios of the five cluster points at the Pareto-optimal solutions are enhanced by multi-objective optimization.

High performance pseudo-analytical simulation of multi-object adaptive optics over multi-GPU systems

KAUST Repository

Abdelfattah, Ahmad; Gendron, É ric; Gratadour, Damien; Keyes, David E.; Ltaief, Hatem; Sevin, Arnaud; Vidal, Fabrice

2014-01-01

Multi-object adaptive optics (MOAO) is a novel adaptive optics (AO) technique dedicated to the special case of wide-field multi-object spectrographs (MOS). It applies dedicated wavefront corrections to numerous independent tiny patches spread over a large field of view (FOV). The control of each deformable mirror (DM) is done individually using a tomographic reconstruction of the phase based on measurements from a number of wavefront sensors (WFS) pointing at natural and artificial guide stars in the field. The output of this study helps the design of a new instrument called MOSAIC, a multi-object spectrograph proposed for the European Extremely Large Telescope (E-ELT). We have developed a novel hybrid pseudo-analytical simulation scheme that allows us to accurately simulate in detail the tomographic problem. The main challenge resides in the computation of the tomographic reconstructor, which involves pseudo-inversion of a large dense symmetric matrix. The pseudo-inverse is computed using an eigenvalue decomposition, based on the divide and conquer algorithm, on multicore systems with multi-GPUs. Thanks to a new symmetric matrix-vector product (SYMV) multi-GPU kernel, our overall implementation scores significant speedups over standard numerical libraries on multicore, like Intel MKL, and up to 60% speedups over the standard MAGMA implementation on 8 Kepler K20c GPUs. At 40,000 unknowns, this appears to be the largest-scale tomographic AO matrix solver submitted to computation, to date, to our knowledge and opens new research directions for extreme scale AO simulations. © 2014 Springer International Publishing Switzerland.

Hybrid Robust Multi-Objective Evolutionary Optimization Algorithm

Science.gov (United States)

2009-03-10

xfar by xint. Else, generate a new individual, using the Sobol pseudo- random sequence generator within the upper and lower bounds of the variables...12. Deb, K., Multi-Objective Optimization Using Evolutionary Algorithms, John Wiley & Sons. 2002. 13. Sobol , I. M., "Uniformly Distributed Sequences

A multi-objective approach for developing national energy efficiency plans

International Nuclear Information System (INIS)

Haydt, Gustavo; Leal, Vítor; Dias, Luís

2014-01-01

This paper proposes a new approach to deal with the problem of building national energy efficiency (EE) plans, considering multiple objectives instead of only energy savings. The objectives considered are minimizing the influence of energy use on climate change, minimizing the financial risk from the investment, maximizing the security of energy supply, minimizing investment costs, minimizing the impacts of building new power plants and transmission infrastructures, and maximizing the local air quality. These were identified through literature review and interaction with real decision makers. A database of measures is established, from which millions of potential EE plans can be built by combining measures and their respective degree of implementation. Finally, a hybrid multi-objective and multi-criteria decision analysis (MCDA) model is proposed to search and select the EE plans that best match the decision makers’ preferences. An illustration of the working mode and the type of results obtained from this novel hybrid model is provided through an application to Portugal. For each of five decision perspectives a wide range of potential best plans were identified. These wide ranges show the relevance of introducing multi-objective analysis in a comprehensive search space as a tool to inform decisions about national EE plans. - Highlights: • A multiple objective approach to aid the choice of national energy efficiency plans. • A hybrid multi-objective MCDA model is proposed to search among the possible plans. • The model identified relevant plans according to five different idealized DMs. • The approach is tested with Portugal

OBJECT-ORIENTED CHANGE DETECTION BASED ON MULTI-SCALE APPROACH

Directory of Open Access Journals (Sweden)

Y. Jia

2016-06-01

Full Text Available The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object-oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.

Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation.

Science.gov (United States)

Hu, Weiming; Li, Wei; Zhang, Xiaoqin; Maybank, Stephen

2015-04-01

In this paper, we propose a tracking algorithm based on a multi-feature joint sparse representation. The templates for the sparse representation can include pixel values, textures, and edges. In the multi-feature joint optimization, noise or occlusion is dealt with using a set of trivial templates. A sparse weight constraint is introduced to dynamically select the relevant templates from the full set of templates. A variance ratio measure is adopted to adaptively adjust the weights of different features. The multi-feature template set is updated adaptively. We further propose an algorithm for tracking multi-objects with occlusion handling based on the multi-feature joint sparse reconstruction. The observation model based on sparse reconstruction automatically focuses on the visible parts of an occluded object by using the information in the trivial templates. The multi-object tracking is simplified into a joint Bayesian inference. The experimental results show the superiority of our algorithm over several state-of-the-art tracking algorithms.

Wide-field infrared survey explorer observations of young stellar objects in the Lynds 1509 dark cloud in Auriga

Energy Technology Data Exchange (ETDEWEB)

Liu, Wilson M.; McCollum, Bruce; Fajardo-Acosta, Sergio [Infrared Processing and Analysis Center, California Institute of Technology, MC 100-22, Pasadena, CA 91125 (United States); Padgett, Deborah L. [National Aeronautics and Space Administration, Goddard Space Flight Center, Code 665, Greenbelt, MD 20771 (United States); Terebey, Susan; Angione, John [Department of Physics and Astronomy, California State University, Los Angeles, CA 90032 (United States); Rebull, Luisa M. [Spitzer Science Center, California Institute of Technology, MC 314-6, Pasadena, CA 91125 (United States); Leisawitz, David, E-mail: wliu@ipac.caltech.edu [National Aeronautics and Space Administration, Goddard Space Flight Center, Code 605, Greenbelt, MD 20771 (United States)

2014-06-01

The Wide-Field Infrared Survey Explorer (WISE) has uncovered a striking cluster of young stellar object (YSO) candidates associated with the L1509 dark cloud in Auriga. The WISE observations, at 3.4 μm, 4.6 μm, 12 μm, and 22 μm, show a number of objects with colors consistent with YSOs, and their spectral energy distributions suggest the presence of circumstellar dust emission, including numerous Class I, flat spectrum, and Class II objects. In general, the YSOs in L1509 are much more tightly clustered than YSOs in other dark clouds in the Taurus-Auriga star forming region, with Class I and flat spectrum objects confined to the densest aggregates, and Class II objects more sparsely distributed. We estimate a most probable distance of 485-700 pc, and possibly as far as the previously estimated distance of 2 kpc.

A hybrid multi-objective evolutionary algorithm approach for ...

Indian Academy of Sciences (India)

V K MANUPATI

for handling sequence- and machine-dependent set-up times ... algorithm has been compared to that of multi-objective particle swarm optimization (MOPSO) and conventional ..... position and cognitive learning factor are considered for.

Effective multi-objective optimization of Stirling engine systems

International Nuclear Information System (INIS)

Punnathanam, Varun; Kotecha, Prakash

2016-01-01

Highlights: • Multi-objective optimization of three recent Stirling engine models. • Use of efficient crossover and mutation operators for real coded Genetic Algorithm. • Demonstrated supremacy of the strategy over the conventionally used algorithm. • Improvements of up to 29% in comparison to literature results. - Abstract: In this article we demonstrate the supremacy of the Non-dominated Sorting Genetic Algorithm-II with Simulated Binary Crossover and Polynomial Mutation operators for the multi-objective optimization of Stirling engine systems by providing three examples, viz., (i) finite time thermodynamic model, (ii) Stirling engine thermal model with associated irreversibility and (iii) polytropic finite speed based thermodynamics. The finite time thermodynamic model involves seven decision variables and consists of three objectives: output power, thermal efficiency and rate of entropy generation. In comparison to literature, it was observed that the used strategy provides a better Pareto front and leads to improvements of up to 29%. The performance is also evaluated on a Stirling engine thermal model which considers the associated irreversibility of the cycle and consists of three objectives involving eleven decision variables. The supremacy of the suggested strategy is also demonstrated on the experimentally validated polytropic finite speed thermodynamics based Stirling engine model for optimization involving two objectives and ten decision variables.

FGP Approach for Solving Multi-level Multi-objective Quadratic Fractional Programming Problem with Fuzzy parameters

Directory of Open Access Journals (Sweden)

m. s. osman

2017-09-01

Full Text Available In this paper, we consider fuzzy goal programming (FGP approach for solving multi-level multi-objective quadratic fractional programming (ML-MOQFP problem with fuzzy parameters in the constraints. Firstly, the concept of the ?-cut approach is applied to transform the set of fuzzy constraints into a common deterministic one. Then, the quadratic fractional objective functions in each level are transformed into quadratic objective functions based on a proposed transformation. Secondly, the FGP approach is utilized to obtain a compromise solution for the ML-MOQFP problem by minimizing the sum of the negative deviational variables. Finally, an illustrative numerical example is given to demonstrate the applicability and performance of the proposed approach.

Stellar axion models

Energy Technology Data Exchange (ETDEWEB)

Nowakowski, Daniel; Kuster, Markus; Meister, Claudia V.; Fuelbert, Florian; Hoffmann, Dieter H.H. [TU Darmstadt (Germany). Institut fuer Kernphysik; Weiss, Achim [Max-Planck-Institut fuer Astrophysik, Garching (Germany)

2010-07-01

An axion helioscope is typically operated to observe the sun as an axion source. Additional pointings at celestial sources, e.g. stars in other galaxies, result in possible detections of axions from distant galactic objects. For the observation of supplementary axion sources we therefore calculate the thereotical axion flux from distant stars by extending axionic flux models for the axion Primakoff effect in the sun to other main sequence stars. The main sequence star models used for our calculations are based on full stellar structure calculations. To deduce the effective axion flux of stellar objects incident on the Earth the All-Sky catalogue was used to obtain the spectral class and distance of the stars treated. Our calculations of the axion flux in the galactic plane show that for a zero age main sequence star an maximum axion flux of {phi}{sub a}=303.43 cm{sup -2}s{sup -1} could be expected. Furthermore we present estimates of axion fluxes from time-evolved stars.

CO-ices in embedded Young Stellar Objects

Science.gov (United States)

Teixeira, Teresa Cláeira V. S.

1998-09-01

Stars are born in dense cores within molecular clouds, enshrouded in large cocoons of gas and dust which completely obscure the forming star. The large degree of obscuration towards the young stars is due to the presence of solid dust grains in their circumstellar envelopes, which efficiently absorb the radiation from the star at visual and ultraviolet wavelengths, reradiating that energy at far-infrared and submillimeter wavelengths. The composition and structure of the dust grains is not well known, but current studies point to grains having a refractory core and acquiring ice mantles in the cool, shielded conditions of molecular clouds. Such ice mantles are the subject of this thesis. Infrared spectroscopy is an important tool in the study of the complex ice mantles on interstellar grains. A variety of absorption features at these wavelengths, which have been identified as the vibrational transitions of the molecules in the ices, can provide important information on the composition, structure and evolution of the grains. The work reported in this thesis consists of an observational study of the composition of the ice mantles acquired by the dust grains in molecular clouds (with particular emphasis on the CO-ices in the material surrounding embedded Young Stellar Objects in nearby molecular clouds), what can be learned from that about the physical conditions in the regions where the ice mantles exist, and what may affect their survival and evolution. In this work, spectra of the 4.67 micron solid CO absorption feature are presented, mostly towards embedded objects in Taurus. The thesis starts with a brief overview of technical aspects of spectroscopic observations at thermal infrared wavelengths, where the CO stretch absorption feature is located. The observations and data reduction procedures are then reported and discussed in detail. The likely composition of the CO-bearing ices is analysed by fitting the observations with laboratory data. The statistical

Convex Coverage Set Methods for Multi-Objective Collaborative Decision Making

NARCIS (Netherlands)

Roijers, D.M.; Lomuscio, A.; Scerri, P.; Bazzan, A.; Huhns, M.

2014-01-01

My research is aimed at finding efficient coordination methods for multi-objective collaborative multi-agent decision theoretic planning. Key to coordinating efficiently in these settings is exploiting loose couplings between agents. We proposed two algorithms for the case in which the agents need

Multi-objective and multi-criteria optimization for power generation expansion planning with CO2 mitigation in Thailand

Directory of Open Access Journals (Sweden)

Kamphol Promjiraprawat

2013-06-01

Full Text Available In power generation expansion planning, electric utilities have encountered the major challenge of environmental awareness whilst being concerned with budgetary burdens. The approach for selecting generating technologies should depend on economic and environmental constraint as well as externalities. Thus, the multi-objective optimization becomes a more attractive approach. This paper presents a hybrid framework of multi-objective optimization and multi-criteria decision making to solve power generation expansion planning problems in Thailand. In this paper, CO2 emissions and external cost are modeled as a multi-objective optimization problem. Then the analytic hierarchy process is utilized to determine thecompromised solution. For carbon capture and storage technology, CO2 emissions can be mitigated by 74.7% from the least cost plan and leads to the reduction of the external cost of around 500 billion US dollars over the planning horizon. Results indicate that the proposed approach provides optimum cost-related CO2 mitigation plan as well as external cost.

Multi-objective Search-based Mobile Testing

OpenAIRE

Mao, K.

2017-01-01

Despite the tremendous popularity of mobile applications, mobile testing still relies heavily on manual testing. This thesis presents mobile test automation approaches based on multi-objective search. We introduce three approaches: Sapienz (for native Android app testing), Octopuz (for hybrid/web JavaScript app testing) and Polariz (for using crowdsourcing to support search-based mobile testing). These three approaches represent the primary scientific and technical contributions of the thesis...

Multi-objective decision-making model based on CBM for an aircraft fleet

Science.gov (United States)

Luo, Bin; Lin, Lin

2018-04-01

Modern production management patterns, in which multi-unit (e.g., a fleet of aircrafts) are managed in a holistic manner, have brought new challenges for multi-unit maintenance decision making. To schedule a good maintenance plan, not only does the individual machine maintenance have to be considered, but also the maintenance of the other individuals have to be taken into account. Since most condition-based maintenance researches for aircraft focused on solely reducing maintenance cost or maximizing the availability of single aircraft, as well as considering that seldom researches concentrated on both the two objectives: minimizing cost and maximizing the availability of a fleet (total number of available aircraft in fleet), a multi-objective decision-making model based on condition-based maintenance concentrated both on the above two objectives is established. Furthermore, in consideration of the decision maker may prefer providing the final optimal result in the form of discrete intervals instead of a set of points (non-dominated solutions) in real decision-making problem, a novel multi-objective optimization method based on support vector regression is proposed to solve the above multi-objective decision-making model. Finally, a case study regarding a fleet is conducted, with the results proving that the approach efficiently generates outcomes that meet the schedule requirements.

Multi-objective approach in thermoenvironomic optimization of a benchmark cogeneration system

International Nuclear Information System (INIS)

Sayyaadi, Hoseyn

2009-01-01

Multi-objective optimization for designing of a benchmark cogeneration system known as CGAM cogeneration system has been performed. In optimization approach, the exergetic, economic and environmental aspects have been considered, simultaneously. The thermodynamic modeling has been implemented comprehensively while economic analysis conducted in accordance with the total revenue requirement (TRR) method. The results for the single objective thermoeconomic optimization have been compared with the previous studies in optimization of CGAM problem. In multi-objective optimization of the CGAM problem, the three objective functions including the exergetic efficiency, total levelized cost rate of the system product and the cost rate of environmental impact have been considered. The environmental impact objective function has been defined and expressed in cost terms. This objective has been integrated with the thermoeconomic objective to form a new unique objective function known as a thermoenvironomic objective function. The thermoenvironomic objective has been minimized while the exergetic objective has been maximized. One of the most suitable optimization techniques developed using a particular class of search algorithms known as multi-objective evolutionary algorithms (MOEAs) has been considered here. This approach which is developed based on the genetic algorithm has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of decision-making has been presented and a final optimal solution has been introduced. The sensitivity of the solutions to the interest rate and the fuel cost has been studied

Integrated production planning and control: A multi-objective optimization model

Directory of Open Access Journals (Sweden)

Cheng Wang

2013-09-01

Full Text Available Purpose: Production planning and control has crucial impact on the production and business activities of enterprise. Enterprise Resource Planning (ERP is the most popular resources planning and management system, however there are some shortcomings and deficiencies in the production planning and control because its core component is still the Material Requirements Planning (MRP. For the defects of ERP system, many local improvement and optimization schemes have been proposed, and improve the feasibility and practicality of the plan in some extent, but study considering the whole planning system optimization in the multiple performance management objectives and achieving better application performance is less. The purpose of this paper is to propose a multi-objective production planning optimization model Based on the point of view of the integration of production planning and control, in order to achieve optimization and control of enterprise manufacturing management. Design/methodology/approach: On the analysis of ERP planning system’s defects and disadvantages, and related research and literature, a multi-objective production planning optimization model is proposed, in addition to net demand and capacity, multiple performance management objectives, such as on-time delivery, production balance, inventory, overtime production, are considered incorporating into the examination scope of the model, so that the manufacturing process could be management and controlled Optimally between multiple objectives. The validity and practicability of the model will be verified by the instance in the last part of the paper. Findings: The main finding is that production planning management of manufacturing enterprise considers not only the capacity and materials, but also a variety of performance management objectives in the production process, and building a multi-objective optimization model can effectively optimize the management and control of enterprise

Blinded by the light: on the relationship between CO first overtone emission and mass accretion rate in massive young stellar objects

Science.gov (United States)

Ilee, J. D.; Oudmaijer, R. D.; Wheelwright, H. E.; Pomohaci, R.

2018-04-01

To date, there is no explanation as to why disc-tracing CO first overtone (or `bandhead') emission is not a ubiquitous feature in low- to medium-resolution spectra of massive young stellar objects, but instead is only detected toward approximately 25 per cent of their spectra. In this paper, we investigate the hypothesis that only certain mass accretion rates result in detectable bandhead emission in the near infrared spectra of MYSOs. Using an analytic disc model combined with an LTE model of the CO emission, we find that high accretion rates (≳ 10-4 M⊙yr-1) result in large dust sublimation radii, a larger contribution to the K-band continuum from hot dust at the dust sublimation radius, and therefore correspondingly lower CO emission with respect to the continuum. On the other hand, low accretion rates (≲ 10-6 M⊙yr-1) result in smaller dust sublimation radii, a correspondingly smaller emitting area of CO, and thus also lower CO emission with respect to the continuum. In general, moderate accretion rates produce the most prominent, and therefore detectable, CO first overtone emission. We compare our findings to a recent near-infrared spectroscopic survey of MYSOs, finding results consistent with our hypothesis. We conclude that the detection rate of CO bandhead emission in the spectra of MYSOs could be the result of MYSOs exhibiting a range of mass accretion rates, perhaps due to the variable accretion suggested by recent multi-epoch observations of these objects.

Exploring the trade-off between competing objectives for electricity energy retailers through a novel multi-objective framework

International Nuclear Information System (INIS)

Charwand, Mansour; Ahmadi, Abdollah; Siano, Pierluigi; Dargahi, Vahid; Sarno, Debora

2015-01-01

Highlights: • Proposing a new stochastic multi-objective framework for an electricity retailer. • Proposing a MIP model for an electricity retailer problem. • Employing ε-constraint method to generate Pareto solution. - Abstract: Energy retailer is the intermediary between Generation Companies and consumers. In the medium time horizon, in order to gain market share, he has to minimize his selling price while looking at the profit, which is dependent on the revenues from selling and the costs to buy energy from forward contracts and participation in the market pool. In this paper, the two competing objectives are engaged proposing a new multi-objective framework in which a ε-constraint mathematical technique is used to produce the Pareto front (set of optimal solutions). The stochasticity of energy prices in the market and customer load demand are coped with the Lattice Monte Carlo Simulation (LMCS) and the method of the roulette wheel, which allow the stochastic multi-objective problem to be turned into a set of deterministic equivalents. The method performance is tested into some case studies

Use of interactive data visualization in multi-objective forest planning.

Science.gov (United States)

Haara, Arto; Pykäläinen, Jouni; Tolvanen, Anne; Kurttila, Mikko

2018-03-15

Common to multi-objective forest planning situations is that they all require comparisons, searches and evaluation among decision alternatives. Through these actions, the decision maker can learn from the information presented and thus make well-justified decisions. Interactive data visualization is an evolving approach that supports learning and decision making in multidimensional decision problems and planning processes. Data visualization contributes the formation of mental image data and this process is further boosted by allowing interaction with the data. In this study, we introduce a multi-objective forest planning decision problem framework and the corresponding characteristics of data. We utilize the framework with example planning data to illustrate and evaluate the potential of 14 interactive data visualization techniques to support multi-objective forest planning decisions. Furthermore, broader utilization possibilities of these techniques to incorporate the provisioning of ecosystem services into forest management and planning are discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

The reliability of age measurements for Young Stellar Objects from Hertzsprung-Russell or color-magnitude diagrams

International Nuclear Information System (INIS)

Preibisch, Thomas

2012-01-01

The possibility to estimate ages and masses of Young Stellar Objects (YSOs) from their location in the Hertzsprung-Russell diagram (HRD) or a color-magnitude diagram provides a very important tool for the investigation of fundamental questions related to the processes of star formation and early stellar evolution. Age estimates are essential for studies of the temporal evolution of circumstellar material around YSOs and the conditions for planet formation. The characterization of the age distribution of the YSOs in a star forming region allows researchers to reconstruct the star formation history and provides important information on the fundamental question of whether star formation is a slow or a fast process. However, the reliability of these age measurements and the ability to detect possible age spreads in the stellar population of star forming regions are fundamentally limited by several factors. The variability of YSOs, unresolved binary components, and uncertainties in the calibrations of the stellar parameters cause uncertainties in the derived luminosities that are usually much larger than the typical photometry errors. Furthermore, the pre-main sequence evolution track of a YSO depends to some degree on the initial conditions and the details of its individual accretion history. I discuss how these observational and model uncertainties affect the derived isochronal ages, and demonstrate how neglecting or underestimating these uncertainties can easily lead to severe misinterpretations, gross overestimates of the age spread, and ill-based conclusions about the star formation history. These effects are illustrated by means of Monte-Carlo simulations of observed star clusters with realistic observational uncertainties. The most important points are as follows. First, the observed scatter in the HRD must not be confused with a genuine age spread, but is always just an upper limit to the true age spread. Second, histograms of isochronal ages naturally show a

Estimating precise metallicity and stellar mass evolution of galaxies

Science.gov (United States)

Mosby, Gregory

2018-01-01

The evolution of galaxies can be conveniently broken down into the evolution of their contents. The changing dust, gas, and stellar content in addition to the changing dark matter potential and periodic feedback from a super-massive blackhole are some of the key ingredients. We focus on the stellar content that can be observed, as the stars reflect information about the galaxy when they were formed. We approximate the stellar content and star formation histories of unresolved galaxies using stellar population modeling. Though simplistic, this approach allows us to reconstruct the star formation histories of galaxies that can be used to test models of galaxy formation and evolution. These models, however, suffer from degeneracies at large lookback times (t > 1 Gyr) as red, low luminosity stars begin to dominate a galaxy’s spectrum. Additionally, degeneracies between stellar populations at different ages and metallicities often make stellar population modeling less precise. The machine learning technique diffusion k-means has been shown to increase the precision in stellar population modeling using a mono-metallicity basis set. However, as galaxies evolve, we expect the metallicity of stellar populations to vary. We use diffusion k-means to generate a multi-metallicity basis set to estimate the stellar mass and chemical evolution of unresolved galaxies. Two basis sets are formed from the Bruzual & Charlot 2003 and MILES stellar population models. We then compare the accuracy and precision of these models in recovering complete (stellar mass and metallicity) histories of mock data. Similarities in the groupings of stellar population spectra in the diffusion maps for each metallicity hint at fundamental age transitions common to both basis sets that can be used to identify stellar populations in a given age range.

Multi-objective optimization for generating a weighted multi-model ensemble

Science.gov (United States)

Lee, H.

2017-12-01

Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic

Multi-element analysis of unidentified fallen objects from Tatale in ...

African Journals Online (AJOL)

A multi-element analysis has been carried out on two fallen objects, # 01 and # 02, using instrumental neutron activation analysis technique. A total of 17 elements were identified in object # 01 while 21 elements were found in object # 02. The two major elements in object # 01 were Fe and Mg, which together constitute ...

THE SPITZER EXTRAGALACTIC REPRESENTATIVE VOLUME SURVEY: THE ENVIRONMENTS OF HIGH-z SDSS QUASI-STELLAR OBJECTS

International Nuclear Information System (INIS)

Falder, J. T.; Stevens, J. A.; Jarvis, Matt J.; Bonfield, D. G.; Lacy, M.; Farrah, D.; Oliver, S.; Surace, J.; Mauduit, J.-C.; Vaccari, M.; Marchetti, L.; Gonzalez-Solares, E.; Afonso, J.; Cava, A.; Seymour, N.

2011-01-01

This paper presents a study of the environments of SDSS quasi-stellar objects (QSOs) in the Spitzer Extragalactic Representative Volume Survey (SERVS). We concentrate on the high-redshift QSOs as these have not been studied in large numbers with data of this depth before. We use the IRAC 3.6-4.5 μm color of objects and ancillary r-band data to filter out as much foreground contamination as possible. This technique allows us to find a significant (>4σ) overdensity of galaxies around QSOs in a redshift bin centered on z ∼ 2.0 and an (>2σ) overdensity of galaxies around QSOs in a redshift bin centered on z ∼ 3.3. We compare our findings to the predictions of a semi-analytic galaxy formation model, based on the ΛCDM MILLENNIUM simulation, and find for both redshift bins that the model predictions match well the source density we have measured from the SERVS data.

Fundamental Stellar Properties of M-Dwarfs from the CHARA Array

Science.gov (United States)

Berger, D. H.; Gies, D. R.; McAlister, H. A.; ten Brummelaar, T. A.; Henry, T. J.; Sturmann, J.; Sturmann, L.; Turner, N. H.; Ridgway, S. T.; Aufdenberg, J. P.; Mérand, A. M.

2005-12-01

We report the angular diameters of six M dwarfs ranging in spectral type from M1.0 V to M3.0 V measured with Georgia State University's CHARA Array, a long-baseline optical interferometer located at Mount Wilson Observatory. Observations were made with the longest baselines in the near infrared K'-band and yielded angular diameters less than one milliarcsecond. Using an iterative process combining parallaxes from the NStars program and photometrically-derived bolometric luminosities and masses, we calculated effective temperatures, surface gravities, and stellar radii. Our results are consistent with other empirical measurements of M-dwarf radii, but found that current models underestimate the true stellar radii by up to 15-20%. We suggest that theoretical models for low mass stars may be lacking an opacity source that alters the computed stellar radii. Science operations at the Array are supported by the National Science Foundation through NSF Grant AST--0307562 and by Georgia State University through the College of Arts and Sciences and the Office of the Vice President for Research. Financial support for DHB was provided by the National Science Foundation through grant AST--0205297.

Medium-resolution near-infrared spectroscopy of massive young stellar objects

Science.gov (United States)

Pomohaci, R.; Oudmaijer, R. D.; Lumsden, S. L.; Hoare, M. G.; Mendigutía, I.

2017-12-01

We present medium-resolution (R ∼ 7000) near-infrared echelle spectroscopic data for 36 massive young stellar objects (MYSOs) drawn from the Red MSX Source survey. This is the largest sample observed at this resolution at these wavelengths of MYSOs to date. The spectra are characterized mostly by emission from hydrogen recombination lines and accretion diagnostic lines. One MYSO shows photospheric H I absorption, a comparison with spectral standards indicates that the star is an A-type star with a low surface gravity, implying that the MYSOs are probably swollen, as also suggested by evolutionary calculations. An investigation of the Brγ line profiles shows that most are in pure emission, while 13 ± 5 per cent display P Cygni profiles, indicative of outflow, while less than 8 ± 4 per cent have inverse P Cygni profiles, indicative of infall. These values are comparable with investigations into the optically bright Herbig Be stars, but not with those of Herbig Ae and T Tauri stars, consistent with the notion that the more massive stars undergo accretion in a different fashion than lower mass objects that are undergoing magnetospheric accretion. Accretion luminosities and rates as derived from the Br γ line luminosities agree with results for lower mass sources, providing tentative evidence for massive star formation theories based on scaling of low-mass scenarios. We present Br γ/Br12 line profile ratios exploiting the fact that optical depth effects can be traced as a function of Doppler shift across the lines. These show that the winds of MYSOs in this sample are nearly equally split between constant, accelerating and decelerating velocity structures. There are no trends between the types of features we see and bolometric luminosities or near-infrared colours.

Exergoeconomic multi objective optimization and sensitivity analysis of a regenerative Brayton cycle

International Nuclear Information System (INIS)

Naserian, Mohammad Mahdi; Farahat, Said; Sarhaddi, Faramarz

2016-01-01

Highlights: • Finite time exergoeconomic multi objective optimization of a Brayton cycle. • Comparing the exergoeconomic and the ecological function optimization results. • Inserting the cost of fluid streams concept into finite-time thermodynamics. • Exergoeconomic sensitivity analysis of a regenerative Brayton cycle. • Suggesting the cycle performance curve drawing and utilization. - Abstract: In this study, the optimal performance of a regenerative Brayton cycle is sought through power maximization and then exergoeconomic optimization using finite-time thermodynamic concept and finite-size components. Optimizations are performed using genetic algorithm. In order to take into account the finite-time and finite-size concepts in current problem, a dimensionless mass-flow parameter is used deploying time variations. The decision variables for the optimum state (of multi objective exergoeconomic optimization) are compared to the maximum power state. One can see that the multi objective exergoeconomic optimization results in a better performance than that obtained with the maximum power state. The results demonstrate that system performance at optimum point of multi objective optimization yields 71% of the maximum power, but only with exergy destruction as 24% of the amount that is produced at the maximum power state and 67% lower total cost rate than that of the maximum power state. In order to assess the impact of the variation of the decision variables on the objective functions, sensitivity analysis is conducted. Finally, the cycle performance curve drawing according to exergoeconomic multi objective optimization results and its utilization, are suggested.

Identification of Young Stellar Variables with KELT for K2 . I. Taurus Dippers and Rotators

Energy Technology Data Exchange (ETDEWEB)

Rodriguez, Joseph E.; Cargile, Phillip A. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Ansdell, Megan [Institute for Astronomy, University of Hawaií at Manoa, Honolulu, HI 96822 (United States); Oelkers, Ryan J.; Somers, Garrett; Lund, Michael B.; Stassun, Keivan G. [Department of Physics and Astronomy, Vanderbilt University, 6301 Stevenson Center, Nashville, TN 37235 (United States); Gaidos, Eric [Department of Geology and Geophysics, University of Hawaií at Manoa, Honolulu, HI 96822 (United States); Cody, Ann Marie [NASA Ames Research Center, Mountain View, CA 94035 (United States); Stevens, Daniel J.; Gaudi, B. Scott [Department of Astronomy, The Ohio State University, Columbus, OH 43210 (United States); James, David [Astronomy Department, University of Washington, Box 351580, Seattle, WA 98195 (United States); Beatty, Thomas G. [Department of Astronomy and Astrophysics, The Pennsylvania State University, 525 Davey Lab, University Park, PA 16802 (United States); Siverd, Robert J. [Las Cumbres Observatory Global Telescope Network, 6740 Cortona Drive, Suite 102, Santa Barbara, CA 93117 (United States); Kuhn, Rudolf B. [South African Astronomical Observatory, PO Box 9, Observatory 7935 (South Africa); Pepper, Joshua [Department of Physics, Lehigh University, 16 Memorial Drive East, Bethlehem, PA 18015 (United States)

2017-10-20

One of the most well-studied young stellar associations, Taurus–Auriga, was observed by the extended Kepler mission, K2 , in the spring of 2017. K2 Campaign 13 (C13) is a unique opportunity to study many stars in this young association at high photometric precision and cadence. Using observations from the Kilodegree Extremely Little Telescope (KELT) survey, we identify “dippers,” aperiodic and periodic variables among K2 C13 target stars. This release of the KELT data (light curve data in e-tables) provides the community with long-time baseline observations to assist in the understanding of the more exotic variables in the association. Transient-like phenomena on timescales of months to years are known characteristics in the light curves of young stellar objects, making contextual pre- and post- K2 observations critical to understanding their underlying processes. We are providing a comprehensive set of the KELT light curves for known Taurus–Auriga stars in K2 C13. The combined data sets from K2 and KELT should permit a broad array of investigations related to star formation, stellar variability, and protoplanetary environments.

Identification of Young Stellar Variables with KELT for K2 . I. Taurus Dippers and Rotators

International Nuclear Information System (INIS)

Rodriguez, Joseph E.; Cargile, Phillip A.; Ansdell, Megan; Oelkers, Ryan J.; Somers, Garrett; Lund, Michael B.; Stassun, Keivan G.; Gaidos, Eric; Cody, Ann Marie; Stevens, Daniel J.; Gaudi, B. Scott; James, David; Beatty, Thomas G.; Siverd, Robert J.; Kuhn, Rudolf B.; Pepper, Joshua

2017-01-01

One of the most well-studied young stellar associations, Taurus–Auriga, was observed by the extended Kepler mission, K2 , in the spring of 2017. K2 Campaign 13 (C13) is a unique opportunity to study many stars in this young association at high photometric precision and cadence. Using observations from the Kilodegree Extremely Little Telescope (KELT) survey, we identify “dippers,” aperiodic and periodic variables among K2 C13 target stars. This release of the KELT data (light curve data in e-tables) provides the community with long-time baseline observations to assist in the understanding of the more exotic variables in the association. Transient-like phenomena on timescales of months to years are known characteristics in the light curves of young stellar objects, making contextual pre- and post- K2 observations critical to understanding their underlying processes. We are providing a comprehensive set of the KELT light curves for known Taurus–Auriga stars in K2 C13. The combined data sets from K2 and KELT should permit a broad array of investigations related to star formation, stellar variability, and protoplanetary environments.

Optical cryptography with biometrics for multi-depth objects.

Science.gov (United States)

Yan, Aimin; Wei, Yang; Hu, Zhijuan; Zhang, Jingtao; Tsang, Peter Wai Ming; Poon, Ting-Chung

2017-10-11

We propose an optical cryptosystem for encrypting images of multi-depth objects based on the combination of optical heterodyne technique and fingerprint keys. Optical heterodyning requires two optical beams to be mixed. For encryption, each optical beam is modulated by an optical mask containing either the fingerprint of the person who is sending, or receiving the image. The pair of optical masks are taken as the encryption keys. Subsequently, the two beams are used to scan over a multi-depth 3-D object to obtain an encrypted hologram. During the decryption process, each sectional image of the 3-D object is recovered by convolving its encrypted hologram (through numerical computation) with the encrypted hologram of a pinhole image that is positioned at the same depth as the sectional image. Our proposed method has three major advantages. First, the lost-key situation can be avoided with the use of fingerprints as the encryption keys. Second, the method can be applied to encrypt 3-D images for subsequent decrypted sectional images. Third, since optical heterodyning scanning is employed to encrypt a 3-D object, the optical system is incoherent, resulting in negligible amount of speckle noise upon decryption. To the best of our knowledge, this is the first time optical cryptography of 3-D object images has been demonstrated in an incoherent optical system with biometric keys.

A new spectroscopic and interferometric study of the young stellar object V645 Cygni

Science.gov (United States)

Miroshnichenko, A. S.; Hofmann, K.-H.; Schertl, D.; Weigelt, G.; Kraus, S.; Manset, N.; Albert, L.; Balega, Y. Y.; Klochkova, V. G.; Rudy, R. J.; Lynch, D. K.; Mazuk, S.; Venturini, C. C.; Russell, R. W.; Grankin, K. N.; Puetter, R. C.; Perry, R. B.

2009-04-01

Aims: We present the results of high-resolution optical spectroscopy, low-resolution near-IR spectroscopy and near-infrared speckle interferometry of the massive young stellar object candidate V645 Cyg, acquired to refine its fundamental parameters and the properties of its circumstellar envelope. Methods: Speckle interferometry in the H- and K-bands and an optical spectrum in the range 5200-6680 Å with a spectral resolving power of R = 60 000 were obtained at the 6 m telescope of the Russian Academy of Sciences. Another optical spectrum in the range 4300-10 500 Å with R = 79 000 was obtained at the 3.6 m CFHT. Low-resolution spectra in the ranges 0.46-1.4 μm and 1.4-2.5 μm with R ~ 800 and ~700, respectively, were obtained at the 3 m Shane telescope of the Lick Observatory. Results: Using a novel kinematical method based on the non-linear modeling of the neutral hydrogen density profile in the direction toward the object, we propose a distance of D = 4.2 ± 0.2 kpc. We also suggest a revised estimate of the star's effective temperature, T_eff ~ 25 000 K. We resolved the object in both H- and K-bands. Using a two-component ring fit, we derived a compact component size of 14 mas and 12 mas in the H- and K-band, respectively, which correspond to 29 and 26 AU at the revised distance. Analysis of our own and previously published data indicates a ~2 mag decrease in the near-infrared brightness of V645 Cyg at the beginning of the 1980's. At the same time, the cometary nebular condensation N1 appears to fade in this wavelength range with respect to the N0 object, representing the star with a nearly pole-on optically-thick disk and an optically-thin envelope. Conclusions: We conclude that V645 Cyg is a young, massive, main-sequence star, which recently emerged from its cocoon and has already experienced its protostellar accretion stage. The presence of accretion is not necessary to account for the high observed luminosity of (2-6) × 104 M⊙ yr-1. The receding part of

The Advanced Stellar Compass onboard the Oersted satellite

DEFF Research Database (Denmark)

Jørgensen, John Leif; Eisenman, Allan R.; Liebe, Carl Christian

1997-01-01

In 1997 the first Danish satellite will be launched. The primarily scientific objective of the satellite is to map the magnetic field of the Earth. The attitude of the satellite is determined by an advanced stellar compass (star tracker). An advanced stellar compass consists of a CCD camera...

Multi-objective reliability redundancy allocation in an interval environment using particle swarm optimization

International Nuclear Information System (INIS)

Zhang, Enze; Chen, Qingwei

2016-01-01

Most of the existing works addressing reliability redundancy allocation problems are based on the assumption of fixed reliabilities of components. In real-life situations, however, the reliabilities of individual components may be imprecise, most often given as intervals, under different operating or environmental conditions. This paper deals with reliability redundancy allocation problems modeled in an interval environment. An interval multi-objective optimization problem is formulated from the original crisp one, where system reliability and cost are simultaneously considered. To render the multi-objective particle swarm optimization (MOPSO) algorithm capable of dealing with interval multi-objective optimization problems, a dominance relation for interval-valued functions is defined with the help of our newly proposed order relations of interval-valued numbers. Then, the crowding distance is extended to the multi-objective interval-valued case. Finally, the effectiveness of the proposed approach has been demonstrated through two numerical examples and a case study of supervisory control and data acquisition (SCADA) system in water resource management. - Highlights: • We model the reliability redundancy allocation problem in an interval environment. • We apply the particle swarm optimization directly on the interval values. • A dominance relation for interval-valued multi-objective functions is defined. • The crowding distance metric is extended to handle imprecise objective functions.

Object recognition through a multi-mode fiber

Science.gov (United States)

Takagi, Ryosuke; Horisaki, Ryoichi; Tanida, Jun

2017-04-01

We present a method of recognizing an object through a multi-mode fiber. A number of speckle patterns transmitted through a multi-mode fiber are provided to a classifier based on machine learning. We experimentally demonstrated binary classification of face and non-face targets based on the method. The measurement process of the experimental setup was random and nonlinear because a multi-mode fiber is a typical strongly scattering medium and any reference light was not used in our setup. Comparisons between three supervised learning methods, support vector machine, adaptive boosting, and neural network, are also provided. All of those learning methods achieved high accuracy rates at about 90% for the classification. The approach presented here can realize a compact and smart optical sensor. It is practically useful for medical applications, such as endoscopy. Also our study indicated a promising utilization of artificial intelligence, which has rapidly progressed, for reducing optical and computational costs in optical sensing systems.

Complex engineering objects construction using Multi-D innovative technology

International Nuclear Information System (INIS)

Agafonov, Alexey

2013-01-01

Multi-D technology is an integrated innovative project management system for a construction of complex engineering objects based on a construction process simulation using an intellectual 3D model. Multi-D technology includes: • The unified schedule of E+P+C; • The schedule of loading of human resources, machines & mechanisms; • The budget of expenses and the income integrated with the schedule; • 3D model; • Multi-D model; • Weekly-daily tasks (with 4th level schedules); • Control system of interaction of Customer-EPC(m) company - Contractors; • Change and configuration management system

X-ray sources associated with young stellar objects in the star formation region CMa R1

Science.gov (United States)

Santos-Silva, Thais; Gregorio-Hetem, Jane; Montmerle, Thierry

2013-07-01

In previous works we studied the star formation scenario in the molecular cloud Canis Major R1 (CMa R1), derived from the existence of young stellar population groups near the Be stars Z CMa and GU CMa. Using data from the ROSAT X-ray satellite, having a field-of-view of ~ 1° in diameter, Gregorio-Hetem et al. (2009) discovered in this region young stellar objects mainly grouped in two clusters of different ages, with others located in between. In order to investigate the nature of these objects and to test a possible scenario of sequential star formation in this region, four fields (each 30 arcmin diameter, with some overlap) have been observed with the XMM-Newton satellite, with a sensitivity about 10 times better than ROSAT. The XMM-Newton data are currently under analysis. Preliminary results indicate the presence of about 324 sources, most of them apparently having one or more near-infrared counterparts showing typical colors of young stars. The youth of the X-ray sources was also confirmed by X-ray hardness ratio diagrams (XHRD), in different energy bands, giving an estimate of their Lx/Lbol ratios. In addition to these results, we present a detailed study of the XMM field covering the cluster near Z CMa. Several of these sources were classified as T Tauri and Herbig Ae/Be stars, using optical spectroscopy obtained with Gemini telescopes, in order to validate the use of XHRD applied to the entire sample. This classification is also used to confirm the relation between the luminosities in the near-infrared and X-ray bands expected for the T Tauri stars in CMa R1. In the present work we show the results of the study based on the spectra of about 90 sources found nearby Z CMa. We checked that the X-ray spectra (0.3 to 10 keV) of young objects is different from that observed in field stars and extragalactic objects. Some of the candidates also have light curve showing flares that are typical of T Tauri stars, which confirms the young nature of these X

Rotational stellar structures based on the Lagrangian variational principle

International Nuclear Information System (INIS)

Yasutake, Nobutoshi; Fujisawa, Kotaro; Yamada, Shoichi

2017-01-01

A new method for multi-dimensional stellar structures is proposed in this study. As for stellar evolution calculations, the Heney method is the defacto standard now, but basically assumed to be spherical symmetric. It is one of the difficulties for deformed stellar-evolution calculations to trace the potentially complex movements of each fluid element. On the other hand, our new method is very suitable to follow such movements, since it is based on the Lagrange coordinate. This scheme is also based on the variational principle, which is adopted to the studies for the pasta structures inside of neutron stars. Our scheme could be a major break through for evolution calculations of any types of deformed stars: proto-planets, proto-stars, and proto-neutron stars, etc. (paper)

Rotational stellar structures based on the Lagrangian variational principle

Science.gov (United States)

Yasutake, Nobutoshi; Fujisawa, Kotaro; Yamada, Shoichi

2017-06-01

A new method for multi-dimensional stellar structures is proposed in this study. As for stellar evolution calculations, the Heney method is the defacto standard now, but basically assumed to be spherical symmetric. It is one of the difficulties for deformed stellar-evolution calculations to trace the potentially complex movements of each fluid element. On the other hand, our new method is very suitable to follow such movements, since it is based on the Lagrange coordinate. This scheme is also based on the variational principle, which is adopted to the studies for the pasta structures inside of neutron stars. Our scheme could be a major break through for evolution calculations of any types of deformed stars: proto-planets, proto-stars, and proto-neutron stars, etc.

Strength Pareto particle swarm optimization and hybrid EA-PSO for multi-objective optimization.

Science.gov (United States)

Elhossini, Ahmed; Areibi, Shawki; Dony, Robert

2010-01-01

This paper proposes an efficient particle swarm optimization (PSO) technique that can handle multi-objective optimization problems. It is based on the strength Pareto approach originally used in evolutionary algorithms (EA). The proposed modified particle swarm algorithm is used to build three hybrid EA-PSO algorithms to solve different multi-objective optimization problems. This algorithm and its hybrid forms are tested using seven benchmarks from the literature and the results are compared to the strength Pareto evolutionary algorithm (SPEA2) and a competitive multi-objective PSO using several metrics. The proposed algorithm shows a slower convergence, compared to the other algorithms, but requires less CPU time. Combining PSO and evolutionary algorithms leads to superior hybrid algorithms that outperform SPEA2, the competitive multi-objective PSO (MO-PSO), and the proposed strength Pareto PSO based on different metrics.

A 1.3 mm SMA survey of 29 variable young stellar objects

Science.gov (United States)

Liu, Hauyu Baobab; Dunham, Michael M.; Pascucci, Ilaria; Bourke, Tyler L.; Hirano, Naomi; Longmore, Steven; Andrews, Sean; Carrasco-González, Carlos; Forbrich, Jan; Galván-Madrid, Roberto; Girart, Josep M.; Green, Joel D.; Juárez, Carmen; Kóspál, Ágnes; Manara, Carlo F.; Palau, Aina; Takami, Michihiro; Testi, Leonardo; Vorobyov, Eduard I.

2018-04-01

Context. Young stellar objects (YSOs) may undergo periods of active accretion (outbursts), during which the protostellar accretion rate is temporarily enhanced by a few orders of magnitude. Whether or not these accretion outburst YSOs possess similar dust and gas reservoirs to each other, and whether or not their dust and gas reservoirs are similar as quiescent YSOs, are issues yet to be clarified. Aims: The aim of this work is to characterize the millimeter thermal dust emission properties of a statistically significant sample of long and short duration accretion outburst YSOs (i.e., FUors and EXors) and the spectroscopically identified candidates of accretion outbursting YSOs (i.e., FUor-like objects). Methods: We have carried out extensive Submillimeter Array (SMA) observations mostly at 225 GHz (1.33 mm) and 272 GHz (1.10 mm), from 2008 to 2017. We covered accretion outburst YSOs located at database of 29 objects. We obtained 21 detections at >3σ significance. Detected sources except for the two cases of V883 Ori and NGC 2071 MM3 were observed with 1″ angular resolution. Overall our observed targets show a systematically higher millimeter luminosity distribution than those of the M* > 0.3 M⊙ Class II YSOs in the nearby (≲400 pc) low-mass star-forming molecular clouds (e.g., Taurus, Lupus, Upp Scorpio, and Chameleon I). In addition, at 1 mm our observed confirmed binaries or triple-system sources are systematically fainter than the rest of the sources even though their 1 mm fluxes are broadly distributed. We may have detected 30-60% millimeter flux variability from V2494 Cyg and V2495 Cyg, from the observations separated by approximately one year.

Multi-Objective Optimization of Managed Aquifer Recharge.

Science.gov (United States)

Fatkhutdinov, Aybulat; Stefan, Catalin

2018-04-27

This study demonstrates the utilization of a multi-objective hybrid global/local optimization algorithm for solving managed aquifer recharge (MAR) design problems, in which the decision variables included spatial arrangement of water injection and abstraction wells and time-variant rates of pumping and injection. The objective of the optimization was to maximize the efficiency of the MAR scheme, which includes both quantitative and qualitative aspects. The case study used to demonstrate the capabilities of the proposed approach is based on a published report on designing a real MAR site with defined aquifer properties, chemical groundwater characteristics as well as quality and volumes of injected water. The demonstration problems include steady-state and transient scenarios. The steady-state scenario demonstrates optimization of spatial arrangement of multiple injection and recovery wells, whereas the transient scenario was developed with the purpose of finding optimal regimes of water injection and recovery at a single location. Both problems were defined as multi-objective problems. The scenarios were simulated by applying coupled numerical groundwater flow and solute transport models: MODFLOW-2005 and MT3D-USGS. The applied optimization method was a combination of global - the Non-Dominated Sorting Genetic Algorithm (NSGA-2), and local - the Nelder-Mead Downhill Simplex search algorithms. The analysis of the resulting Pareto optimal solutions led to the discovery of valuable patterns and dependencies between the decision variables, model properties and problem objectives. Additionally, the performance of the traditional global and the hybrid optimization schemes were compared. This article is protected by copyright. All rights reserved.

Intuitionistic Fuzzy Goal Programming Technique for Solving Non-Linear Multi-objective Structural Problem

Directory of Open Access Journals (Sweden)

Samir Dey

2015-07-01

Full Text Available This paper proposes a new multi-objective intuitionistic fuzzy goal programming approach to solve a multi-objective nonlinear programming problem in context of a structural design. Here we describe some basic properties of intuitionistic fuzzy optimization. We have considered a multi-objective structural optimization problem with several mutually conflicting objectives. The design objective is to minimize weight of the structure and minimize the vertical deflection at loading point of a statistically loaded three-bar planar truss subjected to stress constraints on each of the truss members. This approach is used to solve the above structural optimization model based on arithmetic mean and compare with the solution by intuitionistic fuzzy goal programming approach. A numerical solution is given to illustrate our approach.

An experimental analysis of design choices of multi-objective ant colony optimization algorithms

OpenAIRE

Lopez-Ibanez, Manuel; Stutzle, Thomas

2012-01-01

There have been several proposals on how to apply the ant colony optimization (ACO) metaheuristic to multi-objective combinatorial optimization problems (MOCOPs). This paper proposes a new formulation of these multi-objective ant colony optimization (MOACO) algorithms. This formulation is based on adding specific algorithm components for tackling multiple objectives to the basic ACO metaheuristic. Examples of these components are how to represent multiple objectives using pheromone and heuris...

Energy-Efficient Scheduling Problem Using an Effective Hybrid Multi-Objective Evolutionary Algorithm

Directory of Open Access Journals (Sweden)

Lvjiang Yin

2016-12-01

Full Text Available Nowadays, manufacturing enterprises face the challenge of just-in-time (JIT production and energy saving. Therefore, study of JIT production and energy consumption is necessary and important in manufacturing sectors. Moreover, energy saving can be attained by the operational method and turn off/on idle machine method, which also increases the complexity of problem solving. Thus, most researchers still focus on small scale problems with one objective: a single machine environment. However, the scheduling problem is a multi-objective optimization problem in real applications. In this paper, a single machine scheduling model with controllable processing and sequence dependence setup times is developed for minimizing the total earliness/tardiness (E/T, cost, and energy consumption simultaneously. An effective multi-objective evolutionary algorithm called local multi-objective evolutionary algorithm (LMOEA is presented to tackle this multi-objective scheduling problem. To accommodate the characteristic of the problem, a new solution representation is proposed, which can convert discrete combinational problems into continuous problems. Additionally, a multiple local search strategy with self-adaptive mechanism is introduced into the proposed algorithm to enhance the exploitation ability. The performance of the proposed algorithm is evaluated by instances with comparison to other multi-objective meta-heuristics such as Nondominated Sorting Genetic Algorithm II (NSGA-II, Strength Pareto Evolutionary Algorithm 2 (SPEA2, Multiobjective Particle Swarm Optimization (OMOPSO, and Multiobjective Evolutionary Algorithm Based on Decomposition (MOEA/D. Experimental results demonstrate that the proposed LMOEA algorithm outperforms its counterparts for this kind of scheduling problems.

8th International Conference on Multi-Objective and Goal Programming

CERN Document Server

Tamiz, Mehrdad; Ries, Jana

2010-01-01

This volume shows the state-of-the-art in both theoretical development and application of multiple objective and goal programming. Applications from the fields of supply chain management, financial portfolio selection, financial risk management, insurance, medical imaging, sustainability, nurse scheduling, project management, water resource management, and the interface with data envelopment analysis give a good reflection of current usage. A pleasing variety of techniques are used including models with fuzzy, group-decision, stochastic, interactive, and binary aspects. Additionally, two papers from the upcoming area of multi-objective evolutionary algorithms are included. The book is based on the papers of the 8th International Conference on Multi-Objective and Goal Programming (MOPGP08) which was held in Portsmouth, UK, in September 2008.

SUZAKU OBSERVATION OF STRONG FLUORESCENT IRON LINE EMISSION FROM THE YOUNG STELLAR OBJECT V1647 ORI DURING ITS NEW X-RAY OUTBURST

International Nuclear Information System (INIS)

Hamaguchi, Kenji; Grosso, Nicolas; Kastner, Joel H.; Richmond, Michael; Weintraub, David A.

2010-01-01

The Suzaku X-ray satellite observed the young stellar object (YSO) V1647 Ori on 2008 October 8 during the new mass accretion outburst reported in 2008 August. During the 87 ks observation with a net exposure of 40 ks, V1647 Ori showed a high level of X-ray emission with a gradual decrease in flux by a factor of 5 and then displayed an abrupt flux increase by an order of magnitude. Such enhanced X-ray variability was also seen in XMM-Newton observations in 2004 and 2005 during the 2003-2005 outburst, but has rarely been observed for other YSOs. The spectrum clearly displays emission from Helium-like iron, which is a signature of hot plasma (kT ∼ 5 keV). It also shows a fluorescent iron Kα line with a remarkably large equivalent width (EW) of ∼600 eV. Such a large EW suggests that a part of the incident X-ray emission that irradiates the circumstellar material and/or the stellar surface is hidden from our line of sight. XMM-Newton spectra during the 2003-2005 outburst did not show a strong fluorescent iron Kα line, so that the structure of the circumstellar gas very close to the stellar core that absorbs and re-emits X-ray emission from the central object may have changed in between 2005 and 2008. This phenomenon may be related to changes in the infrared morphology of McNeil's nebula between 2004 and 2008.

Predictions of stellar occultations by TNOs/Centaurs using Gaia

Science.gov (United States)

Desmars, Josselin; Camargo, Julio; Berard, Diane; Sicardy, Bruno; Leiva, Rodrigo; Vieira-Martins, Roberto; Braga-Ribas, Felipe; Assafin, Marcelo; Rossi, Gustavo; Chariklo occultations Team, Rio Group, Lucky Star Occultation Team, Granada Occultation Team

2017-10-01

Stellar occultations are the unique technique from the ground to access physical parameters of the distant solar system objects, such as the measure of the size and the shape at kilometric level, the detection of tenuous atmospheres (few nanobars), and the investigation of close vicinity (satellites, rings, jets).Predictions of stellar occultations require accurate positions of the star and the object.The Gaia DR1 catalog now allows to get stellar position to the milliarcsecond (mas) level. The main uncertainty in the prediction remains in the position of the object (tens to hundreds of mas).Now, we take advantage of the NIMA method for the orbit determination that uses the most recent observations reduced by the Gaia DR1 catalog and the astrometric positions derived from previous positive occultations.Up to now, we have detected nearly 50 positive occultations for about 20 objects that provide astrometric positions of the object at the time of the occultation. The uncertainty of these positions only depends on the uncertainty on the position of the occulted stars, which is a few mas with the Gaia DR1 catalog. The main limitation is now on the proper motion of the star which is only given for bright stars in the Tycho-Gaia Astrometric Solution. This limitation will be solved with the publicationof the Gaia DR2 expected on April 2018 giving proper motions and parallaxes for the Gaia stars. Until this date, we use hybrid stellar catalogs (UCAC5, HSOY) that provide proper motions derived from Gaia DR1 and another stellar catalog.Recently, the Gaia team presented a release of three preliminary Gaia DR2 stellar positions involved in the occultations by Chariklo (22 June and 23 July 2017) and by Triton (5 October 2017).Taking the case of Chariklo as an illustration, we will present a comparison between the proper motions of DR2 and the other catalogs and we will show how the Gaia DR2 will lead to a mas level precision in the orbit and in the prediction of stellar

Multi-objective optimization of a plate and frame heat exchanger via genetic algorithm

Energy Technology Data Exchange (ETDEWEB)

Najafi, Hamidreza; Najafi, Behzad [K. N. Toosi University of Technology, Department of Mechanical Engineering, Tehran (Iran)

2010-06-15

In the present paper, a plate and frame heat exchanger is considered. Multi-objective optimization using genetic algorithm is developed in order to obtain a set of geometric design parameters, which lead to minimum pressure drop and the maximum overall heat transfer coefficient. Vividly, considered objective functions are conflicting and no single solution can satisfy both objectives simultaneously. Multi-objective optimization procedure yields a set of optimal solutions, called Pareto front, each of which is a trade-off between objectives and can be selected by the user, regarding the application and the project's limits. The presented work takes care of numerous geometric parameters in the presence of logical constraints. A sensitivity analysis is also carried out to study the effects of different geometric parameters on the considered objective functions. Modeling the system and implementing the multi-objective optimization via genetic algorithm has been performed by MATLAB. (orig.)

METALLICITY AND AGE OF THE STELLAR STREAM AROUND THE DISK GALAXY NGC 5907

Energy Technology Data Exchange (ETDEWEB)

Laine, Seppo; Grillmair, Carl J.; Capak, Peter [Spitzer Science Center-Caltech, MS 314-6, Pasadena, CA 91125 (United States); Arendt, Richard G. [CRESST/UMBC/NASA GSFC, Code 665, Greenbelt, MD 20771 (United States); Romanowsky, Aaron J. [Department of Physics and Astronomy, San José State University, One Washington Square, San Jose, CA 95192 (United States); Martínez-Delgado, David [Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg, Mönchhofstr. 12-14, D-69120 Heidelberg (Germany); Ashby, Matthew L. N. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Davies, James E. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Majewski, Stephen R. [Department of Astronomy, University of Virginia, P.O. Box 400325, Charlottesville, VA 22904-4325 (United States); Brodie, Jean P.; Arnold, Jacob A. [University of California Observatories and Department of Astronomy and Astrophysics, University of California, 1156 High Street, Santa Cruz, CA 95064 (United States); GaBany, R. Jay, E-mail: seppo@ipac.caltech.edu [Black Bird Observatory, 5660 Brionne Drive, San Jose, CA 95118 (United States)

2016-09-01

Stellar streams have become central to studies of the interaction histories of nearby galaxies. To characterize the most prominent parts of the stellar stream around the well-known nearby ( d  = 17 Mpc) edge-on disk galaxy NGC 5907, we have obtained and analyzed new, deep gri Subaru/Suprime-Cam and 3.6 μ m Spitzer /Infrared Array Camera observations. Combining the near-infrared 3.6 μ m data with visible-light images allows us to use a long wavelength baseline to estimate the metallicity and age of the stellar population along an ∼60 kpc long segment of the stream. We have fitted the stellar spectral energy distribution with a single-burst stellar population synthesis model and we use it to distinguish between the proposed satellite accretion and minor/major merger formation models of the stellar stream around this galaxy. We conclude that a massive minor merger (stellar mass ratio of at least 1:8) can best account for the metallicity of −0.3 inferred along the brightest parts of the stream.

Detection of water masers toward young stellar objects in the Large Magellanic Cloud

International Nuclear Information System (INIS)

Johanson, A. K.; Migenes, V.; Breen, S. L.

2014-01-01

We present results from a search for water maser emission toward N4A, N190, and N206, three regions of massive star formation in the Large Magellanic Cloud (LMC). Four water masers were detected; two toward N4A, and two toward N190. In the latter region, no previously known maser emission has been reported. Future studies of maser proper motion to determine the galactic dynamics of the LMC will benefit from the independent data points the new masers in N190 provide. Two of these masers are associated with previously identified massive young stellar objects (YSOs), which strongly supports the authenticity of the classification. We argue that the other two masers identify previously unknown YSOs. No masers were detected toward N206, but it does host a newly discovered 22 GHz continuum source, also associated with a massive YSO. We suggest that future surveys for water maser emission in the LMC be targeted toward the more luminous, massive YSOs.

A 'variable' stellar object in a variable blue nebula V-V 1-7

International Nuclear Information System (INIS)

Rao, N.K.; Gilra, D.P.

1981-01-01

V-V 1-7 is supposed to be one of the few planetary nebulae with Ao central stars and was included in the planetary-nebula catalogue as PK 235 + 1 0 1. The nebula was seen on the blue Palomar Observatory Sky Survey (POSS) print but not on the red print; as a result it was thought that it might be a reflection nebula. However, the symmetry of the nebula around the central star (HD 62001), and also the ultraviolet photometric variability of this central star led others to suggest that the nebula might be a nova shell. Subsequently it was found that the nebula V-V 1-7 has disappeared. It is not seen on any direct plate known to us except the POSS blue plate. In this paper the disappearance is reported (along with the nebula) of a stellar object, which appears within the 'nebular shell' of V-V 1-7 on the POSS blue plate, but not on the red plate. (author)

MONSS: A multi-objective nonlinear simplex search approach

Science.gov (United States)

Zapotecas-Martínez, Saúl; Coello Coello, Carlos A.

2016-01-01

This article presents a novel methodology for dealing with continuous box-constrained multi-objective optimization problems (MOPs). The proposed algorithm adopts a nonlinear simplex search scheme in order to obtain multiple elements of the Pareto optimal set. The search is directed by a well-distributed set of weight vectors, each of which defines a scalarization problem that is solved by deforming a simplex according to the movements described by Nelder and Mead's method. Considering an MOP with n decision variables, the simplex is constructed using n+1 solutions which minimize different scalarization problems defined by n+1 neighbor weight vectors. All solutions found in the search are used to update a set of solutions considered to be the minima for each separate problem. In this way, the proposed algorithm collectively obtains multiple trade-offs among the different conflicting objectives, while maintaining a proper representation of the Pareto optimal front. In this article, it is shown that a well-designed strategy using just mathematical programming techniques can be competitive with respect to the state-of-the-art multi-objective evolutionary algorithms against which it was compared.

Improved multi-objective clustering algorithm using particle swarm optimization.

Science.gov (United States)

Gong, Congcong; Chen, Haisong; He, Weixiong; Zhang, Zhanliang

2017-01-01

Multi-objective clustering has received widespread attention recently, as it can obtain more accurate and reasonable solution. In this paper, an improved multi-objective clustering framework using particle swarm optimization (IMCPSO) is proposed. Firstly, a novel particle representation for clustering problem is designed to help PSO search clustering solutions in continuous space. Secondly, the distribution of Pareto set is analyzed. The analysis results are applied to the leader selection strategy, and make algorithm avoid trapping in local optimum. Moreover, a clustering solution-improved method is proposed, which can increase the efficiency in searching clustering solution greatly. In the experiments, 28 datasets are used and nine state-of-the-art clustering algorithms are compared, the proposed method is superior to other approaches in the evaluation index ARI.

Compressed multi-block local binary pattern for object tracking

Science.gov (United States)

Li, Tianwen; Gao, Yun; Zhao, Lei; Zhou, Hao

2018-04-01

Both robustness and real-time are very important for the application of object tracking under a real environment. The focused trackers based on deep learning are difficult to satisfy with the real-time of tracking. Compressive sensing provided a technical support for real-time tracking. In this paper, an object can be tracked via a multi-block local binary pattern feature. The feature vector was extracted based on the multi-block local binary pattern feature, which was compressed via a sparse random Gaussian matrix as the measurement matrix. The experiments showed that the proposed tracker ran in real-time and outperformed the existed compressive trackers based on Haar-like feature on many challenging video sequences in terms of accuracy and robustness.

Multi-objective Design Method for Hybrid Active Power Filter

Science.gov (United States)

Yu, Jingrong; Deng, Limin; Liu, Maoyun; Qiu, Zhifeng

2017-10-01

In this paper, a multi-objective optimal design for transformerless hybrid active power filter (HAPF) is proposed. The interactions between the active and passive circuits is analyzed, and by taking the interactions into consideration, a three-dimensional objective problem comprising of performance, efficiency and cost of HAPF system is formulated. To deal with the multiple constraints and the strong coupling characteristics of the optimization model, a novel constraint processing mechanism based on distance measurement and adaptive penalty function is presented. In order to improve the diversity of optimal solution and the local searching ability of the particle swarm optimization (PSO) algorithm, a chaotic mutation operator based on multistage neighborhood is proposed. The simulation results show that the optimums near the ordinate origin of the three-dimension space make better tradeoff among the performance, efficiency and cost of HAPF, and the experimental results of transformerless HAPF verify the effectiveness of the method for multi-objective optimization and design.

First results of the multi-purpose real-time processing video camera system on the Wendelstein 7-X stellarator and implications for future devices

Science.gov (United States)

Zoletnik, S.; Biedermann, C.; Cseh, G.; Kocsis, G.; König, R.; Szabolics, T.; Szepesi, T.; Wendelstein 7-X Team

2018-01-01

A special video camera has been developed for the 10-camera overview video system of the Wendelstein 7-X (W7-X) stellarator considering multiple application needs and limitations resulting from this complex long-pulse superconducting stellarator experiment. The event detection intelligent camera (EDICAM) uses a special 1.3 Mpixel CMOS sensor with non-destructive read capability which enables fast monitoring of smaller Regions of Interest (ROIs) even during long exposures. The camera can perform simple data evaluation algorithms (minimum/maximum, mean comparison to levels) on the ROI data which can dynamically change the readout process and generate output signals. Multiple EDICAM cameras were operated in the first campaign of W7-X and capabilities were explored in the real environment. Data prove that the camera can be used for taking long exposure (10-100 ms) overview images of the plasma while sub-ms monitoring and even multi-camera correlated edge plasma turbulence measurements of smaller areas can be done in parallel. These latter revealed that filamentary turbulence structures extend between neighboring modules of the stellarator. Considerations emerging for future upgrades of this system and similar setups on future long-pulse fusion experiments such as ITER are discussed.

Multi-objective optimization of Stirling engine systems using Front-based Yin-Yang-Pair Optimization

International Nuclear Information System (INIS)

Punnathanam, Varun; Kotecha, Prakash

2017-01-01

Highlights: • Efficient multi-objective optimization algorithm F-YYPO demonstrated. • Three Stirling engine applications with a total of eight cases. • Improvements in the objective function values of up to 30%. • Superior to the popularly used gamultiobj of MATLAB. • F-YYPO has extremely low time complexity. - Abstract: In this work, we demonstrate the performance of Front-based Yin-Yang-Pair Optimization (F-YYPO) to solve multi-objective problems related to Stirling engine systems. The performance of F-YYPO is compared with that of (i) a recently proposed multi-objective optimization algorithm (Multi-Objective Grey Wolf Optimizer) and (ii) an algorithm popularly employed in literature due to its easy accessibility (MATLAB’s inbuilt multi-objective Genetic Algorithm function: gamultiobj). We consider three Stirling engine based optimization problems: (i) the solar-dish Stirling engine system which considers objectives of output power, thermal efficiency and rate of entropy generation; (ii) Stirling engine thermal model which considers the associated irreversibility of the cycle with objectives of output power, thermal efficiency and pressure drop; and finally (iii) an experimentally validated polytropic finite speed thermodynamics based Stirling engine model also with objectives of output power and pressure drop. We observe F-YYPO to be significantly more effective as compared to its competitors in solving the problems, while requiring only a fraction of the computational time required by the other algorithms.

Study on hybrid multi-objective optimization algorithm for inverse treatment planning of radiation therapy

International Nuclear Information System (INIS)

Li Guoli; Song Gang; Wu Yican

2007-01-01

Inverse treatment planning for radiation therapy is a multi-objective optimization process. The hybrid multi-objective optimization algorithm is studied by combining the simulated annealing(SA) and genetic algorithm(GA). Test functions are used to analyze the efficiency of algorithms. The hybrid multi-objective optimization SA algorithm, which displacement is based on the evolutionary strategy of GA: crossover and mutation, is implemented in inverse planning of external beam radiation therapy by using two kinds of objective functions, namely the average dose distribution based and the hybrid dose-volume constraints based objective functions. The test calculations demonstrate that excellent converge speed can be achieved. (authors)

Evolving intelligent vehicle control using multi-objective NEAT

NARCIS (Netherlands)

Willigen, W.H. van; Haasdijk, E.; Kester, L.J.H.M.

2013-01-01

The research in this paper is inspired by a vision of intelligent vehicles that autonomously move along motorways: they join and leave trains of vehicles (platoons), overtake other vehicles, etc. We propose a multi-objective algorithm based on NEAT and SPEA2 that evolves controllers for such

Pareto-optimal multi-objective dimensionality reduction deep auto-encoder for mammography classification.

Science.gov (United States)

Taghanaki, Saeid Asgari; Kawahara, Jeremy; Miles, Brandon; Hamarneh, Ghassan

2017-07-01

Feature reduction is an essential stage in computer aided breast cancer diagnosis systems. Multilayer neural networks can be trained to extract relevant features by encoding high-dimensional data into low-dimensional codes. Optimizing traditional auto-encoders works well only if the initial weights are close to a proper solution. They are also trained to only reduce the mean squared reconstruction error (MRE) between the encoder inputs and the decoder outputs, but do not address the classification error. The goal of the current work is to test the hypothesis that extending traditional auto-encoders (which only minimize reconstruction error) to multi-objective optimization for finding Pareto-optimal solutions provides more discriminative features that will improve classification performance when compared to single-objective and other multi-objective approaches (i.e. scalarized and sequential). In this paper, we introduce a novel multi-objective optimization of deep auto-encoder networks, in which the auto-encoder optimizes two objectives: MRE and mean classification error (MCE) for Pareto-optimal solutions, rather than just MRE. These two objectives are optimized simultaneously by a non-dominated sorting genetic algorithm. We tested our method on 949 X-ray mammograms categorized into 12 classes. The results show that the features identified by the proposed algorithm allow a classification accuracy of up to 98.45%, demonstrating favourable accuracy over the results of state-of-the-art methods reported in the literature. We conclude that adding the classification objective to the traditional auto-encoder objective and optimizing for finding Pareto-optimal solutions, using evolutionary multi-objective optimization, results in producing more discriminative features. Copyright © 2017 Elsevier B.V. All rights reserved.

Fusion of space-borne multi-baseline and multi-frequency interferometric results based on extended Kalman filter to generate high quality DEMs

Science.gov (United States)

Zhang, Xiaojie; Zeng, Qiming; Jiao, Jian; Zhang, Jingfa

2016-01-01

Repeat-pass Interferometric Synthetic Aperture Radar (InSAR) is a technique that can be used to generate DEMs. But the accuracy of InSAR is greatly limited by geometrical distortions, atmospheric effect, and decorrelations, particularly in mountainous areas, such as western China where no high quality DEM has so far been accomplished. Since each of InSAR DEMs generated using data of different frequencies and baselines has their own advantages and disadvantages, it is therefore very potential to overcome some of the limitations of InSAR by fusing Multi-baseline and Multi-frequency Interferometric Results (MMIRs). This paper proposed a fusion method based on Extended Kalman Filter (EKF), which takes the InSAR-derived DEMs as states in prediction step and the flattened interferograms as observations in control step to generate the final fused DEM. Before the fusion, detection of layover and shadow regions, low-coherence regions and regions with large height error is carried out because MMIRs in these regions are believed to be unreliable and thereafter are excluded. The whole processing flow is tested with TerraSAR-X and Envisat ASAR datasets. Finally, the fused DEM is validated with ASTER GDEM and national standard DEM of China. The results demonstrate that the proposed method is effective even in low coherence areas.

A scalable coevolutionary multi-objective particle swarm optimizer

Directory of Open Access Journals (Sweden)

Xiangwei Zheng

2010-11-01

Full Text Available Multi-Objective Particle Swarm Optimizers (MOPSOs are easily trapped in local optima, cost more function evaluations and suffer from the curse of dimensionality. A scalable cooperative coevolution and ?-dominance based MOPSO (CEPSO is proposed to address these issues. In CEPSO, Multi-objective Optimization Problems (MOPs are decomposed in terms of their decision variables and are optimized by cooperative coevolutionary subswarms, and a uniform distribution mutation operator is adopted to avoid premature convergence. All subswarms share an external archive based on ?-dominance, which is also used as a leader set. Collaborators are selected from the archive and used to construct context vectors in order to evaluate particles in a subswarm. CEPSO is tested on several classical MOP benchmark functions and experimental results show that CEPSO can readily escape from local optima and optimize both low and high dimensional problems, but the number of function evaluations only increases linearly with respect to the number of decision variables. Therefore, CEPSO is competitive in solving various MOPs.

Multi-objective optimization of a continuous bio-dissimilation process of glycerol to 1, 3-propanediol.

Science.gov (United States)

Xu, Gongxian; Liu, Ying; Gao, Qunwang

2016-02-10

This paper deals with multi-objective optimization of continuous bio-dissimilation process of glycerol to 1, 3-propanediol. In order to maximize the production rate of 1, 3-propanediol, maximize the conversion rate of glycerol to 1, 3-propanediol, maximize the conversion rate of glycerol, and minimize the concentration of by-product ethanol, we first propose six new multi-objective optimization models that can simultaneously optimize any two of the four objectives above. Then these multi-objective optimization problems are solved by using the weighted-sum and normal-boundary intersection methods respectively. Both the Pareto filter algorithm and removal criteria are used to remove those non-Pareto optimal points obtained by the normal-boundary intersection method. The results show that the normal-boundary intersection method can successfully obtain the approximate Pareto optimal sets of all the proposed multi-objective optimization problems, while the weighted-sum approach cannot achieve the overall Pareto optimal solutions of some multi-objective problems. Copyright © 2015 Elsevier B.V. All rights reserved.

Combining simulation and multi-objective optimisation for equipment quantity optimisation in container terminals

OpenAIRE

Lin, Zhougeng

2013-01-01

This thesis proposes a combination framework to integrate simulation and multi-objective optimisation (MOO) for container terminal equipment optimisation. It addresses how the strengths of simulation and multi-objective optimisation can be integrated to find high quality solutions for multiple objectives with low computational cost. Three structures for the combination framework are proposed respectively: pre-MOO structure, integrated MOO structure and post-MOO structure. The applications of ...

A multi-objective programming model for assessment the GHG emissions in MSW management

Energy Technology Data Exchange (ETDEWEB)

Mavrotas, George, E-mail: mavrotas@chemeng.ntua.gr [National Technical University of Athens, Iroon Polytechniou 9, Zografou, Athens, 15780 (Greece); Skoulaxinou, Sotiria [EPEM SA, 141 B Acharnon Str., Athens, 10446 (Greece); Gakis, Nikos [FACETS SA, Agiou Isidorou Str., Athens, 11471 (Greece); Katsouros, Vassilis [Athena Research and Innovation Center, Artemidos 6 and Epidavrou Str., Maroussi, 15125 (Greece); Georgopoulou, Elena [National Observatory of Athens, Thisio, Athens, 11810 (Greece)

2013-09-15

Highlights: • The multi-objective multi-period optimization model. • The solution approach for the generation of the Pareto front with mathematical programming. • The very detailed description of the model (decision variables, parameters, equations). • The use of IPCC 2006 guidelines for landfill emissions (first order decay model) in the mathematical programming formulation. - Abstract: In this study a multi-objective mathematical programming model is developed for taking into account GHG emissions for Municipal Solid Waste (MSW) management. Mathematical programming models are often used for structure, design and operational optimization of various systems (energy, supply chain, processes, etc.). The last twenty years they are used all the more often in Municipal Solid Waste (MSW) management in order to provide optimal solutions with the cost objective being the usual driver of the optimization. In our work we consider the GHG emissions as an additional criterion, aiming at a multi-objective approach. The Pareto front (Cost vs. GHG emissions) of the system is generated using an appropriate multi-objective method. This information is essential to the decision maker because he can explore the trade-offs in the Pareto curve and select his most preferred among the Pareto optimal solutions. In the present work a detailed multi-objective, multi-period mathematical programming model is developed in order to describe the waste management problem. Apart from the bi-objective approach, the major innovations of the model are (1) the detailed modeling considering 34 materials and 42 technologies, (2) the detailed calculation of the energy content of the various streams based on the detailed material balances, and (3) the incorporation of the IPCC guidelines for the CH{sub 4} generated in the landfills (first order decay model). The equations of the model are described in full detail. Finally, the whole approach is illustrated with a case study referring to the

A multi-objective programming model for assessment the GHG emissions in MSW management

International Nuclear Information System (INIS)

Mavrotas, George; Skoulaxinou, Sotiria; Gakis, Nikos; Katsouros, Vassilis; Georgopoulou, Elena

2013-01-01

Highlights: • The multi-objective multi-period optimization model. • The solution approach for the generation of the Pareto front with mathematical programming. • The very detailed description of the model (decision variables, parameters, equations). • The use of IPCC 2006 guidelines for landfill emissions (first order decay model) in the mathematical programming formulation. - Abstract: In this study a multi-objective mathematical programming model is developed for taking into account GHG emissions for Municipal Solid Waste (MSW) management. Mathematical programming models are often used for structure, design and operational optimization of various systems (energy, supply chain, processes, etc.). The last twenty years they are used all the more often in Municipal Solid Waste (MSW) management in order to provide optimal solutions with the cost objective being the usual driver of the optimization. In our work we consider the GHG emissions as an additional criterion, aiming at a multi-objective approach. The Pareto front (Cost vs. GHG emissions) of the system is generated using an appropriate multi-objective method. This information is essential to the decision maker because he can explore the trade-offs in the Pareto curve and select his most preferred among the Pareto optimal solutions. In the present work a detailed multi-objective, multi-period mathematical programming model is developed in order to describe the waste management problem. Apart from the bi-objective approach, the major innovations of the model are (1) the detailed modeling considering 34 materials and 42 technologies, (2) the detailed calculation of the energy content of the various streams based on the detailed material balances, and (3) the incorporation of the IPCC guidelines for the CH 4 generated in the landfills (first order decay model). The equations of the model are described in full detail. Finally, the whole approach is illustrated with a case study referring to the application

Multi-objective optimization of a continuous thermally regenerative electrochemical cycle for waste heat recovery

International Nuclear Information System (INIS)

Long, Rui; Li, Baode; Liu, Zhichun; Liu, Wei

2015-01-01

An optimization analysis of a continuous TREC (thermally regenerative electrochemical cycle) was conducted with maximum power output and exergy efficiency as the objective functions simultaneously. For comparison, the power output, exergy efficiency, and thermal efficiency under the corresponding single-objective optimization schematics were also calculated. Under different optimization methods it was observed that the power output and the thermal efficiency increase with increasing inlet temperature of the heat source, whereas the exergy efficiency increases with increasing inlet temperature, reaches a maximum value, and then decreases. Results revealed that the optimal power output under the multi-objective optimization turned out to be slightly less than that obtained under the single-objective optimization for power output. However, the exergy and thermal efficiencies were much greater. Furthermore, the thermal exergy and exergy efficiency by single-objective optimization for energy efficiency shows no dominant advantage than that obtained under multi-objective optimization, comparing with the increase amplitude of the power output. This suggests that the multi-objective optimization could coordinate well both the power output and the exergy efficiency of the TREC system, and may serve as a more promising guide for operating and designing TREC systems. - Highlights: • An optimal analysis of a continuous TREC is conducted based on multi-objective optimization. • Performance under corresponding single-objective optimizations has also been calculated and compared. • Power under multi-objective optimization is slightly less than the maximum power. • Exergy and thermal efficiencies are much larger than that under the single-objective optimization.

Evaluation of cephalogram using multi-objective frequency processing

Energy Technology Data Exchange (ETDEWEB)

Hagiwara, Sakae; Takizawa, Tsutomu; Osako, Miho; Kaneda, Takashi; Kasai, Kazutaka [Nihon Univ., Chiba (Japan). School of Dentistry at Matsudo

2002-12-01

A diagnosis with cephalogram is important for orthodontic treatment. Recently, computed radiography (CR) has been performed to the cephalogram. However, evaluation of multi-objective frequency processing (MFP) for cephalograms has been received little attention. The purpose of this study was to evaluate the cephalogram using MFP CR. At first, 450 lateral cephalograms were made, from 50 orthodontic patients, with 9 possible spatial frequency parameter combinations and a contrast scale held fixed in images processing. For each film, the clarity of radiographic images were estimated and scored with respect to landmark identification (total 26 points, 20 points of hard tissue and 6 points of soft tissue). A specific combination of spatial frequency scales (multi-frequency balance types (MRB) F-type, multi-frequency enhancement (MRE) 8) was proved to be adequate to achieve the optimal image quality in the cephalogram. (author)

Evaluation of cephalogram using multi-objective frequency processing

International Nuclear Information System (INIS)

Hagiwara, Sakae; Takizawa, Tsutomu; Osako, Miho; Kaneda, Takashi; Kasai, Kazutaka

2002-01-01

A diagnosis with cephalogram is important for orthodontic treatment. Recently, computed radiography (CR) has been performed to the cephalogram. However, evaluation of multi-objective frequency processing (MFP) for cephalograms has been received little attention. The purpose of this study was to evaluate the cephalogram using MFP CR. At first, 450 lateral cephalograms were made, from 50 orthodontic patients, with 9 possible spatial frequency parameter combinations and a contrast scale held fixed in images processing. For each film, the clarity of radiographic images were estimated and scored with respect to landmark identification (total 26 points, 20 points of hard tissue and 6 points of soft tissue). A specific combination of spatial frequency scales (multi-frequency balance types (MRB) F-type, multi-frequency enhancement (MRE) 8) was proved to be adequate to achieve the optimal image quality in the cephalogram. (author)

Multi-objective optimization in quantum parameter estimation

Science.gov (United States)

Gong, BeiLi; Cui, Wei

2018-04-01

We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved, it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives: (1) maximizing the Fisher information, improving the parameter estimation precision, and (2) minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ɛ-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.

Hydro-environmental management of groundwater resources: A fuzzy-based multi-objective compromise approach

Science.gov (United States)

Alizadeh, Mohammad Reza; Nikoo, Mohammad Reza; Rakhshandehroo, Gholam Reza

2017-08-01

Sustainable management of water resources necessitates close attention to social, economic and environmental aspects such as water quality and quantity concerns and potential conflicts. This study presents a new fuzzy-based multi-objective compromise methodology to determine the socio-optimal and sustainable policies for hydro-environmental management of groundwater resources, which simultaneously considers the conflicts and negotiation of involved stakeholders, uncertainties in decision makers' preferences, existing uncertainties in the groundwater parameters and groundwater quality and quantity issues. The fuzzy multi-objective simulation-optimization model is developed based on qualitative and quantitative groundwater simulation model (MODFLOW and MT3D), multi-objective optimization model (NSGA-II), Monte Carlo analysis and Fuzzy Transformation Method (FTM). Best compromise solutions (best management policies) on trade-off curves are determined using four different Fuzzy Social Choice (FSC) methods. Finally, a unanimity fallback bargaining method is utilized to suggest the most preferred FSC method. Kavar-Maharloo aquifer system in Fars, Iran, as a typical multi-stakeholder multi-objective real-world problem is considered to verify the proposed methodology. Results showed an effective performance of the framework for determining the most sustainable allocation policy in groundwater resource management.

VERY LOW MASS STELLAR AND SUBSTELLAR COMPANIONS TO SOLAR-LIKE STARS FROM MARVELS. IV. A CANDIDATE BROWN DWARF OR LOW-MASS STELLAR COMPANION TO HIP 67526

Energy Technology Data Exchange (ETDEWEB)

Jiang Peng; Ge Jian; De Lee, Nathan; Fleming, Scott W.; Lee, Brian L.; Ma Bo; Wang, Ji [Astronomy Department, University of Florida, 211 Bryant Space Science Center, P.O. Box 112055, Gainesville, FL 32611 (United States); Cargile, Phillip; Hebb, Leslie; Stassun, Keivan G. [Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37235 (United States); Crepp, Justin R. [Department of Physics, University of Notre Dame, 225 Nieuwland Science Hall, Notre Dame, IN 46556 (United States); Porto de Mello, Gustavo F.; Ferreira, Leticia D. [Observatorio do Valongo, Universidade Federal do Rio de Janeiro, Ladeira do Pedro Antonio, 43, CEP: 20080-090, Rio de Janeiro, RJ (Brazil); Esposito, Massimiliano; Femenia, Bruno; Gonzalez Hernandez, Jonay I. [Instituto de Astrofisica de Canarias, C/Via Lactea S/N, E-38200 La Laguna (Spain); Gaudi, B. Scott [Department of Astronomy, The Ohio State University, 140 West 18th Avenue, Columbus, OH 43210 (United States); Ghezzi, Luan [Laboratorio Interinstitucional de e-Astronomia (LIneA), Rio de Janeiro, RJ 20921-400 (Brazil); Wisniewski, John P. [Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, 440 West Brooks Street, Norman, OK 73019 (United States); Agol, Eric, E-mail: jpaty@mail.ustc.edu.cn [Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195-1580 (United States); and others

2013-09-15

We report the discovery of a candidate brown dwarf (BD) or a very low mass stellar companion (MARVELS-5b) to the star HIP 67526 from the Multi-object Apache point observatory Radial Velocity Exoplanet Large-area Survey (MARVELS). The radial velocity curve for this object contains 31 epochs spread over 2.5 yr. Our Keplerian fit, using a Markov Chain Monte Carlo approach, reveals that the companion has an orbital period of 90.2695{sup +0.0188}{sub -0.0187} days, an eccentricity of 0.4375 {+-} 0.0040, and a semi-amplitude of 2948.14{sup +16.65}{sub -16.55} m s{sup -1}. Using additional high-resolution spectroscopy, we find the host star has an effective temperature T{sub eff} = 6004 {+-} 34 K, a surface gravity log g (cgs) =4.55 {+-} 0.17, and a metallicity [Fe/H] =+0.04 {+-} 0.06. The stellar mass and radius determined through the empirical relationship of Torres et al. yields 1.10 {+-} 0.09 M{sub Sun} and 0.92 {+-} 0.19 R{sub Sun }. The minimum mass of MARVELS-5b is 65.0 {+-} 2.9M{sub Jup}, indicating that it is likely to be either a BD or a very low mass star, thus occupying a relatively sparsely populated region of the mass function of companions to solar-type stars. The distance to this system is 101 {+-} 10 pc from the astrometric measurements of Hipparcos. No stellar tertiary is detected in the high-contrast images taken by either FastCam lucky imaging or Keck adaptive optics imaging, ruling out any star with mass greater than 0.2 M{sub Sun} at a separation larger than 40 AU.

Multi area and multistage expansion-planning of electricity supply with sustainable energy development criteria: a multi objective model

Energy Technology Data Exchange (ETDEWEB)

Unsihuay-Vila, Clodomiro; Marangon-Lima, J.W.; Souza, A.C Zambroni de [Universidade Federal de Itajuba (UNIFEI), MG (Brazil)], emails: clodomirounsihuayvila @gmail.com, marangon@unifei.edu.br, zambroni@unifei.edu.br; Perez-Arriaga, I.J. [Universidad Pontificia Comillas, Madrid (Spain)], email: ipa@mit.edu

2010-07-01

A novel multi objective, multi area and multistage model to long-term expansion-planning of integrated generation and transmission corridors incorporating sustainable energy developing is presented in this paper. The proposed MESEDES model is a multi-regional multi-objective and 'bottom-up' energy model which considers the electricity generation/transmission value-chain, i.e., power generation alternatives including renewable, nuclear and traditional thermal generation along with transmission corridors. The model decides the optimal location and timing of the electricity generation/transmission abroad the multistage planning horizon. The MESEDES model considers three objectives belonging to sustainable energy development criteria such as: a) the minimization of investments and operation costs of : power generation, transmission corridors, energy efficiency (demand side management (DSM) programs) considering CO2 capture technologies; b) minimization of Life Cycle Greenhouse Gas Emissions (LC GHG); c) maximization of the diversification of electricity generation mix. The proposed model consider aspects of the carbon abatement policy under the CDM - Clean Development Mechanism or European Union Greenhouse Gas Emission Trading Scheme. A case study is used to illustrate the proposed framework. (author)

Improved multi-objective clustering algorithm using particle swarm optimization.

Directory of Open Access Journals (Sweden)

Congcong Gong

Full Text Available Multi-objective clustering has received widespread attention recently, as it can obtain more accurate and reasonable solution. In this paper, an improved multi-objective clustering framework using particle swarm optimization (IMCPSO is proposed. Firstly, a novel particle representation for clustering problem is designed to help PSO search clustering solutions in continuous space. Secondly, the distribution of Pareto set is analyzed. The analysis results are applied to the leader selection strategy, and make algorithm avoid trapping in local optimum. Moreover, a clustering solution-improved method is proposed, which can increase the efficiency in searching clustering solution greatly. In the experiments, 28 datasets are used and nine state-of-the-art clustering algorithms are compared, the proposed method is superior to other approaches in the evaluation index ARI.

Multi-objective design of PV-wind-diesel-hydrogen-battery systems

Energy Technology Data Exchange (ETDEWEB)

Dufo-Lopez, Rodolfo; Bernal-Agustin, Jose L. [Department of Electrical Engineering, University of Zaragoza, Calle Maria de Luna 3, 50018-Zaragoza (Spain)

2008-12-15

This paper presents, for the first time, a triple multi-objective design of isolated hybrid systems minimizing, simultaneously, the total cost throughout the useful life of the installation, pollutant emissions (CO{sub 2}) and unmet load. For this task, a multi-objective evolutionary algorithm (MOEA) and a genetic algorithm (GA) have been used in order to find the best combination of components of the hybrid system and control strategies. As an example of application, a complex PV-wind-diesel-hydrogen-battery system has been designed, obtaining a set of possible solutions (Pareto Set). The results achieved demonstrate the practical utility of the developed design method. (author)

IN-SYNC I: Homogeneous stellar parameters from high-resolution apogee spectra for thousands of pre-main sequence stars

International Nuclear Information System (INIS)

Cottaar, Michiel; Meyer, Michael R.; Covey, Kevin R.; Nidever, David L.; Stassun, Keivan G.; Foster, Jonathan B.; Tan, Jonathan C.; Da Rio, Nicola; Chojnowski, S. Drew; Skrutskie, Michael; Majewski, Steven R.; Wilson, John C.; Zasowski, Gail; Flaherty, Kevin M.; Frinchaboy, Peter M.

2014-01-01

Over two years, 8859 high-resolution H-band spectra of 3493 young (1-10 Myr) stars were gathered by the multi-object spectrograph of the APOGEE project as part of the IN-SYNC ancillary program of the SDSS-III survey. Here we present the forward modeling approach used to derive effective temperatures, surface gravities, radial velocities, rotational velocities, and H-band veiling from these near-infrared spectra. We discuss in detail the statistical and systematic uncertainties in these stellar parameters. In addition, we present accurate extinctions by measuring the E(J – H) of these young stars with respect to the single-star photometric locus in the Pleiades. Finally, we identify an intrinsic stellar radius spread of about 25% for late-type stars in IC 348 using three (nearly) independent measures of stellar radius, namely, the extinction-corrected J-band magnitude, the surface gravity, and the Rsin i from the rotational velocities and literature rotation periods. We exclude that this spread is caused by uncertainties in the stellar parameters by showing that the three estimators of stellar radius are correlated, so that brighter stars tend to have lower surface gravities and larger Rsin i than fainter stars at the same effective temperature. Tables providing the spectral and photometric parameters for the Pleiades and IC 348 have been provided online.

Sensitivity Analysis of Multi-objective Optimization for Solid Waste Management: A Case Study of Dar es Salaam, Tanzania

Directory of Open Access Journals (Sweden)

Halidi Lyeme

2017-11-01

Full Text Available In this study, a sensitivity analysis of a multi-objective optimization model for solid waste management (SWM for Dar es Salaam city in Tanzania is considered. Our objectives were to identify the most sensitive parameters and effect of other input data to the model output. Five scenarios were considered by varying their associated parameter values. The results showed that the decrease of total cost for the SWM system in all scenarios was observed compared to the baseline solution when the single landfill was considered. Furthermore, the analysis shows that the variable cost parameter for the processing facilities is very sensitivity in such a way that if you increase the variable cost then, there is a rapid increase of total cost for the SWM system and the vice versa is true. The relevant suggestions to the decision makers were also discussed.

The galaxy population of Abell 1367: the stellar mass-metallicity relation

Science.gov (United States)

Mouhcine, M.; Kriwattanawong, W.; James, P. A.

2011-04-01

Using wide baseline broad-band photometry, we analyse the stellar population properties of a sample of 72 galaxies, spanning a wide range of stellar masses and morphological types, in the nearby spiral-rich and dynamically young galaxy cluster Abell 1367. The sample galaxies are distributed from the cluster centre out to approximately half the cluster Abell radius. The optical/near-infrared colours are compared with simple stellar population synthesis models from which the luminosity-weighted stellar population ages and metallicities are determined. The locus of the colours of elliptical galaxies traces a sequence of varying metallicity at a narrow range of luminosity-weighted stellar ages. Lenticular galaxies in the red sequence, however, exhibit a substantial spread of luminosity-weighted stellar metallicities and ages. For red-sequence lenticular galaxies and blue cloud galaxies, low-mass galaxies tend to be on average dominated by stellar populations of younger luminosity-weighted ages. Sample galaxies exhibit a strong correlation between integrated stellar mass and luminosity-weighted stellar metallicity. Galaxies with signs of morphological disturbance and ongoing star formation activity, tend to be underabundant with respect to passive galaxies in the red sequence of comparable stellar masses. We argue that this could be due to tidally driven gas flows towards the star-forming regions, carrying less enriched gas and diluting the pre-existing gas to produce younger stellar populations with lower metallicities than would be obtained prior to the interaction. Finally, we find no statistically significant evidence for changes in the luminosity-weighted ages and metallicities for either red-sequence or blue-cloud galaxies, at fixed stellar mass, with location within the cluster. We dedicate this work to the memory of our friend and colleague C. Moss who died suddenly recently.

Multi-Model Estimation Based Moving Object Detection for Aerial Video

Directory of Open Access Journals (Sweden)

Yanning Zhang

2015-04-01

Full Text Available With the wide development of UAV (Unmanned Aerial Vehicle technology, moving target detection for aerial video has become a popular research topic in the computer field. Most of the existing methods are under the registration-detection framework and can only deal with simple background scenes. They tend to go wrong in the complex multi background scenarios, such as viaducts, buildings and trees. In this paper, we break through the single background constraint and perceive the complex scene accurately by automatic estimation of multiple background models. First, we segment the scene into several color blocks and estimate the dense optical flow. Then, we calculate an affine transformation model for each block with large area and merge the consistent models. Finally, we calculate subordinate degree to multi-background models pixel to pixel for all small area blocks. Moving objects are segmented by means of energy optimization method solved via Graph Cuts. The extensive experimental results on public aerial videos show that, due to multi background models estimation, analyzing each pixel’s subordinate relationship to multi models by energy minimization, our method can effectively remove buildings, trees and other false alarms and detect moving objects correctly.

Multi-objective genetic optimization of linear construction projects

Directory of Open Access Journals (Sweden)

Fatma A. Agrama

2012-08-01

Full Text Available In the real world, the majority cases of optimization problems, met by engineers, are composed of several conflicting objectives. This paper presents an approach for a multi-objective optimization model for scheduling linear construction projects. Linear construction projects have many identical units wherein activities repeat from one unit to another. Highway, pipeline, and tunnels are good examples that exhibit repetitive characteristics. These projects represent a large portion of the construction industry. The present model enables construction planners to generate optimal/near-optimal construction plans that minimize project duration, total work interruptions, and total number of crews. Each of these plans identifies, from a set of feasible alternatives, optimal crew synchronization for each activity and activity interruptions at each unit. This model satisfies the following aspects: (1 it is based on the line of balance technique; (2 it considers non-serial typical activities networks with finish–start relationship and both lag or overlap time between activities is allowed; (3 it utilizes a multi-objective genetic algorithms approach; (4 it is developed as a spreadsheet template that is easy to use. Details of the model with visual charts are presented. An application example is analyzed to illustrate the use of the model and demonstrate its capabilities in optimizing the scheduling of linear construction projects.

A multi-objective approach to solid waste management

International Nuclear Information System (INIS)

Galante, Giacomo; Aiello, Giuseppe; Enea, Mario; Panascia, Enrico

2010-01-01

The issue addressed in this paper consists in the localization and dimensioning of transfer stations, which constitute a necessary intermediate level in the logistic chain of the solid waste stream, from municipalities to the incinerator. Contextually, the determination of the number and type of vehicles involved is carried out in an integrated optimization approach. The model considers both initial investment and operative costs related to transportation and transfer stations. Two conflicting objectives are evaluated, the minimization of total cost and the minimization of environmental impact, measured by pollution. The design of the integrated waste management system is hence approached in a multi-objective optimization framework. To determine the best means of compromise, goal programming, weighted sum and fuzzy multi-objective techniques have been employed. The proposed analysis highlights how different attitudes of the decision maker towards the logic and structure of the problem result in the employment of different methodologies and the obtaining of different results. The novel aspect of the paper lies in the proposal of an effective decision support system for operative waste management, rather than a further contribution to the transportation problem. The model was applied to the waste management of optimal territorial ambit (OTA) of Palermo (Italy).

A multi-objective approach to solid waste management.

Science.gov (United States)

Galante, Giacomo; Aiello, Giuseppe; Enea, Mario; Panascia, Enrico

2010-01-01

The issue addressed in this paper consists in the localization and dimensioning of transfer stations, which constitute a necessary intermediate level in the logistic chain of the solid waste stream, from municipalities to the incinerator. Contextually, the determination of the number and type of vehicles involved is carried out in an integrated optimization approach. The model considers both initial investment and operative costs related to transportation and transfer stations. Two conflicting objectives are evaluated, the minimization of total cost and the minimization of environmental impact, measured by pollution. The design of the integrated waste management system is hence approached in a multi-objective optimization framework. To determine the best means of compromise, goal programming, weighted sum and fuzzy multi-objective techniques have been employed. The proposed analysis highlights how different attitudes of the decision maker towards the logic and structure of the problem result in the employment of different methodologies and the obtaining of different results. The novel aspect of the paper lies in the proposal of an effective decision support system for operative waste management, rather than a further contribution to the transportation problem. The model was applied to the waste management of optimal territorial ambit (OTA) of Palermo (Italy). 2010 Elsevier Ltd. All rights reserved.

Efficient exact optimization of multi-objective redundancy allocation problems in series-parallel systems

International Nuclear Information System (INIS)

Cao, Dingzhou; Murat, Alper; Chinnam, Ratna Babu

2013-01-01

This paper proposes a decomposition-based approach to exactly solve the multi-objective Redundancy Allocation Problem for series-parallel systems. Redundancy allocation problem is a form of reliability optimization and has been the subject of many prior studies. The majority of these earlier studies treat redundancy allocation problem as a single objective problem maximizing the system reliability or minimizing the cost given certain constraints. The few studies that treated redundancy allocation problem as a multi-objective optimization problem relied on meta-heuristic solution approaches. However, meta-heuristic approaches have significant limitations: they do not guarantee that Pareto points are optimal and, more importantly, they may not identify all the Pareto-optimal points. In this paper, we treat redundancy allocation problem as a multi-objective problem, as is typical in practice. We decompose the original problem into several multi-objective sub-problems, efficiently and exactly solve sub-problems, and then systematically combine the solutions. The decomposition-based approach can efficiently generate all the Pareto-optimal solutions for redundancy allocation problems. Experimental results demonstrate the effectiveness and efficiency of the proposed method over meta-heuristic methods on a numerical example taken from the literature.

Multi-Object Spectroscopy in the Next Decade: A Conference Summary

NARCIS (Netherlands)

Trager, S. C.; Skillen, I.; Barcells, M.

2016-01-01

I present a highly-biased summary of the conference "Multi-Object Spectroscopy in the Next Decade: Big Questions, Large Surveys, and Wide Fields," held 2-6 March 2015 in Santa Cruz de la Palma, Spain. I focus on four issues in this summary: (1) complexity in objects, physics, and instruments is

Issues with performance measures for dynamic multi-objective optimisation

CSIR Research Space (South Africa)

Helbig, M

2013-06-01

Full Text Available Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE), Mexico, 20-23 June 2013 Issues with Performance Measures for Dynamic Multi-objective Optimisation Mard´e Helbig CSIR: Meraka Institute Brummeria, South Africa...

A Multi-Objective Learning to re-Rank Approach to Optimize Online Marketplaces for Multiple Stakeholders

OpenAIRE

Nguyen, Phong; Dines, John; Krasnodebski, Jan

2017-01-01

Multi-objective recommender systems address the difficult task of recommending items that are relevant to multiple, possibly conflicting, criteria. However these systems are most often designed to address the objective of one single stakeholder, typically, in online commerce, the consumers whose input and purchasing decisions ultimately determine the success of the recommendation systems. In this work, we address the multi-objective, multi-stakeholder, recommendation problem involving one or ...

The Worst-Case Weighted Multi-Objective Game with an Application to Supply Chain Competitions.

Science.gov (United States)

Qu, Shaojian; Ji, Ying

2016-01-01

In this paper, we propose a worst-case weighted approach to the multi-objective n-person non-zero sum game model where each player has more than one competing objective. Our "worst-case weighted multi-objective game" model supposes that each player has a set of weights to its objectives and wishes to minimize its maximum weighted sum objectives where the maximization is with respect to the set of weights. This new model gives rise to a new Pareto Nash equilibrium concept, which we call "robust-weighted Nash equilibrium". We prove that the robust-weighted Nash equilibria are guaranteed to exist even when the weight sets are unbounded. For the worst-case weighted multi-objective game with the weight sets of players all given as polytope, we show that a robust-weighted Nash equilibrium can be obtained by solving a mathematical program with equilibrium constraints (MPEC). For an application, we illustrate the usefulness of the worst-case weighted multi-objective game to a supply chain risk management problem under demand uncertainty. By the comparison with the existed weighted approach, we show that our method is more robust and can be more efficiently used for the real-world applications.

Multi-objective demand side scheduling considering the operational safety of appliances

International Nuclear Information System (INIS)

Du, Y.F.; Jiang, L.; Li, Y.Z.; Counsell, J.; Smith, J.S.

2016-01-01

Highlights: • Operational safety of appliances is introduced in multi-objective scheduling. • Relationships between operational safety and other objectives are investigated. • Adopted Pareto approach is compared with Weigh and Constraint approaches. • Decision making of Pareto approach is proposed for final appliances’ scheduling. - Abstract: The safe operation of appliances is of great concern to users. The safety risk increases when the appliances are in operation during periods when users are not at home or when they are asleep. In this paper, multi-objective demand side scheduling is investigated with consideration to the appliances’ operational safety together with the electricity cost and the operational delay. The formulation of appliances’ operational safety is proposed based on users’ at-home status and awake status. Then the relationships between the operational safety and the other two objectives are investigated through the approach of finding the Pareto-optimal front. Moreover, this approach is compared with the Weigh and Constraint approaches. As the Pareto-optimal front consists of a set of optimal solutions, this paper proposes a method to make the final scheduling decision based on the relationships among the multiple objectives. Simulation results demonstrate that the operational safety is improved with the sacrifice of the electricity cost and the operational delay, and that the approach of finding the Pareto-optimal front is effective in presenting comprehensive optimal solutions of the multi-objective demand side scheduling.

Solving dynamic multi-objective problems with vector evaluated particle swarm optimisation

CSIR Research Space (South Africa)

Greeff, M

2008-06-01

Full Text Available Many optimisation problems are multi-objective and change dynamically. Many methods use a weighted average approach to the multiple objectives. This paper introduces the usage of the vector evaluated particle swarm optimiser (VEPSO) to solve dynamic...

Multi-objective mixture-based iterated density estimation evolutionary algorithms

NARCIS (Netherlands)

Thierens, D.; Bosman, P.A.N.

2001-01-01

We propose an algorithm for multi-objective optimization using a mixture-based iterated density estimation evolutionary algorithm (MIDEA). The MIDEA algorithm is a prob- abilistic model building evolutionary algo- rithm that constructs at each generation a mixture of factorized probability

Approximate ideal multi-objective solution Q(λ) learning for optimal carbon-energy combined-flow in multi-energy power systems

International Nuclear Information System (INIS)

Zhang, Xiaoshun; Yu, Tao; Yang, Bo; Zheng, Limin; Huang, Linni

2015-01-01

Highlights: • A novel optimal carbon-energy combined-flow (OCECF) model is firstly established. • A novel approximate ideal multi-objective solution Q(λ) learning is designed. • The proposed algorithm has a high convergence stability and reliability. • The proposed algorithm can be applied for OCECF in a large-scale power grid. - Abstract: This paper proposes a novel approximate ideal multi-objective solution Q(λ) learning for optimal carbon-energy combined-flow in multi-energy power systems. The carbon emissions, fuel cost, active power loss, voltage deviation and carbon emission loss are chosen as the optimization objectives, which are simultaneously optimized by five different Q-value matrices. The dynamic optimal weight of each objective is calculated online from the entire Q-value matrices such that the greedy action policy can be obtained. Case studies are carried out to evaluate the optimization performance for carbon-energy combined-flow in an IEEE 118-bus system and the regional power grid of southern China.

Sensitivity Synthesis for MIMO Systems: A Multi Objective H^2 Approach

DEFF Research Database (Denmark)

Stoustrup, Jakob; Niemann, Hans Henrik

1996-01-01

A series of multi objective QTR H-infinity designproblems are considered in this paper. The problems are formulatedas a number of coupled QTR H-infinity design problems. TheseQTR H-infinity problems can be formulated as sensitivityproblems, complementary sensitivity problems, or control...... sensitivityproblems for every output (or input) in the system. It turns out thatthese multi objective QTR H-infinity design problems, based ona number of different types of sensitivity problems, can be exactlydecoupled into k\\QTR H-infinity sensitivity problems for stablesystems, where k is the number of outputs (for...... unstable systems,independent stabilization is required). Further, it is shown how to usesimilar techniques to incorporate simultaneous specifications for differentcontrol objectives such as QTR H-infinity, etc., for the sensitivities....

Multi-Objective Optimization of the Hedging Model for reservoir Operation Using Evolutionary Algorithms

Directory of Open Access Journals (Sweden)

sadegh sadeghitabas

2015-12-01

Full Text Available Multi-objective problems rarely ever provide a single optimal solution, rather they yield an optimal set of outputs (Pareto fronts. Solving these problems was previously accomplished by using some simplifier methods such as the weighting coefficient method used for converting a multi-objective problem to a single objective function. However, such robust tools as multi-objective meta-heuristic algorithms have been recently developed for solving these problems. The hedging model is one of the classic problems for reservoir operation that is generally employed for mitigating drought impacts in water resources management. According to this method, although it is possible to supply the total planned demands, only portions of the demands are met to save water by allowing small deficits in the current conditions in order to avoid or reduce severe deficits in future. The approach heavily depends on economic and social considerations. In the present study, the meta-heuristic algorithms of NSGA-II, MOPSO, SPEA-II, and AMALGAM are used toward the multi-objective optimization of the hedging model. For this purpose, the rationing factors involved in Taleghan dam operation are optimized over a 35-year statistical period of inflow. There are two objective functions: a minimizing the modified shortage index, and b maximizing the reliability index (i.e., two opposite objectives. The results show that the above algorithms are applicable to a wide range of optimal solutions. Among the algorithms, AMALGAM is found to produce a better Pareto front for the values of the objective function, indicating its more satisfactory performance.

Ensemble based multi-objective production optimization of smart wells

NARCIS (Netherlands)

Fonseca, R.M.; Leeuwenburgh, O.; Jansen, J.D.

2012-01-01

In a recent study two hierarchical multi-objective methods were suggested to include short-term targets in life-cycle production optimization. However this previous study has two limitations: 1) the adjoint formulation is used to obtain gradient information, requiring simulator source code access

An Extensible Component-Based Multi-Objective Evolutionary Algorithm Framework

DEFF Research Database (Denmark)

Sørensen, Jan Corfixen; Jørgensen, Bo Nørregaard

2017-01-01

The ability to easily modify the problem definition is currently missing in Multi-Objective Evolutionary Algorithms (MOEA). Existing MOEA frameworks do not support dynamic addition and extension of the problem formulation. The existing frameworks require a re-specification of the problem definition...

An Agent-Based Co-Evolutionary Multi-Objective Algorithm for Portfolio Optimization

Directory of Open Access Journals (Sweden)

Rafał Dreżewski

2017-08-01

Full Text Available Algorithms based on the process of natural evolution are widely used to solve multi-objective optimization problems. In this paper we propose the agent-based co-evolutionary algorithm for multi-objective portfolio optimization. The proposed technique is compared experimentally to the genetic algorithm, co-evolutionary algorithm and a more classical approach—the trend-following algorithm. During the experiments historical data from the Warsaw Stock Exchange is used in order to assess the performance of the compared algorithms. Finally, we draw some conclusions from these experiments, showing the strong and weak points of all the techniques.

Bi-objective optimization for multi-modal transportation routing planning problem based on Pareto optimality

Directory of Open Access Journals (Sweden)

Yan Sun

2015-09-01

Full Text Available Purpose: The purpose of study is to solve the multi-modal transportation routing planning problem that aims to select an optimal route to move a consignment of goods from its origin to its destination through the multi-modal transportation network. And the optimization is from two viewpoints including cost and time. Design/methodology/approach: In this study, a bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. Minimizing the total transportation cost and the total transportation time are set as the optimization objectives of the model. In order to balance the benefit between the two objectives, Pareto optimality is utilized to solve the model by gaining its Pareto frontier. The Pareto frontier of the model can provide the multi-modal transportation operator (MTO and customers with better decision support and it is gained by the normalized normal constraint method. Then, an experimental case study is designed to verify the feasibility of the model and Pareto optimality by using the mathematical programming software Lingo. Finally, the sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case. Findings: The calculation results indicate that the proposed model and Pareto optimality have good performance in dealing with the bi-objective optimization. The sensitivity analysis also shows the influence of the variation of the demand and supply on the multi-modal transportation organization clearly. Therefore, this method can be further promoted to the practice. Originality/value: A bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. The Pareto frontier based sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case.

The Worst-Case Weighted Multi-Objective Game with an Application to Supply Chain Competitions.

Directory of Open Access Journals (Sweden)

Shaojian Qu

Full Text Available In this paper, we propose a worst-case weighted approach to the multi-objective n-person non-zero sum game model where each player has more than one competing objective. Our "worst-case weighted multi-objective game" model supposes that each player has a set of weights to its objectives and wishes to minimize its maximum weighted sum objectives where the maximization is with respect to the set of weights. This new model gives rise to a new Pareto Nash equilibrium concept, which we call "robust-weighted Nash equilibrium". We prove that the robust-weighted Nash equilibria are guaranteed to exist even when the weight sets are unbounded. For the worst-case weighted multi-objective game with the weight sets of players all given as polytope, we show that a robust-weighted Nash equilibrium can be obtained by solving a mathematical program with equilibrium constraints (MPEC. For an application, we illustrate the usefulness of the worst-case weighted multi-objective game to a supply chain risk management problem under demand uncertainty. By the comparison with the existed weighted approach, we show that our method is more robust and can be more efficiently used for the real-world applications.

Multi objective optimization of horizontal axis tidal current turbines, using Meta heuristics algorithms

International Nuclear Information System (INIS)

Tahani, Mojtaba; Babayan, Narek; Astaraei, Fatemeh Razi; Moghadam, Ali

2015-01-01

Highlights: • The performance of four different Meta heuristic optimization algorithms was studied. • Power coefficient and produced torque on stationary blade were selected as objective functions. • Chord and twist distributions were selected as decision variables. • All optimization algorithms were combined with blade element momentum theory. • The best Pareto front was obtained by multi objective flower pollination algorithm for HATCTs. - Abstract: The performance of horizontal axis tidal current turbines (HATCT) strongly depends on their geometry. According to this fact, the optimum performance will be achieved by optimized geometry. In this research study, the multi objective optimization of the HATCT is carried out by using four different multi objective optimization algorithms and their performance is evaluated in combination with blade element momentum theory (BEM). The second version of non-dominated sorting genetic algorithm (NSGA-II), multi objective particle swarm optimization algorithm (MOPSO), multi objective cuckoo search algorithm (MOCS) and multi objective flower pollination algorithm (MOFPA) are the selected algorithms. The power coefficient and the produced torque on stationary blade are selected as objective functions and chord and twist distributions along the blade span are selected as decision variables. These algorithms are combined with the blade element momentum (BEM) theory for the purpose of achieving the best Pareto front. The obtained Pareto fronts are compared with each other. Different sets of experiments are carried out by considering different numbers of iterations, population size and tip speed ratios. The Pareto fronts which are achieved by MOFPA and NSGA-II have better quality in comparison to MOCS and MOPSO, but on the other hand a detail comparison between the first fronts of MOFPA and NSGA-II indicated that MOFPA algorithm can obtain the best Pareto front and can maximize the power coefficient up to 4.3% and the

SU-F-R-10: Selecting the Optimal Solution for Multi-Objective Radiomics Model

International Nuclear Information System (INIS)

Zhou, Z; Folkert, M; Wang, J

2016-01-01

Purpose: To develop an evidential reasoning approach for selecting the optimal solution from a Pareto solution set obtained by a multi-objective radiomics model for predicting distant failure in lung SBRT. Methods: In the multi-objective radiomics model, both sensitivity and specificity are considered as the objective functions simultaneously. A Pareto solution set with many feasible solutions will be resulted from the multi-objective optimization. In this work, an optimal solution Selection methodology for Multi-Objective radiomics Learning model using the Evidential Reasoning approach (SMOLER) was proposed to select the optimal solution from the Pareto solution set. The proposed SMOLER method used the evidential reasoning approach to calculate the utility of each solution based on pre-set optimal solution selection rules. The solution with the highest utility was chosen as the optimal solution. In SMOLER, an optimal learning model coupled with clonal selection algorithm was used to optimize model parameters. In this study, PET, CT image features and clinical parameters were utilized for predicting distant failure in lung SBRT. Results: Total 126 solution sets were generated by adjusting predictive model parameters. Each Pareto set contains 100 feasible solutions. The solution selected by SMOLER within each Pareto set was compared to the manually selected optimal solution. Five-cross-validation was used to evaluate the optimal solution selection accuracy of SMOLER. The selection accuracies for five folds were 80.00%, 69.23%, 84.00%, 84.00%, 80.00%, respectively. Conclusion: An optimal solution selection methodology for multi-objective radiomics learning model using the evidential reasoning approach (SMOLER) was proposed. Experimental results show that the optimal solution can be found in approximately 80% cases.

SU-F-R-10: Selecting the Optimal Solution for Multi-Objective Radiomics Model

Energy Technology Data Exchange (ETDEWEB)

Zhou, Z; Folkert, M; Wang, J [UT Southwestern Medical Center, Dallas, TX (United States)

2016-06-15

Purpose: To develop an evidential reasoning approach for selecting the optimal solution from a Pareto solution set obtained by a multi-objective radiomics model for predicting distant failure in lung SBRT. Methods: In the multi-objective radiomics model, both sensitivity and specificity are considered as the objective functions simultaneously. A Pareto solution set with many feasible solutions will be resulted from the multi-objective optimization. In this work, an optimal solution Selection methodology for Multi-Objective radiomics Learning model using the Evidential Reasoning approach (SMOLER) was proposed to select the optimal solution from the Pareto solution set. The proposed SMOLER method used the evidential reasoning approach to calculate the utility of each solution based on pre-set optimal solution selection rules. The solution with the highest utility was chosen as the optimal solution. In SMOLER, an optimal learning model coupled with clonal selection algorithm was used to optimize model parameters. In this study, PET, CT image features and clinical parameters were utilized for predicting distant failure in lung SBRT. Results: Total 126 solution sets were generated by adjusting predictive model parameters. Each Pareto set contains 100 feasible solutions. The solution selected by SMOLER within each Pareto set was compared to the manually selected optimal solution. Five-cross-validation was used to evaluate the optimal solution selection accuracy of SMOLER. The selection accuracies for five folds were 80.00%, 69.23%, 84.00%, 84.00%, 80.00%, respectively. Conclusion: An optimal solution selection methodology for multi-objective radiomics learning model using the evidential reasoning approach (SMOLER) was proposed. Experimental results show that the optimal solution can be found in approximately 80% cases.

FRIENDS OF HOT JUPITERS. II. NO CORRESPONDENCE BETWEEN HOT-JUPITER SPIN-ORBIT MISALIGNMENT AND THE INCIDENCE OF DIRECTLY IMAGED STELLAR COMPANIONS

Energy Technology Data Exchange (ETDEWEB)

Ngo, Henry; Knutson, Heather A.; Hinkley, Sasha; Batygin, Konstantin [Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA (United States); Crepp, Justin R.; Bechter, Eric B. [Department of Physics, University of Notre Dame, Notre Dame, IN (United States); Howard, Andrew W. [Institute for Astronomy, University of Hawaii at Manoa, Honolulu, HI (United States); Johnson, John A. [Harvard-Smithsonian Center for Astrophysics, Cambridge, MA (United States); Morton, Timothy D. [Cahill Center for Astronomy and Astrophysics, California Institute of Technology, Pasadena, CA (United States); Muirhead, Philip S., E-mail: hngo@caltech.edu [Department of Astronomy, Boston University, Boston, MA (United States)

2015-02-20

Multi-star systems are common, yet little is known about a stellar companion's influence on the formation and evolution of planetary systems. For instance, stellar companions may have facilitated the inward migration of hot Jupiters toward to their present day positions. Many observed short-period gas giant planets also have orbits that are misaligned with respect to their star's spin axis, which has also been attributed to the presence of a massive outer companion on a non-coplanar orbit. We present the results of a multi-band direct imaging survey using Keck NIRC2 to measure the fraction of short-period gas giant planets found in multi-star systems. Over three years, we completed a survey of 50 targets ('Friends of Hot Jupiters') with 27 targets showing some signature of multi-body interaction (misaligned or eccentric orbits) and 23 targets in a control sample (well-aligned and circular orbits). We report the masses, projected separations, and confirmed common proper motion for the 19 stellar companions found around 17 stars. Correcting for survey incompleteness, we report companion fractions of 48% ± 9%, 47% ± 12%, and 51% ± 13% in our total, misaligned/eccentric, and control samples, respectively. This total stellar companion fraction is 2.8σ larger than the fraction of field stars with companions approximately 50-2000 AU. We observe no correlation between misaligned/eccentric hot Jupiter systems and the incidence of stellar companions. Combining this result with our previous radial velocity survey, we determine that 72% ± 16% of hot Jupiters are part of multi-planet and/or multi-star systems.

Stellar Physics 2: Stellar Evolution and Stability

CERN Document Server

Bisnovatyi-Kogan, Gennady S

2011-01-01

"Stellar Physics" is a an outstanding book in the growing body of literature on star formation and evolution. Not only does the author, a leading expert in the field, very thoroughly present the current state of knowledge on stellar physics, but he handles with equal care the many problems that this field of research still faces. A bibliography with well over 1000 entries makes this book an unparalleled reference source. "Stellar Evolution and Stability" is the second of two volumes and can be read, as can the first volume "Fundamental Concepts and Stellar Equilibrium," as a largely independent work. It traces in great detail the evolution of protostars towards the main sequence and beyond this to the last stage of stellar evolution, with the corresponding vast range from white dwarfs to supernovae explosions, gamma-ray bursts and black hole formation. The book concludes with special chapters on the dynamical, thermal and pulsing stability of stars. This second edition is carefully updated in the areas of pre...

Bi-objective integrating sustainable order allocation and sustainable supply chain network strategic design with stochastic demand using a novel robust hybrid multi-objective metaheuristic

DEFF Research Database (Denmark)

Govindan, Kannan; Jafarian, Ahmad; Nourbakhsh, Vahid

2015-01-01

simultaneously considering the sustainable OAP in the sustainable SCND as a strategic decision. The proposed supply chain network is composed of five echelons including suppliers classified in different classes, plants, distribution centers that dispatch products via two different ways, direct shipment......, a novel multi-objective hybrid approach called MOHEV with two strategies for its best particle selection procedure (BPSP), minimum distance, and crowding distance is proposed. MOHEV is constructed through hybridization of two multi-objective algorithms, namely the adapted multi-objective electromagnetism...

Effectiveness of meta-models for multi-objective optimization of centrifugal impeller

Energy Technology Data Exchange (ETDEWEB)

Bellary, Sayed Ahmed Imran; Samad, Abdus [Indian Institute of Technology Madras, Chennai (India); Husain, Afzal [Sultan Qaboos University, Al-Khoudh (Oman)

2014-12-15

The major issue of multiple fidelity based analysis and optimization of fluid machinery system depends upon the proper construction of low fidelity model or meta-model. A low fidelity model uses responses obtained from a high fidelity model, and the meta-model is then used to produce population of solutions required for evolutionary algorithm for multi-objective optimization. The Pareto-optimal front which shows functional relationships among the multiple objectives can produce erroneous results if the low fidelity models are not well-constructed. In the present research, response surface approximation and Kriging meta-models were evaluated for their effectiveness for the application in the turbomachinery design and optimization. A high fidelity model such as CFD technique along with the metamodels was used to obtain Pareto-optimal front via multi-objective genetic algorithm. A centrifugal impeller has been considered as case study to find relationship between two conflicting objectives, viz., hydraulic efficiency and head. Design variables from the impeller geometry have been chosen and the responses of the objective functions were evaluated through CFD analysis. The fidelity of each metamodel has been discussed in context of their predictions in entire design space in general and near optimal region in particular. Exploitation of the multiple meta-models enhances the quality of multi-objective optimization and provides the information pertaining to fidelity of optimization model. It was observed that the Kriging meta-model was better suited for this type of problem as it involved less approximation error in the Pareto-optimal front.

Effectiveness of meta-models for multi-objective optimization of centrifugal impeller

International Nuclear Information System (INIS)

Bellary, Sayed Ahmed Imran; Samad, Abdus; Husain, Afzal

2014-01-01

The major issue of multiple fidelity based analysis and optimization of fluid machinery system depends upon the proper construction of low fidelity model or meta-model. A low fidelity model uses responses obtained from a high fidelity model, and the meta-model is then used to produce population of solutions required for evolutionary algorithm for multi-objective optimization. The Pareto-optimal front which shows functional relationships among the multiple objectives can produce erroneous results if the low fidelity models are not well-constructed. In the present research, response surface approximation and Kriging meta-models were evaluated for their effectiveness for the application in the turbomachinery design and optimization. A high fidelity model such as CFD technique along with the metamodels was used to obtain Pareto-optimal front via multi-objective genetic algorithm. A centrifugal impeller has been considered as case study to find relationship between two conflicting objectives, viz., hydraulic efficiency and head. Design variables from the impeller geometry have been chosen and the responses of the objective functions were evaluated through CFD analysis. The fidelity of each metamodel has been discussed in context of their predictions in entire design space in general and near optimal region in particular. Exploitation of the multiple meta-models enhances the quality of multi-objective optimization and provides the information pertaining to fidelity of optimization model. It was observed that the Kriging meta-model was better suited for this type of problem as it involved less approximation error in the Pareto-optimal front.

Multi-Objective Optimization for Energy Performance Improvement of Residential Buildings: A Comparative Study

Directory of Open Access Journals (Sweden)

Kangji Li

2017-02-01

Full Text Available Numerous conflicting criteria exist in building design optimization, such as energy consumption, greenhouse gas emission and indoor thermal performance. Different simulation-based optimization strategies and various optimization algorithms have been developed. A few of them are analyzed and compared in solving building design problems. This paper presents an efficient optimization framework to facilitate optimization designs with the aid of commercial simulation software and MATLAB. The performances of three optimization strategies, including the proposed approach, GenOpt method and artificial neural network (ANN method, are investigated using a case study of a simple building energy model. Results show that the proposed optimization framework has competitive performances compared with the GenOpt method. Further, in another practical case, four popular multi-objective algorithms, e.g., the non-dominated sorting genetic algorithm (NSGA-II, multi-objective particle swarm optimization (MOPSO, the multi-objective genetic algorithm (MOGA and multi-objective differential evolution (MODE, are realized using the propose optimization framework and compared with three criteria. Results indicate that MODE achieves close-to-optimal solutions with the best diversity and execution time. An uncompetitive result is achieved by the MOPSO in this case study.

Multi-Objective Constraint Satisfaction for Mobile Robot Area Defense

Science.gov (United States)

2010-03-01

David A. Van Veldhuizen . Evo- lutionary Algorithms for Solving Multi-Objective Problems. Springer, New York, NY, 2nd edition, 2007. [9] Dean, Thomas...J.I. van Hemert, E. Marchiori, and A. G. Steenbeek. “Solving Binary Constraint Satisfaction Problems using Evolutionary Algorithms with an Adaptive

Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method

Science.gov (United States)

Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan

2017-05-01

In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability.

Adaptive multi-objective Optimization scheme for cognitive radio resource management

KAUST Repository

Alqerm, Ismail; Shihada, Basem

2014-01-01

configuration by exploiting optimization and machine learning techniques. In this paper, we propose an Adaptive Multi-objective Optimization Scheme (AMOS) for cognitive radio resource management to improve spectrum operation and network performance

Multi-objective game-theory models for conflict analysis in reservoir watershed management.

Science.gov (United States)

Lee, Chih-Sheng

2012-05-01

This study focuses on the development of a multi-objective game-theory model (MOGM) for balancing economic and environmental concerns in reservoir watershed management and for assistance in decision. Game theory is used as an alternative tool for analyzing strategic interaction between economic development (land use and development) and environmental protection (water-quality protection and eutrophication control). Geographic information system is used to concisely illustrate and calculate the areas of various land use types. The MOGM methodology is illustrated in a case study of multi-objective watershed management in the Tseng-Wen reservoir, Taiwan. The innovation and advantages of MOGM can be seen in the results, which balance economic and environmental concerns in watershed management and which can be interpreted easily by decision makers. For comparison, the decision-making process using conventional multi-objective method to produce many alternatives was found to be more difficult. Copyright © 2012 Elsevier Ltd. All rights reserved.

Objective-guided image annotation.

Science.gov (United States)

Mao, Qi; Tsang, Ivor Wai-Hung; Gao, Shenghua

2013-04-01

Automatic image annotation, which is usually formulated as a multi-label classification problem, is one of the major tools used to enhance the semantic understanding of web images. Many multimedia applications (e.g., tag-based image retrieval) can greatly benefit from image annotation. However, the insufficient performance of image annotation methods prevents these applications from being practical. On the other hand, specific measures are usually designed to evaluate how well one annotation method performs for a specific objective or application, but most image annotation methods do not consider optimization of these measures, so that they are inevitably trapped into suboptimal performance of these objective-specific measures. To address this issue, we first summarize a variety of objective-guided performance measures under a unified representation. Our analysis reveals that macro-averaging measures are very sensitive to infrequent keywords, and hamming measure is easily affected by skewed distributions. We then propose a unified multi-label learning framework, which directly optimizes a variety of objective-specific measures of multi-label learning tasks. Specifically, we first present a multilayer hierarchical structure of learning hypotheses for multi-label problems based on which a variety of loss functions with respect to objective-guided measures are defined. And then, we formulate these loss functions as relaxed surrogate functions and optimize them by structural SVMs. According to the analysis of various measures and the high time complexity of optimizing micro-averaging measures, in this paper, we focus on example-based measures that are tailor-made for image annotation tasks but are seldom explored in the literature. Experiments show consistency with the formal analysis on two widely used multi-label datasets, and demonstrate the superior performance of our proposed method over state-of-the-art baseline methods in terms of example-based measures on four

Compact Starburst Galaxies with Fast Outflows: Spatially Resolved Stellar Mass Profiles

Science.gov (United States)

Gottlieb, Sophia; Diamond-Stanic, Aleksandar; Lipscomb, Charles; Ohene, Senyo; Rines, Josh; Moustakas, John; Sell, Paul; Tremonti, Christy; Coil, Alison; Rudnick, Gregory; Hickox, Ryan C.; Geach, James; Kepley, Amanda

2018-01-01

Powerful galactic winds driven by stellar feedback and black hole accretion are thought to play an important role in regulating star formation in galaxies. In particular, strong stellar feedback from supernovae, stellar winds, radiation pressure, and cosmic rays is required by simulations of star-forming galaxies to prevent the vast majority of baryons from cooling and collapsing to form stars. However, it remains unclear whether these stellar processes play a significant role in expelling gas and shutting down star formation in massive progenitors of quiescent galaxies. What are the limits of stellar feedback? We present multi-band photometry with HST/WFC3 (F475W, F814W, F160W) for a dozen compact starburst galaxies at z~0.6 with half-light radii that suggest incredibly large central escape velocities. These massive galaxies are driving fast (>1000 km/s) outflows that have been previously attributed to stellar feedback associated with the compact (r~100 pc) starburst. But how compact is the stellar mass? In the context of the stellar feedback hypothesis, it is unclear whether these fast outflows are being driven at velocities comparable to the escape velocity of an incredibly dense stellar system (as predicted by some models of radiation-pressure winds) or at velocities that exceed the central escape velocity by large factor. Our spatially resolved measurements with HST show that the stellar mass is more extended than the light, and this requires that the physical mechanism responsible for driving the winds must be able to launch gas at velocities that are factors of 5-10 beyond the central escape velocity.

Provisional-Ideal-Point-Based Multi-objective Optimization Method for Drone Delivery Problem

Science.gov (United States)

Omagari, Hiroki; Higashino, Shin-Ichiro

2018-04-01

In this paper, we proposed a new evolutionary multi-objective optimization method for solving drone delivery problems (DDP). It can be formulated as a constrained multi-objective optimization problem. In our previous research, we proposed the "aspiration-point-based method" to solve multi-objective optimization problems. However, this method needs to calculate the optimal values of each objective function value in advance. Moreover, it does not consider the constraint conditions except for the objective functions. Therefore, it cannot apply to DDP which has many constraint conditions. To solve these issues, we proposed "provisional-ideal-point-based method." The proposed method defines a "penalty value" to search for feasible solutions. It also defines a new reference solution named "provisional-ideal point" to search for the preferred solution for a decision maker. In this way, we can eliminate the preliminary calculations and its limited application scope. The results of the benchmark test problems show that the proposed method can generate the preferred solution efficiently. The usefulness of the proposed method is also demonstrated by applying it to DDP. As a result, the delivery path when combining one drone and one truck drastically reduces the traveling distance and the delivery time compared with the case of using only one truck.

Robust multi-objective calibration strategies – possibilities for improving flood forecasting

Directory of Open Access Journals (Sweden)

G. H. Schmitz

2012-10-01

Full Text Available Process-oriented rainfall-runoff models are designed to approximate the complex hydrologic processes within a specific catchment and in particular to simulate the discharge at the catchment outlet. Most of these models exhibit a high degree of complexity and require the determination of various parameters by calibration. Recently, automatic calibration methods became popular in order to identify parameter vectors with high corresponding model performance. The model performance is often assessed by a purpose-oriented objective function. Practical experience suggests that in many situations one single objective function cannot adequately describe the model's ability to represent any aspect of the catchment's behaviour. This is regardless of whether the objective is aggregated of several criteria that measure different (possibly opposite aspects of the system behaviour. One strategy to circumvent this problem is to define multiple objective functions and to apply a multi-objective optimisation algorithm to identify the set of Pareto optimal or non-dominated solutions. Nonetheless, there is a major disadvantage of automatic calibration procedures that understand the problem of model calibration just as the solution of an optimisation problem: due to the complex-shaped response surface, the estimated solution of the optimisation problem can result in different near-optimum parameter vectors that can lead to a very different performance on the validation data. Bárdossy and Singh (2008 studied this problem for single-objective calibration problems using the example of hydrological models and proposed a geometrical sampling approach called Robust Parameter Estimation (ROPE. This approach applies the concept of data depth in order to overcome the shortcomings of automatic calibration procedures and find a set of robust parameter vectors. Recent studies confirmed the effectivity of this method. However, all ROPE approaches published so far just identify

MultiController: the PLC-SCADA object for advanced regulation

CERN Document Server

Ortola, J

2007-01-01

Nowadays, industrial solutions with PLCs (Programmable Logic Controllers) have basic control loop features. The SCADA (Supervisory Control And Data Acquisition) system is a key point of the process control system due to an efficient HMI (Human Machine Interfaces) that provides an open method of tuning and leading possibilities. As a consequence, advanced control algorithms have to be developed and implemented for those PLC-SCADA solutions in order to provide perspectives in solving complex and critical regulation problems. The MultiController is an object integrated for a large scale project at CERN (the European Organization for Nuclear Research) named LHC-GCS (Large Hadron Collider - Gas Control System). It is developed for a Framework called CERN-UNICOS based on PLC-SCADA facilities. The MultiController object offers various advanced control loop strategies. It gives to the user advanced control algorithms like PID, Smith Predictor, PFC, GPC and RST. It is implemented as a monolithic entity (in PLC and SCA...

A performance comparison of multi-objective optimization algorithms for solving nearly-zero-energy-building design problems

NARCIS (Netherlands)

Hamdy, M.; Nguyen, A.T. (Anh Tuan); Hensen, J.L.M.

2016-01-01

Integrated building design is inherently a multi-objective optimization problem where two or more conflicting objectives must be minimized and/or maximized concurrently. Many multi-objective optimization algorithms have been developed; however few of them are tested in solving building design

Flexible Multi-Objective Transmission Expansion Planning with Adjustable Risk Aversion

Directory of Open Access Journals (Sweden)

Jing Qiu

2017-07-01

Full Text Available This paper presents a multi-objective transmission expansion planning (TEP framework. Rather than using the conventional deterministic reliability criterion, a risk component based on the probabilistic reliability criterion is incorporated into the TEP objectives. This risk component can capture the stochastic nature of power systems, such as load and wind power output variations, component availability, and incentive-based demand response (IBDR costs. Specifically, the formulation of risk value after risk aversion is explicitly given, and it aims to provide network planners with the flexibility to conduct risk analysis. Thus, a final expansion plan can be selected according to individual risk preferences. Moreover, the economic value of IBDR is modeled and integrated into the cost objective. In addition, a relatively new multi-objective evolutionary algorithm called the MOEA/D is introduced and employed to find Pareto optimal solutions, and tradeoffs between overall cost and risk are provided. The proposed approach is numerically verified on the Garver’s six-bus, IEEE 24-bus RTS and Polish 2383-bus systems. Case study results demonstrate that the proposed approach can effectively reduce cost and hedge risk in relation to increasing wind power integration.

Multi-objective optimization of a vertical ground source heat pump using evolutionary algorithm

International Nuclear Information System (INIS)

Sayyaadi, Hoseyn; Amlashi, Emad Hadaddi; Amidpour, Majid

2009-01-01

Thermodynamic and thermoeconomic optimization of a vertical ground source heat pump system has been studied. A model based on the energy and exergy analysis is presented here. An economic model of the system is developed according to the Total Revenue Requirement (TRR) method. The objective functions based on the thermodynamic and thermoeconomic analysis are developed. The proposed vertical ground source heat pump system including eight decision variables is considered for optimization. An artificial intelligence technique known as evolutionary algorithm (EA) has been utilized as an optimization method. This approach has been applied to minimize either the total levelized cost of the system product or the exergy destruction of the system. Three levels of optimization including thermodynamic single objective, thermoeconomic single objective and multi-objective optimizations are performed. In Multi-objective optimization, both thermodynamic and thermoeconomic objectives are considered, simultaneously. In the case of multi-objective optimization, an example of decision-making process for selection of the final solution from available optimal points on Pareto frontier is presented. The results obtained using the various optimization approaches are compared and discussed. Further, the sensitivity of optimized systems to the interest rate, to the annual number of operating hours and to the electricity cost are studied in detail.

Considering Decision Variable Diversity in Multi-Objective Optimization: Application in Hydrologic Model Calibration

Science.gov (United States)

Sahraei, S.; Asadzadeh, M.

2017-12-01

Any modern multi-objective global optimization algorithm should be able to archive a well-distributed set of solutions. While the solution diversity in the objective space has been explored extensively in the literature, little attention has been given to the solution diversity in the decision space. Selection metrics such as the hypervolume contribution and crowding distance calculated in the objective space would guide the search toward solutions that are well-distributed across the objective space. In this study, the diversity of solutions in the decision-space is used as the main selection criteria beside the dominance check in multi-objective optimization. To this end, currently archived solutions are clustered in the decision space and the ones in less crowded clusters are given more chance to be selected for generating new solution. The proposed approach is first tested on benchmark mathematical test problems. Second, it is applied to a hydrologic model calibration problem with more than three objective functions. Results show that the chance of finding more sparse set of high-quality solutions increases, and therefore the analyst would receive a well-diverse set of options with maximum amount of information. Pareto Archived-Dynamically Dimensioned Search, which is an efficient and parsimonious multi-objective optimization algorithm for model calibration, is utilized in this study.

A Generalized Decision Framework Using Multi-objective Optimization for Water Resources Planning

Science.gov (United States)

Basdekas, L.; Stewart, N.; Triana, E.

2013-12-01

Colorado Springs Utilities (CSU) is currently engaged in an Integrated Water Resource Plan (IWRP) to address the complex planning scenarios, across multiple time scales, currently faced by CSU. The modeling framework developed for the IWRP uses a flexible data-centered Decision Support System (DSS) with a MODSIM-based modeling system to represent the operation of the current CSU raw water system coupled with a state-of-the-art multi-objective optimization algorithm. Three basic components are required for the framework, which can be implemented for planning horizons ranging from seasonal to interdecadal. First, a water resources system model is required that is capable of reasonable system simulation to resolve performance metrics at the appropriate temporal and spatial scales of interest. The system model should be an existing simulation model, or one developed during the planning process with stakeholders, so that 'buy-in' has already been achieved. Second, a hydrologic scenario tool(s) capable of generating a range of plausible inflows for the planning period of interest is required. This may include paleo informed or climate change informed sequences. Third, a multi-objective optimization model that can be wrapped around the system simulation model is required. The new generation of multi-objective optimization models do not require parameterization which greatly reduces problem complexity. Bridging the gap between research and practice will be evident as we use a case study from CSU's planning process to demonstrate this framework with specific competing water management objectives. Careful formulation of objective functions, choice of decision variables, and system constraints will be discussed. Rather than treating results as theoretically Pareto optimal in a planning process, we use the powerful multi-objective optimization models as tools to more efficiently and effectively move out of the inferior decision space. The use of this framework will help CSU

Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking.

Science.gov (United States)

Bae, Seung-Hwan; Yoon, Kuk-Jin

2018-03-01

Online multi-object tracking aims at estimating the tracks of multiple objects instantly with each incoming frame and the information provided up to the moment. It still remains a difficult problem in complex scenes, because of the large ambiguity in associating multiple objects in consecutive frames and the low discriminability between objects appearances. In this paper, we propose a robust online multi-object tracking method that can handle these difficulties effectively. We first define the tracklet confidence using the detectability and continuity of a tracklet, and decompose a multi-object tracking problem into small subproblems based on the tracklet confidence. We then solve the online multi-object tracking problem by associating tracklets and detections in different ways according to their confidence values. Based on this strategy, tracklets sequentially grow with online-provided detections, and fragmented tracklets are linked up with others without any iterative and expensive association steps. For more reliable association between tracklets and detections, we also propose a deep appearance learning method to learn a discriminative appearance model from large training datasets, since the conventional appearance learning methods do not provide rich representation that can distinguish multiple objects with large appearance variations. In addition, we combine online transfer learning for improving appearance discriminability by adapting the pre-trained deep model during online tracking. Experiments with challenging public datasets show distinct performance improvement over other state-of-the-arts batch and online tracking methods, and prove the effect and usefulness of the proposed methods for online multi-object tracking.

Analysing the performance of dynamic multi-objective optimisation algorithms

CSIR Research Space (South Africa)

Helbig, M

2013-06-01

Full Text Available and the goal of the algorithm is to track a set of tradeoff solutions over time. Analysing the performance of a dynamic multi-objective optimisation algorithm (DMOA) is not a trivial task. For each environment (before a change occurs) the DMOA has to find a set...

Multi-objective evolutionary optimisation for product design and manufacturing

CERN Document Server

2011-01-01

Presents state-of-the-art research in the area of multi-objective evolutionary optimisation for integrated product design and manufacturing Provides a comprehensive review of the literature Gives in-depth descriptions of recently developed innovative and novel methodologies, algorithms and systems in the area of modelling, simulation and optimisation

Study on multi-objective flexible job-shop scheduling problem considering energy consumption

Directory of Open Access Journals (Sweden)

Zengqiang Jiang

2014-06-01

Full Text Available Purpose: Build a multi-objective Flexible Job-shop Scheduling Problem(FJSP optimization model, in which the makespan, processing cost, energy consumption and cost-weighted processing quality are considered, then Design a Modified Non-dominated Sorting Genetic Algorithm (NSGA-II based on blood variation for above scheduling model.Design/methodology/approach: A multi-objective optimization theory based on Pareto optimal method is used in carrying out the optimization model. NSGA-II is used to solve the model.Findings: By analyzing the research status and insufficiency of multi-objective FJSP, Find that the difference in scheduling will also have an effect on energy consumption in machining process and environmental emissions. Therefore, job-shop scheduling requires not only guaranteeing the processing quality, time and cost, but also optimizing operation plan of machines and minimizing energy consumption.Originality/value: A multi-objective FJSP optimization model is put forward, in which the makespan, processing cost, energy consumption and cost-weighted processing quality are considered. According to above model, Blood-Variation-based NSGA-II (BVNSGA-II is designed. In which, the chromosome mutation rate is determined after calculating the blood relationship between two cross chromosomes, crossover and mutation strategy of NSGA-II is optimized and the prematurity of population is overcome. Finally, the performance of the proposed model and algorithm is evaluated through a case study, and the results proved the efficiency and feasibility of the proposed model and algorithm.

The Resolved Stellar Populations Early Release Science Program

Science.gov (United States)

Weisz, Daniel; Anderson, J.; Boyer, M.; Cole, A.; Dolphin, A.; Geha, M.; Kalirai, J.; Kallivayalil, N.; McQuinn, K.; Sandstrom, K.; Williams, B.

2017-11-01

We propose to obtain deep multi-band NIRCam and NIRISS imaging of three resolved stellar systems within 1 Mpc (NOI 104). We will use this broad science program to optimize observational setups and to develop data reduction techniques that will be common to JWST studies of resolved stellar populations. We will combine our expertise in HST resolved star studies with these observations to design, test, and release point spread function (PSF) fitting software specific to JWST. PSF photometry is at the heart of resolved stellar populations studies, but is not part of the standard JWST reduction pipeline. Our program will establish JWST-optimized methodologies in six scientific areas: star formation histories, measurement of the sub-Solar mass stellar IMF, extinction maps, evolved stars, proper motions, and globular clusters, all of which will be common pursuits for JWST in the local Universe. Our observations of globular cluster M92, ultra-faint dwarf Draco II, and star-forming dwarf WLM, will be of high archival value for other science such as calibrating stellar evolution models, measuring properties of variable stars, and searching for metal-poor stars. We will release the results of our program, including PSF fitting software, matched HST and JWST catalogs, clear documentation, and step-by-step tutorials (e.g., Jupyter notebooks) for data reduction and science application, to the community prior to the Cycle 2 Call for Proposals. We will host a workshop to help community members plan their Cycle 2 observations of resolved stars. Our program will provide blueprints for the community to efficiently reduce and analyze JWST observations of resolved stellar populations.

A multi-objective robust optimization model for logistics planning in the earthquake response phase

NARCIS (Netherlands)

Najafi, M.; Eshghi, K.; Dullaert, W.E.H.

2013-01-01

Usually, resources are short in supply when earthquakes occur. In such emergency situations, disaster relief organizations must use these scarce resources efficiently to achieve the best possible emergency relief. This paper therefore proposes a multi-objective, multi-mode, multi-commodity, and

The multi-objective decision making methods based on MULTIMOORA and MOOSRA for the laptop selection problem

Science.gov (United States)

Aytaç Adalı, Esra; Tuş Işık, Ayşegül

2017-06-01

A decision making process requires the values of conflicting objectives for alternatives and the selection of the best alternative according to the needs of decision makers. Multi-objective optimization methods may provide solution for this selection. In this paper it is aimed to present the laptop selection problem based on MOORA plus full multiplicative form (MULTIMOORA) and multi-objective optimization on the basis of simple ratio analysis (MOOSRA) which are relatively new multi-objective optimization methods. The novelty of this paper is solving this problem with the MULTIMOORA and MOOSRA methods for the first time.

Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method.

Science.gov (United States)

Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan

2017-05-01

In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability. Copyright © 2017 Elsevier B.V. All rights reserved.

Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters

Directory of Open Access Journals (Sweden)

Fonseca Carlos M

2010-10-01

Full Text Available Abstract Background Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the

Distributed parallel cooperative coevolutionary multi-objective large-scale immune algorithm for deployment of wireless sensor networks

DEFF Research Database (Denmark)

Cao, Bin; Zhao, Jianwei; Yang, Po

2018-01-01

-objective evolutionary algorithms the Cooperative Coevolutionary Generalized Differential Evolution 3, the Cooperative Multi-objective Differential Evolution and the Nondominated Sorting Genetic Algorithm III, the proposed algorithm addresses the deployment optimization problem efficiently and effectively.......Using immune algorithms is generally a time-intensive process especially for problems with a large number of variables. In this paper, we propose a distributed parallel cooperative coevolutionary multi-objective large-scale immune algorithm that is implemented using the message passing interface...... (MPI). The proposed algorithm is composed of three layers: objective, group and individual layers. First, for each objective in the multi-objective problem to be addressed, a subpopulation is used for optimization, and an archive population is used to optimize all the objectives. Second, the large...

All-hexahedral meshing and remeshing for multi-object manufacturing applications

DEFF Research Database (Denmark)

Nielsen, Chris Valentin; Fernandes, J.L.M.; Martins, P.A.F.

2013-01-01

new developments related to the construction of adaptive core meshes and processing of multi-objects that are typical of manufacturing applications.Along with the aforementioned improvements there are other developments that will also be presented due to their effectiveness in increasing.......The presentation is enriched with examples taken from pure geometry and metal forming applications, and a resistance projection welding industrial test case consisting of four different objects is included to show the capabilities of selective remeshing of objects while maintaining contact conditions and local...

On the universal stellar law

Science.gov (United States)

Krot, Alexander

In this work, we consider a statistical theory of gravitating spheroidal bodies to derive and develop the universal stellar law for extrasolar systems. Previously, the statistical theory for a cosmogonic body forming (so-called spheroidal body)has been proposed [1-3]. This theory starts from the conception for forming a spheroidal body inside a gas-dust protoplanetary nebula; it permits us to derive the form of distribution functions, mass density, gravitational potentials and strengths both for immovable and rotating spheroidal bodies as well as to find the distribution function of specific angular momentum[1-3]. If we start from the conception for forming a spheroidal body as a protostar (in particular, proto-Sun) inside a prestellar (presolar) nebula then the derived distribution functions of particle (as well as the mass density of an immovable spheroidal body) characterizes the first stage of evolution: from a prestellar molecular cloud (the presolar nebula) to the forming core of protostar (the proto-Sun) together with its shell as a stellar nebula (the solar nebula). This work derives the equation of state of an ideal stellar substance based on conception of gravitating spheroidal body. Using this equation, we obtain the universal stellar law (USL) for the planetary systems connecting temperature, size and mass of each of stars. This work also considers the Solar corona in the connection with USL. Then it is accounting under calculation of the ratio of temperature of the Solar corona to effective temperature of the Sun’ surfaceand modification of USL. To test justice of the modified USLfor different types of stars, the temperature of stellar corona is estimated. The prediction of parameters of stars is carrying out by means of the modified USL,as well as the Hertzsprung-Russell’s dependence [5-7]is derivedby means of USL directly. This paper also shows that knowledge of some characteristics for multi-planet extrasolar systems refines own parameters of

LASR-Guided Variability Subtraction: The Linear Algorithm for Significance Reduction of Stellar Seismic Activity

Science.gov (United States)

Horvath, Sarah; Myers, Sam; Ahlers, Johnathon; Barnes, Jason W.

2017-10-01

Stellar seismic activity produces variations in brightness that introduce oscillations into transit light curves, which can create challenges for traditional fitting models. These oscillations disrupt baseline stellar flux values and potentially mask transits. We develop a model that removes these oscillations from transit light curves by minimizing the significance of each oscillation in frequency space. By removing stellar variability, we prepare each light curve for traditional fitting techniques. We apply our model to $\\delta$-Scuti KOI-976 and demonstrate that our variability subtraction routine successfully allows for measuring bulk system characteristics using traditional light curve fitting. These results open a new window for characterizing bulk system parameters of planets orbiting seismically active stars.

PRIMUS: THE DEPENDENCE OF AGN ACCRETION ON HOST STELLAR MASS AND COLOR

Energy Technology Data Exchange (ETDEWEB)

Aird, James; Coil, Alison L.; Moustakas, John; Smith, M. Stephen M. [Center for Astrophysics and Space Sciences, Department of Physics, University of California, 9500 Gilman Dr., La Jolla, San Diego, CA 92093 (United States); Blanton, Michael R.; Zhu Guangtun [Center for Cosmology and Particle Physics, Department of Physics, New York University, 4 Washington Place, New York, NY 10003 (United States); Burles, Scott M. [D.E. Shaw and Co., L.P., 20400 Stevens Creek Blvd., Suite 850, Cupertino, CA 95014 (United States); Cool, Richard J. [Department of Astrophysical Sciences, Princeton University, Peyton Hall, Princeton, NJ 08544 (United States); Eisenstein, Daniel J. [Harvard College Observatory, 60 Garden St., Cambridge, MA 02138 (United States); Wong, Kenneth C. [Steward Observatory, University of Arizona, 933 N. Cherry Ave., Tucson, AZ 85721 (United States)

2012-02-10

We present evidence that the incidence of active galactic nuclei (AGNs) and the distribution of their accretion rates do not depend on the stellar masses of their host galaxies, contrary to previous studies. We use hard (2-10 keV) X-ray data from three extragalactic fields (XMM-LSS, COSMOS, and ELAIS-S1) with redshifts from the Prism Multi-object Survey to identify 242 AGNs with L{sub 2-10keV} = 10{sup 42-44} erg s{sup -1} within a parent sample of {approx}25,000 galaxies at 0.2 < z < 1.0 over {approx}3.4 deg{sup 2} and to i {approx} 23. We find that although the fraction of galaxies hosting an AGN at fixed X-ray luminosity rises strongly with stellar mass, the distribution of X-ray luminosities is independent of mass. Furthermore, we show that the probability that a galaxy will host an AGN can be defined by a universal Eddington ratio distribution that is independent of the host galaxy stellar mass and has a power-law shape with slope -0.65. These results demonstrate that AGNs are prevalent at all stellar masses in the range 9.5< log M{sub *}/M{sub sun}<12 and that the same physical processes regulate AGN activity in all galaxies in this stellar mass range. While a higher AGN fraction may be observed in massive galaxies, this is a selection effect related to the underlying Eddington ratio distribution. We also find that the AGN fraction drops rapidly between z {approx} 1 and the present day and is moderately enhanced (factor {approx}2) in galaxies with blue or green optical colors. Consequently, while AGN activity and star formation appear to be globally correlated, we do not find evidence that the presence of an AGN is related to the quenching of star formation or the color transformation of galaxies.

A fuzzy multi-objective optimization model for sustainable reverse logistics network design

DEFF Research Database (Denmark)

Govindan, Kannan; Paam, Parichehr; Abtahi, Amir Reza

2016-01-01

Decreasing the environmental impact, increasing the degree of social responsibility, and considering the economic motivations of organizations are three significant features in designing a reverse logistics network under sustainability respects. Developing a model, which can simultaneously consider...... a multi-echelon multi-period multi-objective model for a sustainable reverse logistics network. To reflect all aspects of sustainability, we try to minimize the present value of costs, as well as environmental impacts, and optimize the social responsibility as objective functions of the model. In order...... these environmental, social, and economic aspects and their indicators, is an important problem for both researchers and practitioners. In this paper, we try to address this comprehensive approach by using indicators for measurement of aforementioned aspects and by applying fuzzy mathematical programming to design...

Multi-objective parallel particle swarm optimization for day-ahead Vehicle-to-Grid scheduling

DEFF Research Database (Denmark)

Soares, Joao; Vale, Zita; Canizes, Bruno

2013-01-01

This paper presents a methodology for multi-objective day-ahead energy resource scheduling for smart grids considering intensive use of distributed generation and Vehicle-To-Grid (V2G). The main focus is the application of weighted Pareto to a multi-objective parallel particle swarm approach aiming...... to solve the dual-objective V2G scheduling: minimizing total operation costs and maximizing V2G income. A realistic mathematical formulation, considering the network constraints and V2G charging and discharging efficiencies is presented and parallel computing is applied to the Pareto weights. AC power flow...

Project overview of OPTIMOS-EVE: the fibre-fed multi-object spectrograph for the E-ELT

NARCIS (Netherlands)

Navarro, R.; Chemla, F.; Bonifacio, P.; Flores, H.; Guinouard, I.; Huet, J.-M.; Puech, M.; Royer, F.; Pragt, J.H.; Wulterkens, G.; Sawyer, E.C.; Caldwell, M.E.; Tosh, I.A.J.; Whalley, M.S.; Woodhouse, G.F.W.; Spanò, P.; Di Marcantonio, P.; Andersen, M.I.; Dalton, G.B.; Kaper, L.; Hammer, F.

2010-01-01

OPTIMOS-EVE (OPTical Infrared Multi Object Spectrograph - Extreme Visual Explorer) is the fibre fed multi object spectrograph proposed for the European Extremely Large Telescope (E-ELT), planned to be operational in 2018 at Cerro Armazones (Chile). It is designed to provide a spectral resolution of

Multi-objective room acoustic optimization of timber folded plate structure

DEFF Research Database (Denmark)

Skov, Rasmus; Parigi, Dario; Damkilde, Lars

2017-01-01

This paper investigates the application of multi-objective optimization in the design of timber folded plate structures in the scope of the architectural design process. Considering contrasting objectives of structural displacement, early decay time (EDT), clarity (C50) and sound strength (G......), the methodology applied in two benchmarks tests, encompasses both structural and acoustic performance when determining folding characteristics and directionality of surfaces in a timber folded plate structure....

Fuzzy Multi Objective Linear Programming Problem with Imprecise Aspiration Level and Parameters

Directory of Open Access Journals (Sweden)

Zahra Shahraki

2015-07-01

Full Text Available This paper considers the multi-objective linear programming problems with fuzzygoal for each of the objective functions and constraints. Most existing works deal withlinear membership functions for fuzzy goals. In this paper, exponential membershipfunction is used.

A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

Science.gov (United States)

Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

2017-01-01

Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

Analytic hierarchy process-based approach for selecting a Pareto-optimal solution of a multi-objective, multi-site supply-chain planning problem

Science.gov (United States)

Ayadi, Omar; Felfel, Houssem; Masmoudi, Faouzi

2017-07-01

The current manufacturing environment has changed from traditional single-plant to multi-site supply chain where multiple plants are serving customer demands. In this article, a tactical multi-objective, multi-period, multi-product, multi-site supply-chain planning problem is proposed. A corresponding optimization model aiming to simultaneously minimize the total cost, maximize product quality and maximize the customer satisfaction demand level is developed. The proposed solution approach yields to a front of Pareto-optimal solutions that represents the trade-offs among the different objectives. Subsequently, the analytic hierarchy process method is applied to select the best Pareto-optimal solution according to the preferences of the decision maker. The robustness of the solutions and the proposed approach are discussed based on a sensitivity analysis and an application to a real case from the textile and apparel industry.

Computing Convex Coverage Sets for Faster Multi-Objective Coordination

NARCIS (Netherlands)

Roijers, D.M.; Whiteson, S.; Oliehoek, F.A.

2015-01-01

In this article, we propose new algorithms for multi-objective coordination graphs (MO-CoGs). Key to the efficiency of these algorithms is that they compute a convex coverage set (CCS) instead of a Pareto coverage set (PCS). Not only is a CCS a sufficient solution set for a large class of problems,

Multi-objective decision-making framework for effective waste collection in smart cities

CSIR Research Space (South Africa)

Manqele, Lindelweyizizwe

2017-10-01

Full Text Available T-enabled objects. This implies taking into account multi-objective goals in the collection process while dealing with complexities such as data loss during IoT based data collection. Understanding current decision-making algorithms highlights the deeper insight...

A framework for multi-object tracking over distributed wireless camera networks

Science.gov (United States)

Gau, Victor; Hwang, Jenq-Neng

2010-07-01

In this paper, we propose a unified framework targeting at two important issues in a distributed wireless camera network, i.e., object tracking and network communication, to achieve reliable multi-object tracking over distributed wireless camera networks. In the object tracking part, we propose a fully automated approach for tracking of multiple objects across multiple cameras with overlapping and non-overlapping field of views without initial training. To effectively exchange the tracking information among the distributed cameras, we proposed an idle probability based broadcasting method, iPro, which adaptively adjusts the broadcast probability to improve the broadcast effectiveness in a dense saturated camera network. Experimental results for the multi-object tracking demonstrate the promising performance of our approach on real video sequences for cameras with overlapping and non-overlapping views. The modeling and ns-2 simulation results show that iPro almost approaches the theoretical performance upper bound if cameras are within each other's transmission range. In more general scenarios, e.g., in case of hidden node problems, the simulation results show that iPro significantly outperforms standard IEEE 802.11, especially when the number of competing nodes increases.

Multi-objective genetic algorithm for solving N-version program design problem

Energy Technology Data Exchange (ETDEWEB)

Yamachi, Hidemi [Department of Computer and Information Engineering, Nippon Institute of Technology, Miyashiro, Saitama 345-8501 (Japan) and Department of Production and Information Systems Engineering, Tokyo Metropolitan Institute of Technology, Hino, Tokyo 191-0065 (Japan)]. E-mail: yamachi@nit.ac.jp; Tsujimura, Yasuhiro [Department of Computer and Information Engineering, Nippon Institute of Technology, Miyashiro, Saitama 345-8501 (Japan)]. E-mail: tujimr@nit.ac.jp; Kambayashi, Yasushi [Department of Computer and Information Engineering, Nippon Institute of Technology, Miyashiro, Saitama 345-8501 (Japan)]. E-mail: yasushi@nit.ac.jp; Yamamoto, Hisashi [Department of Production and Information Systems Engineering, Tokyo Metropolitan Institute of Technology, Hino, Tokyo 191-0065 (Japan)]. E-mail: yamamoto@cc.tmit.ac.jp

2006-09-15

N-version programming (NVP) is a programming approach for constructing fault tolerant software systems. Generally, an optimization model utilized in NVP selects the optimal set of versions for each module to maximize the system reliability and to constrain the total cost to remain within a given budget. In such a model, while the number of versions included in the obtained solution is generally reduced, the budget restriction may be so rigid that it may fail to find the optimal solution. In order to ameliorate this problem, this paper proposes a novel bi-objective optimization model that maximizes the system reliability and minimizes the system total cost for designing N-version software systems. When solving multi-objective optimization problem, it is crucial to find Pareto solutions. It is, however, not easy to obtain them. In this paper, we propose a novel bi-objective optimization model that obtains many Pareto solutions efficiently. We formulate the optimal design problem of NVP as a bi-objective 0-1 nonlinear integer programming problem. In order to overcome this problem, we propose a Multi-objective genetic algorithm (MOGA), which is a powerful, though time-consuming, method to solve multi-objective optimization problems. When implementing genetic algorithm (GA), the use of an appropriate genetic representation scheme is one of the most important issues to obtain good performance. We employ random-key representation in our MOGA to find many Pareto solutions spaced as evenly as possible along the Pareto frontier. To pursue improve further performance, we introduce elitism, the Pareto-insertion and the Pareto-deletion operations based on distance between Pareto solutions in the selection process. The proposed MOGA obtains many Pareto solutions along the Pareto frontier evenly. The user of the MOGA can select the best compromise solution among the candidates by controlling the balance between the system reliability and the total cost.

Multi-objective genetic algorithm for solving N-version program design problem

International Nuclear Information System (INIS)

Yamachi, Hidemi; Tsujimura, Yasuhiro; Kambayashi, Yasushi; Yamamoto, Hisashi

2006-01-01

N-version programming (NVP) is a programming approach for constructing fault tolerant software systems. Generally, an optimization model utilized in NVP selects the optimal set of versions for each module to maximize the system reliability and to constrain the total cost to remain within a given budget. In such a model, while the number of versions included in the obtained solution is generally reduced, the budget restriction may be so rigid that it may fail to find the optimal solution. In order to ameliorate this problem, this paper proposes a novel bi-objective optimization model that maximizes the system reliability and minimizes the system total cost for designing N-version software systems. When solving multi-objective optimization problem, it is crucial to find Pareto solutions. It is, however, not easy to obtain them. In this paper, we propose a novel bi-objective optimization model that obtains many Pareto solutions efficiently. We formulate the optimal design problem of NVP as a bi-objective 0-1 nonlinear integer programming problem. In order to overcome this problem, we propose a Multi-objective genetic algorithm (MOGA), which is a powerful, though time-consuming, method to solve multi-objective optimization problems. When implementing genetic algorithm (GA), the use of an appropriate genetic representation scheme is one of the most important issues to obtain good performance. We employ random-key representation in our MOGA to find many Pareto solutions spaced as evenly as possible along the Pareto frontier. To pursue improve further performance, we introduce elitism, the Pareto-insertion and the Pareto-deletion operations based on distance between Pareto solutions in the selection process. The proposed MOGA obtains many Pareto solutions along the Pareto frontier evenly. The user of the MOGA can select the best compromise solution among the candidates by controlling the balance between the system reliability and the total cost

Application of evolutionary algorithms for multi-objective optimization in VLSI and embedded systems

CERN Document Server

2015-01-01

This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design. Many complex engineering optimization problems can be modelled as multi-objective formulations. This book provides an introduction to multi-objective optimization using meta-heuristic algorithms, GA and PSO, and how they can be applied to problems like hardware/software partitioning in embedded systems, circuit partitioning in VLSI, design of operational amplifiers in analog VLSI, design space exploration in high-level synthesis, delay fault testing in VLSI testing, and scheduling in heterogeneous distributed systems. It is shown how, in each case, the various aspects of the EA, namely its representation, and operators like crossover, mutation, etc. can be separately formulated to solve these problems. This book is intended for design engineers and researchers in the field ...

SU-F-R-46: Predicting Distant Failure in Lung SBRT Using Multi-Objective Radiomics Model

Energy Technology Data Exchange (ETDEWEB)

Zhou, Z; Folkert, M; Iyengar, P; Zhang, Y; Wang, J [UT Southwestern Medical Center, Dallas, TX (United States)

2016-06-15

Purpose: To predict distant failure in lung stereotactic body radiation therapy (SBRT) in early stage non-small cell lung cancer (NSCLC) by using a new multi-objective radiomics model. Methods: Currently, most available radiomics models use the overall accuracy as the objective function. However, due to data imbalance, a single object may not reflect the performance of a predictive model. Therefore, we developed a multi-objective radiomics model which considers both sensitivity and specificity as the objective functions simultaneously. The new model is used to predict distant failure in lung SBRT using 52 patients treated at our institute. Quantitative imaging features of PET and CT as well as clinical parameters are utilized to build the predictive model. Image features include intensity features (9), textural features (12) and geometric features (8). Clinical parameters for each patient include demographic parameters (4), tumor characteristics (8), treatment faction schemes (4) and pretreatment medicines (6). The modelling procedure consists of two steps: extracting features from segmented tumors in PET and CT; and selecting features and training model parameters based on multi-objective. Support Vector Machine (SVM) is used as the predictive model, while a nondominated sorting-based multi-objective evolutionary computation algorithm II (NSGA-II) is used for solving the multi-objective optimization. Results: The accuracy for PET, clinical, CT, PET+clinical, PET+CT, CT+clinical, PET+CT+clinical are 71.15%, 84.62%, 84.62%, 85.54%, 82.69%, 84.62%, 86.54%, respectively. The sensitivities for the above seven combinations are 41.76%, 58.33%, 50.00%, 50.00%, 41.67%, 41.67%, 58.33%, while the specificities are 80.00%, 92.50%, 90.00%, 97.50%, 92.50%, 97.50%, 97.50%. Conclusion: A new multi-objective radiomics model for predicting distant failure in NSCLC treated with SBRT was developed. The experimental results show that the best performance can be obtained by combining

THE SPITZER SURVEY OF STELLAR STRUCTURE IN GALAXIES (S4G): MULTI-COMPONENT DECOMPOSITION STRATEGIES AND DATA RELEASE

International Nuclear Information System (INIS)

Salo, Heikki; Laurikainen, Eija; Laine, Jarkko; Comerón, Sebastien; Gadotti, Dimitri A.; Kim, Taehyun; Buta, Ron; Sheth, Kartik; Muñoz-Mateos, Juan Carlos; Zaritsky, Dennis; Hinz, Joannah L.; Ho, Luis; Knapen, Johan; Cisternas, Mauricio; Athanassoula, E.; Bosma, Albert; Laine, Seppo; Regan, Michael; De Paz, Armando Gil; Menendez-Delmestre, Karin

2015-01-01

The Spitzer Survey of Stellar Structure in Galaxies (S 4 G) is a deep 3.6 and 4.5 μm imaging survey of 2352 nearby (<40 Mpc) galaxies. We describe the S 4 G data analysis pipeline 4, which is dedicated to two-dimensional structural surface brightness decompositions of 3.6 μm images, using GALFIT3.0. Besides automatic 1-component Sérsic fits, and 2-component Sérsic bulge + exponential disk fits, we present human-supervised multi-component decompositions, which include, when judged appropriate, a central point source, bulge, disk, and bar components. Comparison of the fitted parameters indicates that multi-component models are needed to obtain reliable estimates for the bulge Sérsic index and bulge-to-total light ratio (B/T), confirming earlier results. Here, we describe the preparations of input data done for decompositions, give examples of our decomposition strategy, and describe the data products released via IRSA and via our web page (www.oulu.fi/astronomy/S4G-PIPELINE4/MAIN). These products include all the input data and decomposition files in electronic form, making it easy to extend the decompositions to suit specific science purposes. We also provide our IDL-based visualization tools (GALFIDL) developed for displaying/running GALFIT-decompositions, as well as our mask editing procedure (MASK-EDIT) used in data preparation. A detailed analysis of the bulge, disk, and bar parameters derived from multi-component decompositions will be published separately

A new analysis of the momentum and mass-loss rates of stellar jets

International Nuclear Information System (INIS)

Raga, A.C.

1991-01-01

A very important question in the theory of bipolar outflows from young stars is posed by the still not understood relation between molecular outflows and optical outflows (i.e., stellar jets and Herbig-Haro objects). In some past studies, estimates of mass and momentum rates associated with these outflows indicated that stellar jets have approximately 2 orders of magnitude smaller values for these parameters than the molecular outflows associated with the same sources. However, a reanalysis of observations of stellar jets in the light of new theoretical jet models yields values of mass and momentum rates comparable to the ones of molecular outflows. From this result it can be tentatively speculated that stellar jets (or Herbig-Haro objects) and molecular outflows might be different manifestations of basically the same flow. 21 refs

Towards lexicographic multi-objective linear programming using grossone methodology

Science.gov (United States)

Cococcioni, Marco; Pappalardo, Massimo; Sergeyev, Yaroslav D.

2016-10-01

Lexicographic Multi-Objective Linear Programming (LMOLP) problems can be solved in two ways: preemptive and nonpreemptive. The preemptive approach requires the solution of a series of LP problems, with changing constraints (each time the next objective is added, a new constraint appears). The nonpreemptive approach is based on a scalarization of the multiple objectives into a single-objective linear function by a weighted combination of the given objectives. It requires the specification of a set of weights, which is not straightforward and can be time consuming. In this work we present both mathematical and software ingredients necessary to solve LMOLP problems using a recently introduced computational methodology (allowing one to work numerically with infinities and infinitesimals) based on the concept of grossone. The ultimate goal of such an attempt is an implementation of a simplex-like algorithm, able to solve the original LMOLP problem by solving only one single-objective problem and without the need to specify finite weights. The expected advantages are therefore obvious.

Teaching stellar interferometry with polymer optical fibers

Science.gov (United States)

Illarramendi, M. A.; Arregui, L.; Zubia, J.; Hueso, R.; Sanchez-Lavega, A.

2017-08-01

In this manuscript we show the design of a simple experiment that reproduces the operation of the Michelson stellar interferometer by using step-index polymer optical fibers. The emission of stellar sources, single or binary stars, has been simulated by the laser light emerging from the output surface of the 2 meter-long polymer optical fiber. This light has an emission pattern that is similar to the emission pattern of stellar sources - circular, uniform, spatially incoherent, and quasi-monochromatic. Light coming from the fiber end faces passes through two identical pinholes located on a lid covering the objective of a small telescope, thus producing interference. Interference fringes have been acquired using a camera that is coupled to a telescope. The experiments have been carried out both outdoors in the daytime and indoors. By measuring the fringe visibilities, we have determined the size of our artificial stellar sources and the distance between them, when placing them at distances of 54 m from the telescope in the indoor measurements and of 75 m in the outdoor ones.

Optimal Golomb Ruler Sequences Generation for Optical WDM Systems: A Novel Parallel Hybrid Multi-objective Bat Algorithm

Science.gov (United States)

Bansal, Shonak; Singh, Arun Kumar; Gupta, Neena

2017-02-01

In real-life, multi-objective engineering design problems are very tough and time consuming optimization problems due to their high degree of nonlinearities, complexities and inhomogeneity. Nature-inspired based multi-objective optimization algorithms are now becoming popular for solving multi-objective engineering design problems. This paper proposes original multi-objective Bat algorithm (MOBA) and its extended form, namely, novel parallel hybrid multi-objective Bat algorithm (PHMOBA) to generate shortest length Golomb ruler called optimal Golomb ruler (OGR) sequences at a reasonable computation time. The OGRs found their application in optical wavelength division multiplexing (WDM) systems as channel-allocation algorithm to reduce the four-wave mixing (FWM) crosstalk. The performances of both the proposed algorithms to generate OGRs as optical WDM channel-allocation is compared with other existing classical computing and nature-inspired algorithms, including extended quadratic congruence (EQC), search algorithm (SA), genetic algorithms (GAs), biogeography based optimization (BBO) and big bang-big crunch (BB-BC) optimization algorithms. Simulations conclude that the proposed parallel hybrid multi-objective Bat algorithm works efficiently as compared to original multi-objective Bat algorithm and other existing algorithms to generate OGRs for optical WDM systems. The algorithm PHMOBA to generate OGRs, has higher convergence and success rate than original MOBA. The efficiency improvement of proposed PHMOBA to generate OGRs up to 20-marks, in terms of ruler length and total optical channel bandwidth (TBW) is 100 %, whereas for original MOBA is 85 %. Finally the implications for further research are also discussed.

A hybrid multi-objective cultural algorithm for short-term environmental/economic hydrothermal scheduling

International Nuclear Information System (INIS)

Lu Youlin; Zhou Jianzhong; Qin Hui; Wang Ying; Zhang Yongchuan

2011-01-01

Research highlights: → Multi-objective optimization model of short-term environmental/economic hydrothermal scheduling. → A hybrid multi-objective cultural algorithm (HMOCA) is presented. → New heuristic constraint handling methods are proposed. → Better quality solutions by reducing fuel cost and emission effects simultaneously are obtained. -- Abstract: The short-term environmental/economic hydrothermal scheduling (SEEHS) with the consideration of multiple objectives is a complicated non-linear constrained optimization problem with non-smooth and non-convex characteristics. In this paper, a multi-objective optimization model of SEEHS is proposed to consider the minimal of fuel cost and emission effects synthetically, and the transmission loss, the water transport delays between connected reservoirs as well as the valve-point effects of thermal plants are taken into consideration to formulate the problem precisely. Meanwhile, a hybrid multi-objective cultural algorithm (HMOCA) is presented to deal with SEEHS problem by optimizing both two objectives simultaneously. The proposed method integrated differential evolution (DE) algorithm into the framework of cultural algorithm model to implement the evolution of population space, and two knowledge structures in belief space are redefined according to the characteristics of DE and SEEHS problem to avoid premature convergence effectively. Moreover, in order to deal with the complicated constraints effectively, new heuristic constraint handling methods without any penalty factor settings are proposed in this paper. The feasibility and effectiveness of the proposed HMOCA method are demonstrated by two case studies of a hydrothermal power system. The simulation results reveal that, compared with other methods established recently, HMOCA can get better quality solutions by reducing fuel cost and emission effects simultaneously.

Nonlinear MHD and energetic particle modes in stellarators

International Nuclear Information System (INIS)

Strauss, H.R.; Fu, G.Y.; Park, W.; Breslau, J.; Sugiyama, L.E.

2003-01-01

The M3D (Multi-level 3D) project carries out simulation studies of plasmas using multiple levels of physics, geometry and grid models. The M3D code has been applied to ideal, resistive, two fluid, and hybrid simulations of compact quasi axisymmetric stellarators. When β exceeds a threshold, moderate toroidal mode number (n ∼ 10) modes grow exponentially, clearly distinguishable from the equilibrium evolution. The β limits are significantly higher than the infinite mode number ballooning limits. In the presence of resistivity, these modes occur well below the ideal limit. Their growth rate scaling with resistivity is similar to tearing modes. At low resistivity, the modes couple to resistive interchanges, which are unstable in most stellarators. Two fluid simulations with M3D show that resistive modes can be stabilized by diamagnetic drift. The two fluid computations are done with a realistic value of the Hall parameter, the ratio of ion skin depth to major radius. Hybrid gyrokinetic simulations with energetic particles indicate that global shear Alfven TAE - like modes can be destabilized in stellarators. Computations in a two-period compact stellarator obtained a predominantly n=1 toroidal mode with the expected TAE frequency. It is found that TAE modes are more stable in the two-period compact stellarator that in a tokamak with the same q and pressure profiles. M3D combines a two dimensional unstructured mesh with finite element discretization in poloidal planes, and fourth order finite differencing in the toroidal direction. (author)

Growth of a Massive Young Stellar Object Fed by a Gas Flow from a Companion Gas Clump

Energy Technology Data Exchange (ETDEWEB)

Chen, Xi; Shen, Zhiqiang [Shanghai Astronomical Observatories, Chinese Academy of Science, Nandan Rd. 80, Shanghai (China); Ren, Zhiyuan [National Astronomical Observatories, Chinese Academy of Science, Chaoyang District Datun Rd. A20, Beijing (China); Zhang, Qizhou [Harvard-Smithsonian Center for Astrophysics, 60 Garden St, Cambridge, MA 02138 (United States); Qiu, Keping [School of Astronomy and Space Science, Nanjing University, 22 Hankou Rd., Nanjing, Jiangsu 210093 (China)

2017-02-01

We present a Submillimeter Array (SMA) observation toward the young massive double-core system G350.69-0.49. This system consists of a northeast (NE) diffuse gas bubble and a southwest (SW) massive young stellar object (MYSO), both clearly seen in the Spitzer images. The SMA observations reveal a gas flow between the NE bubble and the SW MYSO in a broad velocity range from 5 to 30 km s{sup −1} with respect to the system velocity. The gas flow is well confined within the interval between the two objects and traces a significant mass transfer from the NE gas bubble to the SW massive core. The transfer flow can supply the material accreted onto the SW MYSO at a rate of 4.2×10{sup −4} M{sub ⊙} yr{sup −1}. The whole system therefore suggests a mode for the mass growth in the MYSO from a gas transfer flow launched from its companion gas clump, despite the driving mechanism of the transfer flow not being fully determined from the current data.

Global Vlasov simulation on magnetospheres of astronomical objects

International Nuclear Information System (INIS)

Umeda, Takayuki; Ito, Yosuke; Fukazawa, Keiichiro

2013-01-01

Space plasma is a collisionless, multi-scale, and highly nonlinear medium. There are various types of self-consistent computer simulations that treat space plasma according to various approximations. We develop numerical schemes for solving the Vlasov (collisionless Boltzmann) equation, which is the first-principle kinetic equation for collisionless plasma. The weak-scaling benchmark test shows that our parallel Vlasov code achieves a high performance and a high scalability. Currently, we use more than 1000 cores for parallel computations and apply the present parallel Vlasov code to various cross-scale processes in space plasma, such as a global simulation on the interaction between solar/stellar wind and magnetospheres of astronomical objects

A multi-objective multi-memetic algorithm for network-wide conflict-free 4D flight trajectories planning

Institute of Scientific and Technical Information of China (English)

Su YAN; Kaiquan CAI

2017-01-01

Under the demand of strategic air traffic flow management and the concept of trajectory based operations (TBO),the network-wide 4D flight trajectories planning (N4DFTP) problem has been investigated with the purpose of safely and efficiently allocating 4D trajectories (4DTs) (3D position and time) for all the flights in the whole airway network.Considering that the introduction of large-scale 4DTs inevitably increases the problem complexity,an efficient model for strategic level conflict management is developed in this paper.Specifically,a bi-objective N4DFTP problem that aims to minimize both potential conflicts and the trajectory cost is formulated.In consideration of the large-scale,high-complexity,and multi-objective characteristics of the N4DFTP problem,a multi-objective multi-memetic algorithm (MOMMA) that incorporates an evolutionary global search framework together with three problem-specific local search operators is implemented.It is capable of rapidly and effectively allocating 4DTs via rerouting,target time controlling,and flight level changing.Additionally,to balance the ability of exploitation and exploration of the algorithm,a special hybridization scheme is adopted for the integration of local and global search.Empirical studies using real air traffic data in China with different network complexities show that the pro posed MOMMA is effective to solve the N4DFTP problem.The solutions achieved are competitive for elaborate decision support under a TBO environment.

A multi-objective multi-memetic algorithm for network-wide conflict-free 4D flight trajectories planning

Directory of Open Access Journals (Sweden)

Su YAN

2017-06-01

Full Text Available Under the demand of strategic air traffic flow management and the concept of trajectory based operations (TBO, the network-wide 4D flight trajectories planning (N4DFTP problem has been investigated with the purpose of safely and efficiently allocating 4D trajectories (4DTs (3D position and time for all the flights in the whole airway network. Considering that the introduction of large-scale 4DTs inevitably increases the problem complexity, an efficient model for strategic-level conflict management is developed in this paper. Specifically, a bi-objective N4DFTP problem that aims to minimize both potential conflicts and the trajectory cost is formulated. In consideration of the large-scale, high-complexity, and multi-objective characteristics of the N4DFTP problem, a multi-objective multi-memetic algorithm (MOMMA that incorporates an evolutionary global search framework together with three problem-specific local search operators is implemented. It is capable of rapidly and effectively allocating 4DTs via rerouting, target time controlling, and flight level changing. Additionally, to balance the ability of exploitation and exploration of the algorithm, a special hybridization scheme is adopted for the integration of local and global search. Empirical studies using real air traffic data in China with different network complexities show that the proposed MOMMA is effective to solve the N4DFTP problem. The solutions achieved are competitive for elaborate decision support under a TBO environment.

2MASS J11151597+1937266: A Young, Dusty, Isolated, Planetary-mass Object with a Potential Wide Stellar Companion

Science.gov (United States)

Theissen, Christopher A.; Burgasser, Adam J.; Bardalez Gagliuffi, Daniella C.; Hardegree-Ullman, Kevin K.; Gagné, Jonathan; Schmidt, Sarah J.; West, Andrew A.

2018-01-01

We present 2MASS J11151597+1937266, a recently identified low-surface-gravity L dwarf, classified as an L2γ based on Sloan Digital Sky Survey optical spectroscopy. We confirm this spectral type with near-infrared spectroscopy, which provides further evidence that 2MASS J11151597+1937266 is a low-surface-gravity L dwarf. This object also shows significant excess mid-infrared flux, indicative of circumstellar material; and its strong Hα emission (EWHα = 560 ± 82 Å) is an indicator of enhanced magnetic activity or weak accretion. Comparison of its spectral energy distribution to model photospheres yields an effective temperature of {1724}-38+184 {{K}}. We also provide a revised distance estimate of 37 ± 6 pc using a spectral type–luminosity relationship for low-surface-gravity objects. The three-dimensional galactic velocities and positions of 2MASS J11151597+1937266 do not match any known young association or moving group. Assuming a probable age in the range of 5–45 Myr, the model-dependent estimated mass of this object is between 7 and 21 M Jup, making it a potentially isolated planetary-mass object. We also identify a candidate co-moving, young stellar companion, 2MASS J11131089+2110086.

Ensemble-based hierarchical multi-objective production optimization of smart wells

NARCIS (Netherlands)

Fonseca, R.M.; Leeuwenburgh, O.; Van den Hof, P.M.J.; Jansen, J.D.

2014-01-01

In an earlier study two hierarchical multi-objective methods were suggested to include short-term targets in life-cycle production optimization. However this earlier study has two limitations: 1) the adjoint formulation is used to obtain gradient information, requiring simulator source code access

A Multi-Objective Trade-Off Model in Sustainable Construction Projects

Directory of Open Access Journals (Sweden)

Guangdong Wu

2017-10-01

Full Text Available Based on the consideration of the relative importance of sustainability-related objectives and the inherent nature of sustainable construction projects, this study proposes that the contractor can balance the levels of efforts and resources used to improve the overall project sustainability. A multi-objective trade-off model using game theory was established and verified through simulation and numerical example under a moral hazard situation. Results indicate that effort levels of the contractor on sustainability-related objectives are positively related to the outcome coefficient while negatively to the coefficients of effort cost of the relevant objectives. High levels of the relative importance of sustainability-related objectives contribute to high levels of effort of the contractor. With the variation in effort levels and the coefficient of benefit allocation, the project net benefit increases before declining. The function of project benefit has a marked peak value, with an inverted “U” shape. An equilibrium always exists as for the given relative importance and coefficients of the effort costs of sustainability-related objectives. Under this condition, the owner may offer the contractor a less intense incentive and motivate the contractor reasonably arranging input resources. The coefficient of benefit allocation is affected by the contractor characteristic factors and the project characteristic factors. The owner should balance these two types of factors and select the most appropriate incentive mechanism to improve the project benefit. Meanwhile, the contractor can balance the relative importance of the objectives and arrange the appropriate levels of effort and resources to achieve a sustainability-related objective. Very few studies have emphasized the effects of the relative importance of sustainability-related objectives on the benefits of sustainable construction projects. This study therefore builds a multi-objective trade

Multi-objective optimization approach for air traffic flow management

Directory of Open Access Journals (Sweden)

Fadil Rabie

2017-01-01

The decision-making stage was then performed with the aid of data clustering techniques to reduce the sizeof the Pareto-optimal set and obtain a smaller representation of the multi-objective design space, there by making it easier for the decision-maker to find satisfactory and meaningful trade-offs, and to select a preferred final design solution.

Multi-Modal Inference in Animacy Perception for Artificial Object

Directory of Open Access Journals (Sweden)

Kohske Takahashi

2011-10-01

Full Text Available Sometimes we feel animacy for artificial objects and their motion. Animals usually interact with environments through multiple sensory modalities. Here we investigated how the sensory responsiveness of artificial objects to the environment would contribute to animacy judgment for them. In a 90-s trial, observers freely viewed four objects moving in a virtual 3D space. The objects, whose position and motion were determined following Perlin-noise series, kept drifting independently in the space. Visual flashes, auditory bursts, or synchronous flashes and bursts appeared with 1–2 s intervals. The first object abruptly accelerated their motion just after visual flashes, giving an impression of responding to the flash. The second object responded to bursts. The third object responded to synchronous flashes and bursts. The forth object accelerated at a random timing independent of flashes and bursts. The observers rated how strongly they felt animacy for each object. The results showed that the object responding to the auditory bursts was rated as having weaker animacy compared to the other objects. This implies that sensory modality through which an object interacts with the environment may be a factor for animacy perception in the object and may serve as the basis of multi-modal and cross-modal inference of animacy.

Stochastic resource allocation in emergency departments with a multi-objective simulation optimization algorithm.

Science.gov (United States)

Feng, Yen-Yi; Wu, I-Chin; Chen, Tzu-Li

2017-03-01

The number of emergency cases or emergency room visits rapidly increases annually, thus leading to an imbalance in supply and demand and to the long-term overcrowding of hospital emergency departments (EDs). However, current solutions to increase medical resources and improve the handling of patient needs are either impractical or infeasible in the Taiwanese environment. Therefore, EDs must optimize resource allocation given limited medical resources to minimize the average length of stay of patients and medical resource waste costs. This study constructs a multi-objective mathematical model for medical resource allocation in EDs in accordance with emergency flow or procedure. The proposed mathematical model is complex and difficult to solve because its performance value is stochastic; furthermore, the model considers both objectives simultaneously. Thus, this study develops a multi-objective simulation optimization algorithm by integrating a non-dominated sorting genetic algorithm II (NSGA II) with multi-objective computing budget allocation (MOCBA) to address the challenges of multi-objective medical resource allocation. NSGA II is used to investigate plausible solutions for medical resource allocation, and MOCBA identifies effective sets of feasible Pareto (non-dominated) medical resource allocation solutions in addition to effectively allocating simulation or computation budgets. The discrete event simulation model of ED flow is inspired by a Taiwan hospital case and is constructed to estimate the expected performance values of each medical allocation solution as obtained through NSGA II. Finally, computational experiments are performed to verify the effectiveness and performance of the integrated NSGA II and MOCBA method, as well as to derive non-dominated medical resource allocation solutions from the algorithms.

Image Segmentation Method Using Fuzzy C Mean Clustering Based on Multi-Objective Optimization

Science.gov (United States)

Chen, Jinlin; Yang, Chunzhi; Xu, Guangkui; Ning, Li

2018-04-01

Image segmentation is not only one of the hottest topics in digital image processing, but also an important part of computer vision applications. As one kind of image segmentation algorithms, fuzzy C-means clustering is an effective and concise segmentation algorithm. However, the drawback of FCM is that it is sensitive to image noise. To solve the problem, this paper designs a novel fuzzy C-mean clustering algorithm based on multi-objective optimization. We add a parameter λ to the fuzzy distance measurement formula to improve the multi-objective optimization. The parameter λ can adjust the weights of the pixel local information. In the algorithm, the local correlation of neighboring pixels is added to the improved multi-objective mathematical model to optimize the clustering cent. Two different experimental results show that the novel fuzzy C-means approach has an efficient performance and computational time while segmenting images by different type of noises.

A Theoretical Model of X-Ray Jets from Young Stellar Objects

Energy Technology Data Exchange (ETDEWEB)

Takasao, Shinsuke; Suzuki, Takeru K. [Department of Physics, Nagoya University, Nagoya, Aichi 464-8602 (Japan); Shibata, Kazunari, E-mail: takasao@kwasan.kyoto-u.ac.jp [Kwasan and Hida Observatories, Kyoto University, Yamashina, Kyoto 607-8471 (Japan)

2017-09-20

There is a subclass of X-ray jets from young stellar objects that are heated very close to the footpoint of the jets, particularly DG Tau jets. Previous models have attributed the strong heating to shocks in the jets. However, the mechanism that localizes the heating at the footpoint remains puzzling. We presented a different model of such X-ray jets, in which the disk atmosphere is magnetically heated. Our disk corona model is based on the so-called nanoflare model for the solar corona. We show that the magnetic heating near the disks can result in the formation of a hot corona with a temperature of ≳10{sup 6} K, even if the average field strength in the disk is moderately weak, ≳1 G. We determine the density and the temperature at the jet base by considering the energy balance between the heating and cooling. We derive the scaling relations of the mass-loss rate and terminal velocity of jets. Our model is applied to the DG Tau jets. The observed temperature and estimated mass-loss rate are consistent with the prediction of our model in the case of a disk magnetic field strength of ∼20 G and a heating region of <0.1 au. The derived scaling relation of the temperature of X-ray jets could be a useful tool for estimating the magnetic field strength. We also find that the jet X-ray can have a significant impact on the ionization degree near the disk surface and the dead zone size.

Multi objective decision making in hybrid energy system design

Science.gov (United States)

Merino, Gabriel Guillermo

The design of grid-connected photovoltaic wind generator system supplying a farmstead in Nebraska has been undertaken in this dissertation. The design process took into account competing criteria that motivate the use of different sources of energy for electric generation. The criteria considered were 'Financial', 'Environmental', and 'User/System compatibility'. A distance based multi-objective decision making methodology was developed to rank design alternatives. The method is based upon a precedence order imposed upon the design objectives and a distance metric describing the performance of each alternative. This methodology advances previous work by combining ambiguous information about the alternatives with a decision-maker imposed precedence order in the objectives. Design alternatives, defined by the photovoltaic array and wind generator installed capacities, were analyzed using the multi-objective decision making approach. The performance of the design alternatives was determined by simulating the system using hourly data for an electric load for a farmstead and hourly averages of solar irradiation, temperature and wind speed from eight wind-solar energy monitoring sites in Nebraska. The spatial variability of the solar energy resource within the region was assessed by determining semivariogram models to krige hourly and daily solar radiation data. No significant difference was found in the predicted performance of the system when using kriged solar radiation data, with the models generated vs. using actual data. The spatial variability of the combined wind and solar energy resources was included in the design analysis by using fuzzy numbers and arithmetic. The best alternative was dependent upon the precedence order assumed for the main criteria. Alternatives with no PV array or wind generator dominated when the 'Financial' criteria preceded the others. In contrast, alternatives with a nil component of PV array but a high wind generator component

Nonlinear bioheat transfer models and multi-objective numerical optimization of the cryosurgery operations

Energy Technology Data Exchange (ETDEWEB)

Kudryashov, Nikolay A.; Shilnikov, Kirill E. [National Research Nuclear University MEPhI, Department of Applied Mathematics, Moscow (Russian Federation)

2016-06-08

Numerical computation of the three dimensional problem of the freezing interface propagation during the cryosurgery coupled with the multi-objective optimization methods is used in order to improve the efficiency and safety of the cryosurgery operations performing. Prostate cancer treatment and cutaneous cryosurgery are considered. The heat transfer in soft tissue during the thermal exposure to low temperature is described by the Pennes bioheat model and is coupled with an enthalpy method for blurred phase change computations. The finite volume method combined with the control volume approximation of the heat fluxes is applied for the cryosurgery numerical modeling on the tumor tissue of a quite arbitrary shape. The flux relaxation approach is used for the stability improvement of the explicit finite difference schemes. The method of the additional heating elements mounting is studied as an approach to control the cellular necrosis front propagation. Whereas the undestucted tumor tissue and destucted healthy tissue volumes are considered as objective functions, the locations of additional heating elements in cutaneous cryosurgery and cryotips in prostate cancer cryotreatment are considered as objective variables in multi-objective problem. The quasi-gradient method is proposed for the searching of the Pareto front segments as the multi-objective optimization problem solutions.

Transient Mass-loss Analysis of Solar Observations Using Stellar Methods

Energy Technology Data Exchange (ETDEWEB)

Crosley, M. K.; Norman, C. [Johns Hopkins University, Department of Physics and Astronomy, 3400 N. Charles Street, Baltimore, MD 21218 (United States); Osten, R. A. [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States)

2017-08-10

Low-frequency dynamic spectra of radio bursts from nearby stars offer the best chance to directly detect the stellar signature of transient mass loss on low-mass stars. Crosley et al. (2016) proposes a multi-wavelength methodology to determine coronal mass ejection (CME) parameters, such as speed, mass, and kinetic energy. We test the validity and accuracy of the results derived from the methodology by using Geostationary Operational Environmental Satellite X-ray observations and Bruny Island Radio Spectrometer radio observations. These are analogous observations to those that would be found in the stellar studies. Derived results from these observations are compared to direct white light measurements of the Large Angle and Spectrometric Coronagraph. We find that, when a pre-event temperature can be determined, the accuracy of CME speeds are within a few hundred km s{sup −1}, and are reliable when specific criteria has been met. CME mass and kinetic energies are only useful in determining the approximate order of magnitude measurements when considering the large errors associated to them. These results will be directly applicable to the interpretation of any detected stellar events and the derivation of stellar CME properties.

A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

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Marko Budinich

Full Text Available Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA and multi-objective flux variability analysis (MO-FVA. Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity that take place at the ecosystem scale.

Stellar-Mass Black Holes in the Solar Neighborhood

CERN Document Server

Chisholm, J S R; Kolb, Edward W; Chisholm, James R.; Dodelson, Scott; Kolb, Edward W.

2003-01-01

We search for nearby, isolated, accreting, ``stellar-mass'' (3 to $100M_\\odot$) black holes. Models suggest a synchrotron spectrum in visible wavelengths and some emission in X-ray wavelengths. Of 3.7 million objects in the Sloan Digital Sky Survey Early Data Release, about 150,000 have colors and properties consistent with such a spectrum, and 47 of these objects are X-ray sources from the ROSAT All Sky Survey. Optical spectra exclude seven of these. We give the positions and colors of these 40 black-hole candidates, as well as a measure of their distances from the stellar loci in color--color space. We discuss uncertainties the expected number of sources, and the contribution of black holes to local dark matter.

Improving package structure of object-oriented software using multi-objective optimization and weighted class connections

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Amarjeet

2017-07-01

Full Text Available The software maintenance activities performed without following the original design decisions about the package structure usually deteriorate the quality of software modularization, leading to decay of the quality of the system. One of the main reasons for such structural deterioration is inappropriate grouping of source code classes in software packages. To improve such grouping/modular-structure, previous researchers formulated the software remodularization problem as an optimization problem and solved it using search-based meta-heuristic techniques. These optimization approaches aimed at improving the quality metrics values of the structure without considering the original package design decisions, often resulting into a totally new software modularization. The entirely changed software modularization becomes costly to realize as well as difficult to understand for the developers/maintainers. To alleviate this issue, we propose a multi-objective optimization approach to improve the modularization quality of an object-oriented system with minimum possible movement of classes between existing packages of original software modularization. The optimization is performed using NSGA-II, a widely-accepted multi-objective evolutionary algorithm. In order to ensure minimum modification of original package structure, a new approach of computing class relations using weighted strengths has been proposed here. The weights of relations among different classes are computed on the basis of the original package structure. A new objective function has been formulated using these weighted class relations. This objective function drives the optimization process toward better modularization quality simultaneously ensuring preservation of original structure. To evaluate the results of the proposed approach, a series of experiments are conducted over four real-worlds and two random software applications. The experimental results clearly indicate the effectiveness

Multi-objective ant algorithm for wireless sensor network positioning

International Nuclear Information System (INIS)

Fidanova, S.; Shindarov, M.; Marinov, P.

2013-01-01

It is impossible to imagine our modern life without telecommunications. Wireless networks are a part of telecommunications. Wireless sensor networks (WSN) consist of spatially distributed sensors, which communicate in wireless way. This network monitors physical or environmental conditions. The objective is the full coverage of the monitoring region and less energy consumption of the network. The most appropriate approach to solve the problem is metaheuristics. In this paper the full coverage of the area is treated as a constrain. The objectives which are optimized are a minimal number of sensors and energy (lifetime) of the network. We apply multi-objective Ant Colony Optimization to solve this important telecommunication problem. We chose MAX-MIN Ant System approach, because it is proven to converge to the global optima

Constraining stellar physics from red-giant stars in binaries – stellar rotation, mixing processes and stellar activity

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Beck P. G.

2017-01-01

Full Text Available The unparalleled photometric data obtained by NASA’s Kepler Space Telescope has led to an improved understanding of stellar structure and evolution - in particular for solar-like oscillators in this context. Binary stars are fascinating objects. Because they were formed together, binary systems provide a set of two stars with very well constrained parameters. Those can be used to study properties and physical processes, such as the stellar rotation, dynamics and rotational mixing of elements and allows us to learn from the differences we find between the two components. In this work, we discussed a detailed study of the binary system KIC 9163796, discovered through Kepler photometry. The ground-based follow-up spectroscopy showed that this system is a double-lined spectroscopic binary, with a mass ratio close to unity. However, the fundamental parameters of the components of this system as well as their lithium abundances differ substantially. Kepler photometry of this system allows to perform a detailed seismic analysis as well as to derive the orbital period and the surface rotation rate of the primary component of the system. Indications of the seismic signature of the secondary are found. The differing parameters are best explained with both components located in the early and the late phase of the first dredge up at the bottom of the red-giant branch. Observed lithium abundances in both components are in good agreement with prediction of stellar models including rotational mixing. By combining observations and theory, a comprehensive picture of the system can be drawn.

Research on connection structure of aluminumbody bus using multi-objective topology optimization

Science.gov (United States)

Peng, Q.; Ni, X.; Han, F.; Rhaman, K.; Ulianov, C.; Fang, X.

2018-01-01

For connecting Aluminum Alloy bus body aluminum components often occur the problem of failure, a new aluminum alloy connection structure is designed based on multi-objective topology optimization method. Determining the shape of the outer contour of the connection structure with topography optimization, establishing a topology optimization model of connections based on SIMP density interpolation method, going on multi-objective topology optimization, and improving the design of the connecting piece according to the optimization results. The results show that the quality of the aluminum alloy connector after topology optimization is reduced by 18%, and the first six natural frequencies are improved and the strength performance and stiffness performance are obviously improved.

Investigating multi-objective fluence and beam orientation IMRT optimization

Science.gov (United States)

Potrebko, Peter S.; Fiege, Jason; Biagioli, Matthew; Poleszczuk, Jan

2017-07-01

Radiation Oncology treatment planning requires compromises to be made between clinical objectives that are invariably in conflict. It would be beneficial to have a ‘bird’s-eye-view’ perspective of the full spectrum of treatment plans that represent the possible trade-offs between delivering the intended dose to the planning target volume (PTV) while optimally sparing the organs-at-risk (OARs). In this work, the authors demonstrate Pareto-aware radiotherapy evolutionary treatment optimization (PARETO), a multi-objective tool featuring such bird’s-eye-view functionality, which optimizes fluence patterns and beam angles for intensity-modulated radiation therapy (IMRT) treatment planning. The problem of IMRT treatment plan optimization is managed as a combined monolithic problem, where all beam fluence and angle parameters are treated equally during the optimization. To achieve this, PARETO is built around a powerful multi-objective evolutionary algorithm, called Ferret, which simultaneously optimizes multiple fitness functions that encode the attributes of the desired dose distribution for the PTV and OARs. The graphical interfaces within PARETO provide useful information such as: the convergence behavior during optimization, trade-off plots between the competing objectives, and a graphical representation of the optimal solution database allowing for the rapid exploration of treatment plan quality through the evaluation of dose-volume histograms and isodose distributions. PARETO was evaluated for two relatively complex clinical cases, a paranasal sinus and a pancreas case. The end result of each PARETO run was a database of optimal (non-dominated) treatment plans that demonstrated trade-offs between the OAR and PTV fitness functions, which were all equally good in the Pareto-optimal sense (where no one objective can be improved without worsening at least one other). Ferret was able to produce high quality solutions even though a large number of parameters

A linear bi-level multi-objective program for optimal allocation of water resources.

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Ijaz Ahmad

Full Text Available This paper presents a simple bi-level multi-objective linear program (BLMOLP with a hierarchical structure consisting of reservoir managers and several water use sectors under a multi-objective framework for the optimal allocation of limited water resources. Being the upper level decision makers (i.e., leader in the hierarchy, the reservoir managers control the water allocation system and tend to create a balance among the competing water users thereby maximizing the total benefits to the society. On the other hand, the competing water use sectors, being the lower level decision makers (i.e., followers in the hierarchy, aim only to maximize individual sectoral benefits. This multi-objective bi-level optimization problem can be solved using the simultaneous compromise constraint (SICCON technique which creates a compromise between upper and lower level decision makers (DMs, and transforms the multi-objective function into a single decision-making problem. The bi-level model developed in this study has been applied to the Swat River basin in Pakistan for the optimal allocation of water resources among competing water demand sectors and different scenarios have been developed. The application of the model in this study shows that the SICCON is a simple, applicable and feasible approach to solve the BLMOLP problem. Finally, the comparisons of the model results show that the optimization model is practical and efficient when it is applied to different conditions with priorities assigned to various water users.

Optimum analysis of pavement maintenance using multi-objective genetic algorithms

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Amr A. Elhadidy

2015-04-01

Full Text Available Road network expansion in Egypt is considered as a vital issue for the development of the country. This is done while upgrading current road networks to increase the safety and efficiency. A pavement management system (PMS is a set of tools or methods that assist decision makers in finding optimum strategies for providing and maintaining pavements in a serviceable condition over a given period of time. A multi-objective optimization problem for pavement maintenance and rehabilitation strategies on network level is discussed in this paper. A two-objective optimization model considers minimum action costs and maximum condition for used road network. In the proposed approach, Markov-chain models are used for predicting the performance of road pavement and to calculate the expected decline at different periods of time. A genetic-algorithm-based procedure is developed for solving the multi-objective optimization problem. The model searched for the optimum maintenance actions at adequate time to be implemented on an appropriate pavement. Based on the computing results, the Pareto optimal solutions of the two-objective optimization functions are obtained. From the optimal solutions represented by cost and condition, a decision maker can easily obtain the information of the maintenance and rehabilitation planning with minimum action costs and maximum condition. The developed model has been implemented on a network of roads and showed its ability to derive the optimal solution.

Multi-objective experimental design for (13)C-based metabolic flux analysis.

Science.gov (United States)

Bouvin, Jeroen; Cajot, Simon; D'Huys, Pieter-Jan; Ampofo-Asiama, Jerry; Anné, Jozef; Van Impe, Jan; Geeraerd, Annemie; Bernaerts, Kristel

2015-10-01

(13)C-based metabolic flux analysis is an excellent technique to resolve fluxes in the central carbon metabolism but costs can be significant when using specialized tracers. This work presents a framework for cost-effective design of (13)C-tracer experiments, illustrated on two different networks. Linear and non-linear optimal input mixtures are computed for networks for Streptomyces lividans and a carcinoma cell line. If only glucose tracers are considered as labeled substrate for a carcinoma cell line or S. lividans, the best parameter estimation accuracy is obtained by mixtures containing high amounts of 1,2-(13)C2 glucose combined with uniformly labeled glucose. Experimental designs are evaluated based on a linear (D-criterion) and non-linear approach (S-criterion). Both approaches generate almost the same input mixture, however, the linear approach is favored due to its low computational effort. The high amount of 1,2-(13)C2 glucose in the optimal designs coincides with a high experimental cost, which is further enhanced when labeling is introduced in glutamine and aspartate tracers. Multi-objective optimization gives the possibility to assess experimental quality and cost at the same time and can reveal excellent compromise experiments. For example, the combination of 100% 1,2-(13)C2 glucose with 100% position one labeled glutamine and the combination of 100% 1,2-(13)C2 glucose with 100% uniformly labeled glutamine perform equally well for the carcinoma cell line, but the first mixture offers a decrease in cost of $ 120 per ml-scale cell culture experiment. We demonstrated the validity of a multi-objective linear approach to perform optimal experimental designs for the non-linear problem of (13)C-metabolic flux analysis. Tools and a workflow are provided to perform multi-objective design. The effortless calculation of the D-criterion can be exploited to perform high-throughput screening of possible (13)C-tracers, while the illustrated benefit of multi-objective

Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control

Science.gov (United States)

Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.

2015-01-01

The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.

Analysis of process parameters in surface grinding using single objective Taguchi and multi-objective grey relational grade

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Prashant J. Patil

2016-09-01

Full Text Available Close tolerance and good surface finish are achieved by means of grinding process. This study was carried out for multi-objective optimization of MQL grinding process parameters. Water based Al2O3 and CuO nanofluids of various concentrations are used as lubricant for MQL system. Grinding experiments were carried out on instrumented surface grinding machine. For experimentation purpose Taguchi's method was used. Important process parameters that affect the G ratio and surface finish in MQL grinding are depth of cut, type of lubricant, feed rate, grinding wheel speed, coolant flow rate, and nanoparticle size. Grinding performance was calculated by the measurement G ratio and surface finish. For improvement of grinding process a multi-objective process parameter optimization is performed by use of Taguchi based grey relational analysis. To identify most significant factor of process analysis of variance (ANOVA has been used.

Multi-objective optimization of p-xylene oxidation process using an improved self-adaptive differential evolution algorithm

Institute of Scientific and Technical Information of China (English)

Lili Tao; Bin Xu; Zhihua Hu; Weimin Zhong

2017-01-01

The rise in the use of global polyester fiber contributed to strong demand of the Terephthalic acid (TPA). The liquid-phase catalytic oxidation of p-xylene (PX) to TPA is regarded as a critical and efficient chemical process in industry [1]. PX oxidation reaction involves many complex side reactions, among which acetic acid combustion and PX combustion are the most important. As the target product of this oxidation process, the quality and yield of TPA are of great concern. However, the improvement of the qualified product yield can bring about the high energy consumption, which means that the economic objectives of this process cannot be achieved simulta-neously because the two objectives are in conflict with each other. In this paper, an improved self-adaptive multi-objective differential evolution algorithm was proposed to handle the multi-objective optimization prob-lems. The immune concept is introduced to the self-adaptive multi-objective differential evolution algorithm (SADE) to strengthen the local search ability and optimization accuracy. The proposed algorithm is successfully tested on several benchmark test problems, and the performance measures such as convergence and divergence metrics are calculated. Subsequently, the multi-objective optimization of an industrial PX oxidation process is carried out using the proposed immune self-adaptive multi-objective differential evolution algorithm (ISADE). Optimization results indicate that application of ISADE can greatly improve the yield of TPA with low combustion loss without degenerating TA quality.

Dual-mode nested search method for categorical uncertain multi-objective optimization

Science.gov (United States)

Tang, Long; Wang, Hu

2016-10-01

Categorical multi-objective optimization is an important issue involved in many matching design problems. Non-numerical variables and their uncertainty are the major challenges of such optimizations. Therefore, this article proposes a dual-mode nested search (DMNS) method. In the outer layer, kriging metamodels are established using standard regular simplex mapping (SRSM) from categorical candidates to numerical values. Assisted by the metamodels, a k-cluster-based intelligent sampling strategy is developed to search Pareto frontier points. The inner layer uses an interval number method to model the uncertainty of categorical candidates. To improve the efficiency, a multi-feature convergent optimization via most-promising-area stochastic search (MFCOMPASS) is proposed to determine the bounds of objectives. Finally, typical numerical examples are employed to demonstrate the effectiveness of the proposed DMNS method.

Underlying topography extraction over forest areas from multi-baseline PolInSAR data

Science.gov (United States)

Fu, Haiqiang; Zhu, Jianjun; Wang, Changcheng; Li, Zhiwei

2017-11-01

In this paper, the digital elevation model (DEM) for a forest area is extracted from multi-baseline (MB) polarimetric interferometric synthetic aperture radar (PolInSAR) data. On the basis of the random-volume-over-ground (RVoG) model, the weighted complex least-squares adjustment (WCLSA) method is proposed for the ground phase estimation, so that the MB PolInSAR observations can be constrained by a generalized observation function and the observation contribution to the solution can be adjusted by a weighting strategy. A baseline length weighting strategy is then adopted to syncretize the DEMs estimated with the ground phases. The results of the simulated experiment undertaken in this study demonstrate that the WCLSA method is sensitive to the number of redundant observations and can adjust the contributions of the different observations. We also applied the WCLSA method to E-SAR L- and P-band MB PolInSAR data from the Krycklan River catchment in Northern Sweden. The results show that the two extracted DEMs are in close agreement with the Light Detection and Ranging (Lidar) DEM, with root-mean-square errors of 3.54 and 3.16 m. The DEM vertical error is correlated with the terrain slope and ground-cover condition, but not with the forest height.

Constrained multi-objective optimization of storage ring lattices

Science.gov (United States)

Husain, Riyasat; Ghodke, A. D.

2018-03-01

The storage ring lattice optimization is a class of constrained multi-objective optimization problem, where in addition to low beam emittance, a large dynamic aperture for good injection efficiency and improved beam lifetime are also desirable. The convergence and computation times are of great concern for the optimization algorithms, as various objectives are to be optimized and a number of accelerator parameters to be varied over a large span with several constraints. In this paper, a study of storage ring lattice optimization using differential evolution is presented. The optimization results are compared with two most widely used optimization techniques in accelerators-genetic algorithm and particle swarm optimization. It is found that the differential evolution produces a better Pareto optimal front in reasonable computation time between two conflicting objectives-beam emittance and dispersion function in the straight section. The differential evolution was used, extensively, for the optimization of linear and nonlinear lattices of Indus-2 for exploring various operational modes within the magnet power supply capabilities.

Multi-objective trajectory optimization of Space Manoeuvre Vehicle using adaptive differential evolution and modified game theory

Science.gov (United States)

Chai, Runqi; Savvaris, Al; Tsourdos, Antonios; Chai, Senchun

2017-07-01

Highly constrained trajectory optimization for Space Manoeuvre Vehicles (SMV) is a challenging problem. In practice, this problem becomes more difficult when multiple mission requirements are taken into account. Because of the nonlinearity in the dynamic model and even the objectives, it is usually hard for designers to generate a compromised trajectory without violating strict path and box constraints. In this paper, a new multi-objective SMV optimal control model is formulated and parameterized using combined shooting-collocation technique. A modified game theory approach, coupled with an adaptive differential evolution algorithm, is designed in order to generate the pareto front of the multi-objective trajectory optimization problem. In addition, to improve the quality of obtained solutions, a control logic is embedded in the framework of the proposed approach. Several existing multi-objective evolutionary algorithms are studied and compared with the proposed method. Simulation results indicate that without driving the solution out of the feasible region, the proposed method can perform better in terms of convergence ability and convergence speed than its counterparts. Moreover, the quality of the pareto set generated using the proposed method is higher than other multi-objective evolutionary algorithms, which means the newly proposed algorithm is more attractive for solving multi-criteria SMV trajectory planning problem.

Optimization of Fuel Consumption and Emissions for Auxiliary Power Unit Based on Multi-Objective Optimization Model

Directory of Open Access Journals (Sweden)

Yongpeng Shen

2016-02-01

Full Text Available Auxiliary power units (APUs are widely used for electric power generation in various types of electric vehicles, improvements in fuel economy and emissions of these vehicles directly depend on the operating point of the APUs. In order to balance the conflicting goals of fuel consumption and emissions reduction in the process of operating point choice, the APU operating point optimization problem is formulated as a constrained multi-objective optimization problem (CMOP firstly. The four competing objectives of this CMOP are fuel-electricity conversion cost, hydrocarbon (HC emissions, carbon monoxide (CO emissions and nitric oxide (NO x emissions. Then, the multi-objective particle swarm optimization (MOPSO algorithm and weighted metric decision making method are employed to solve the APU operating point multi-objective optimization model. Finally, bench experiments under New European driving cycle (NEDC, Federal test procedure (FTP and high way fuel economy test (HWFET driving cycles show that, compared with the results of the traditional fuel consumption single-objective optimization approach, the proposed multi-objective optimization approach shows significant improvements in emissions performance, at the expense of a slight drop in fuel efficiency.

Scheduling for the National Hockey League Using a Multi-objective Evolutionary Algorithm

Science.gov (United States)

Craig, Sam; While, Lyndon; Barone, Luigi

We describe a multi-objective evolutionary algorithm that derives schedules for the National Hockey League according to three objectives: minimising the teams' total travel, promoting equity in rest time between games, and minimising long streaks of home or away games. Experiments show that the system is able to derive schedules that beat the 2008-9 NHL schedule in all objectives simultaneously, and that it returns a set of schedules that offer a range of trade-offs across the objectives.

Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

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Syed Ali Abbas Kazmi

2017-02-01

Full Text Available Distribution networks (DNWs are facing numerous challenges, notably growing load demands, environmental concerns, operational constraints and expansion limitations with the current infrastructure. These challenges serve as a motivation factor for various distribution network planning (DP strategies, such as timely addressing load growth aiming at prominent objectives such as reliability, power quality, economic viability, system stability and deferring costly reinforcements. The continuous transformation of passive to active distribution networks (ADN needs to consider choices, primarily distributed generation (DG, network topology change, installation of new protection devices and key enablers as planning options in addition to traditional grid reinforcements. Since modern DP (MDP in deregulated market environments includes multiple stakeholders, primarily owners, regulators, operators and consumers, one solution fit for all planning scenarios may not satisfy all these stakeholders. Hence, this paper presents a review of several planning techniques (PTs based on mult-objective optimizations (MOOs in DNWs, aiming at better trade-off solutions among conflicting objectives and satisfying multiple stakeholders. The PTs in the paper spread across four distinct planning classifications including DG units as an alternative to costly reinforcements, capacitors and power electronic devices for ensuring power quality aspects, grid reinforcements, expansions, and upgrades as a separate category and network topology alteration and reconfiguration as a viable planning option. Several research works associated with multi-objective planning techniques (MOPT have been reviewed with relevant models, methods and achieved objectives, abiding with system constraints. The paper also provides a composite review of current research accounts and interdependence of associated components in the respective classifications. The potential future planning areas, aiming at

Inferring probabilistic stellar rotation periods using Gaussian processes

Science.gov (United States)

Angus, Ruth; Morton, Timothy; Aigrain, Suzanne; Foreman-Mackey, Daniel; Rajpaul, Vinesh

2018-02-01

Variability in the light curves of spotted, rotating stars is often non-sinusoidal and quasi-periodic - spots move on the stellar surface and have finite lifetimes, causing stellar flux variations to slowly shift in phase. A strictly periodic sinusoid therefore cannot accurately model a rotationally modulated stellar light curve. Physical models of stellar surfaces have many drawbacks preventing effective inference, such as highly degenerate or high-dimensional parameter spaces. In this work, we test an appropriate effective model: a Gaussian Process with a quasi-periodic covariance kernel function. This highly flexible model allows sampling of the posterior probability density function of the periodic parameter, marginalizing over the other kernel hyperparameters using a Markov Chain Monte Carlo approach. To test the effectiveness of this method, we infer rotation periods from 333 simulated stellar light curves, demonstrating that the Gaussian process method produces periods that are more accurate than both a sine-fitting periodogram and an autocorrelation function method. We also demonstrate that it works well on real data, by inferring rotation periods for 275 Kepler stars with previously measured periods. We provide a table of rotation periods for these and many more, altogether 1102 Kepler objects of interest, and their posterior probability density function samples. Because this method delivers posterior probability density functions, it will enable hierarchical studies involving stellar rotation, particularly those involving population modelling, such as inferring stellar ages, obliquities in exoplanet systems, or characterizing star-planet interactions. The code used to implement this method is available online.

Distributed Generation Planning using Peer Enhanced Multi-objective Teaching-Learning based Optimization in Distribution Networks

Science.gov (United States)

Selvam, Kayalvizhi; Vinod Kumar, D. M.; Siripuram, Ramakanth

2017-04-01

In this paper, an optimization technique called peer enhanced teaching learning based optimization (PeTLBO) algorithm is used in multi-objective problem domain. The PeTLBO algorithm is parameter less so it reduced the computational burden. The proposed peer enhanced multi-objective based TLBO (PeMOTLBO) algorithm has been utilized to find a set of non-dominated optimal solutions [distributed generation (DG) location and sizing in distribution network]. The objectives considered are: real power loss and the voltage deviation subjected to voltage limits and maximum penetration level of DG in distribution network. Since the DG considered is capable of injecting real and reactive power to the distribution network the power factor is considered as 0.85 lead. The proposed peer enhanced multi-objective optimization technique provides different trade-off solutions in order to find the best compromise solution a fuzzy set theory approach has been used. The effectiveness of this proposed PeMOTLBO is tested on IEEE 33-bus and Indian 85-bus distribution system. The performance is validated with Pareto fronts and two performance metrics (C-metric and S-metric) by comparing with robust multi-objective technique called non-dominated sorting genetic algorithm-II and also with the basic TLBO.

Short-term economic environmental hydrothermal scheduling using improved multi-objective gravitational search algorithm

International Nuclear Information System (INIS)

Li, Chunlong; Zhou, Jianzhong; Lu, Peng; Wang, Chao

2015-01-01

Highlights: • Improved multi-objective gravitational search algorithm. • An elite archive set is proposed to guide evolutionary process. • Neighborhood searching mechanism to improve local search ability. • Adopt chaotic mutation for avoiding premature convergence. • Propose feasible space method to handle hydro plant constrains. - Abstract: With growing concerns about energy and environment, short-term economic environmental hydrothermal scheduling (SEEHS) plays a more and more important role in power system. Because of the two objectives and various constraints, SEEHS is a complex multi-objective optimization problem (MOOP). In order to solve the problem, we propose an improved multi-objective gravitational search algorithm (IMOGSA) in this paper. In IMOGSA, the mass of the agent is redefined by multiple objectives to make it suitable for MOOP. An elite archive set is proposed to keep Pareto optimal solutions and guide evolutionary process. For balancing exploration and exploitation, a neighborhood searching mechanism is presented to cooperate with chaotic mutation. Moreover, a novel method based on feasible space is proposed to handle hydro plant constraints during SEEHS, and a violation adjustment method is adopted to handle power balance constraint. For verifying its effectiveness, the proposed IMOGSA is applied to a hydrothermal system in two different case studies. The simulation results show that IMOGSA has a competitive performance in SEEHS when compared with other established algorithms

Multi-objective optimization of coal-fired power plants using differential evolution

International Nuclear Information System (INIS)

Wang, Ligang; Yang, Yongping; Dong, Changqing; Morosuk, Tatiana; Tsatsaronis, George

2014-01-01

Highlights: • Multi-objective optimization of large-scale coal-fired power plants using differential evolution. • A newly-proposed algorithm for searching the fronts of decision space in a single run. • A reduction of cost of electricity by 2–4% with an optimal efficiency increase up to 2% points. • The uncertainty comes mainly from temperature- and reheat-related cost factors of steam generator. • An exergoeconomic analysis and comparison between optimal designs and one real industrial design. - Abstract: The design trade-offs between thermodynamics and economics for thermal systems can be studied with the aid of multi-objective optimization techniques. The investment costs usually increase with increasing thermodynamic performance of a system. In this paper, an enhanced differential evolution with diversity-preserving and density-adjusting mechanisms, and a newly-proposed algorithm for searching the decision space frontier in a single run were used, to conduct the multi-objective optimization of large-scale, supercritical coal-fired plants. The uncertainties associated with cost functions were discussed by analyzing the sensitivity of the decision space frontier to some significant parameters involved in cost functions. Comparisons made with the aid of an exergoeconomic analysis between the cost minimum designs and a real industrial design demonstrated how the plant improvement was achieved. It is concluded that the cost of electricity could be reduced by a 2–4%, whereas the efficiency could be increased by up to two percentage points. The largest uncertainty is introduced by the temperature-related and reheat-related cost coefficients of the steam generator. More reliable data on the price prediction of future advanced materials should be used to obtain more accurate fronts of the objective space

Multi-objective decision-making under uncertainty: Fuzzy logic methods

Science.gov (United States)

Hardy, Terry L.

1995-01-01

Fuzzy logic allows for quantitative representation of vague or fuzzy objectives, and therefore is well-suited for multi-objective decision-making. This paper presents methods employing fuzzy logic concepts to assist in the decision-making process. In addition, this paper describes software developed at NASA Lewis Research Center for assisting in the decision-making process. Two diverse examples are used to illustrate the use of fuzzy logic in choosing an alternative among many options and objectives. One example is the selection of a lunar lander ascent propulsion system, and the other example is the selection of an aeration system for improving the water quality of the Cuyahoga River in Cleveland, Ohio. The fuzzy logic techniques provided here are powerful tools which complement existing approaches, and therefore should be considered in future decision-making activities.

THE SPITZER SURVEY OF STELLAR STRUCTURE IN GALAXIES (S{sup 4}G): MULTI-COMPONENT DECOMPOSITION STRATEGIES AND DATA RELEASE

Energy Technology Data Exchange (ETDEWEB)

Salo, Heikki; Laurikainen, Eija; Laine, Jarkko; Comerón, Sebastien [Astronomy and Space Physics, University of Oulu, FI-90014 (Finland); Gadotti, Dimitri A.; Kim, Taehyun [European Southern Observatory, Casilla 19001, Santiago 19 (Chile); Buta, Ron [Department of Physics and Astronomy, University of Alabama, Box 870324, Tuscaloosa, AL 35487 (United States); Sheth, Kartik; Muñoz-Mateos, Juan Carlos [National Radio Astronomy Observatory/NAASC, 520 Edgemont Road, Charlottesville, VA 22903 (United States); Zaritsky, Dennis; Hinz, Joannah L. [University of Arizona, 933 N. Cherry Ave, Tucson, AZ 85721 (United States); Ho, Luis [Kavli Institute for Astronomy and Astrophysics, Peking University, Beijing 100871 (China); Knapen, Johan; Cisternas, Mauricio [Instituto de Astrofísica de Canarias, E-38205 La Laguna (Spain); Athanassoula, E.; Bosma, Albert [Aix Marseille Universite, CNRS, LAM (Laboratoire d’Astrophysique de Marseille) UMR 7326, F-13388, Marseille (France); Laine, Seppo [Spitzer Science Center—Caltech, MS 314-6, Pasadena, CA 91125 (United States); Regan, Michael [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); De Paz, Armando Gil [Departamento de Astrofísica, Universidad Complutense de Madrid, Madrid E-28040 (Spain); Menendez-Delmestre, Karin [Observatorio do Valongo, Universidade Federal de Rio de Janeiro, Ladeira Pedro Antonio, 43, Saude CEP 20080-090, Rio de Janeiro—RJ (Brazil); and others

2015-07-20

The Spitzer Survey of Stellar Structure in Galaxies (S{sup 4}G) is a deep 3.6 and 4.5 μm imaging survey of 2352 nearby (<40 Mpc) galaxies. We describe the S{sup 4}G data analysis pipeline 4, which is dedicated to two-dimensional structural surface brightness decompositions of 3.6 μm images, using GALFIT3.0. Besides automatic 1-component Sérsic fits, and 2-component Sérsic bulge + exponential disk fits, we present human-supervised multi-component decompositions, which include, when judged appropriate, a central point source, bulge, disk, and bar components. Comparison of the fitted parameters indicates that multi-component models are needed to obtain reliable estimates for the bulge Sérsic index and bulge-to-total light ratio (B/T), confirming earlier results. Here, we describe the preparations of input data done for decompositions, give examples of our decomposition strategy, and describe the data products released via IRSA and via our web page (www.oulu.fi/astronomy/S4G-PIPELINE4/MAIN). These products include all the input data and decomposition files in electronic form, making it easy to extend the decompositions to suit specific science purposes. We also provide our IDL-based visualization tools (GALFIDL) developed for displaying/running GALFIT-decompositions, as well as our mask editing procedure (MASK-EDIT) used in data preparation. A detailed analysis of the bulge, disk, and bar parameters derived from multi-component decompositions will be published separately.

NSGA-II algorithm for multi-objective generation expansion planning problem

Energy Technology Data Exchange (ETDEWEB)

Murugan, P.; Kannan, S. [Electronics and Communication Engineering Department, Arulmigu Kalasalingam College of Engineering, Krishnankoil 626190, Tamilnadu (India); Baskar, S. [Electrical Engineering Department, Thiagarajar College of Engineering, Madurai 625015, Tamilnadu (India)

2009-04-15

This paper presents an application of Elitist Non-dominated Sorting Genetic Algorithm version II (NSGA-II), to multi-objective generation expansion planning (GEP) problem. The GEP problem is considered as a two-objective problem. The first objective is the minimization of investment cost and the second objective is the minimization of outage cost (or maximization of reliability). To improve the performance of NSGA-II, two modifications are proposed. One modification is incorporation of Virtual Mapping Procedure (VMP), and the other is introduction of controlled elitism in NSGA-II. A synthetic test system having 5 types of candidate units is considered here for GEP for a 6-year planning horizon. The effectiveness of the proposed modifications is illustrated in detail. (author)

Comparative Study of Evolutionary Multi-objective Optimization Algorithms for a Non-linear Greenhouse Climate Control Problem

DEFF Research Database (Denmark)

Ghoreishi, Newsha; Sørensen, Jan Corfixen; Jørgensen, Bo Nørregaard

2015-01-01

Non-trivial real world decision-making processes usually involve multiple parties having potentially conflicting interests over a set of issues. State-of-the-art multi-objective evolutionary algorithms (MOEA) are well known to solve this class of complex real-world problems. In this paper, we...... compare the performance of state-of-the-art multi-objective evolutionary algorithms to solve a non-linear multi-objective multi-issue optimisation problem found in Greenhouse climate control. The chosen algorithms in the study includes NSGAII, eNSGAII, eMOEA, PAES, PESAII and SPEAII. The performance...... of all aforementioned algorithms is assessed and compared using performance indicators to evaluate proximity, diversity and consistency. Our insights to this comparative study enhanced our understanding of MOEAs performance in order to solve a non-linear complex climate control problem. The empirical...

Efficient solution of a multi objective fuzzy transportation problem

Science.gov (United States)

Vidhya, V.; Ganesan, K.

2018-04-01

In this paper we present a methodology for the solution of multi-objective fuzzy transportation problem when all the cost and time coefficients are trapezoidal fuzzy numbers and the supply and demand are crisp numbers. Using a new fuzzy arithmetic on parametric form of trapezoidal fuzzy numbers and a new ranking method all efficient solutions are obtained. The proposed method is illustrated with an example.

Energy thermal management in commercial bread-baking using a multi-objective optimisation framework

International Nuclear Information System (INIS)

Khatir, Zinedine; Taherkhani, A.R.; Paton, Joe; Thompson, Harvey; Kapur, Nik; Toropov, Vassili

2015-01-01

In response to increasing energy costs and legislative requirements energy efficient high-speed air impingement jet baking systems are now being developed. In this paper, a multi-objective optimisation framework for oven designs is presented which uses experimentally verified heat transfer correlations and high fidelity Computational Fluid Dynamics (CFD) analyses to identify optimal combinations of design features which maximise desirable characteristics such as temperature uniformity in the oven and overall energy efficiency of baking. A surrogate-assisted multi-objective optimisation framework is proposed and used to explore a range of practical oven designs, providing information on overall temperature uniformity within the oven together with ensuing energy usage and potential savings. - Highlights: • A multi-objective optimisation framework to design commercial ovens is presented. • High fidelity CFD embeds experimentally calibrated heat transfer inputs. • The optimum oven design minimises specific energy and bake time. • The Pareto front outlining the surrogate-assisted optimisation framework is built. • Optimisation of industrial bread-baking ovens reveals an energy saving of 637.6 GWh

A study of the LCA based biofuel supply chain multi-objective optimization model with multi-conversion paths in China

International Nuclear Information System (INIS)

Liu, Zhexuan; Qiu, Tong; Chen, Bingzhen

2014-01-01

Highlights: • A LCA based biofuel supply chain model considering 3E criteria was proposed. • The model was used to design a supply chain considering three conversion pathways. • An experimental biofuel supply chain for China was designed. • A Pareto-optimal solution surface of this multi-objective problem was obtained. • The designed supply chain was rather robust to price variation. - Abstract: In this paper we present a life cycle assessment (LCA) based biofuel supply chain model with multi-conversion pathways. This model was formulated as a mixed integer linear programming (MILP) problem which took economic, energy, and environmental criteria (3E) into consideration. The economic objective was measured by the total annual profit. The energy objective was measured by using the average fossil energy input per megajoule (MJ) of biofuel. The environmental objective was measured by greenhouse gas (GHG) emissions per MJ of biofuel. After carefully consideration of the current situation in China, we chose to examine three conversion pathways: bio-ethanol (BE), bio-methanol (BM) and bio-diesel (BD). LCA was integrated to a multi-objective supply chain model by dividing each pathway into several individual parts and analyzing each part. The multi-objective MILP problem was solved using a ε-constraint method by defining the total annual profit as the optimization objective and assigning the average fossil energy input per MJ biofuel and GHG emissions per MJ biofuel as constraints. This model was then used to design an experimental biofuel supply chain for China. A surface of the Pareto optimal solutions was obtained by linear interpolation of the non-inferior solutions. The optimal results included the choice of optimal conversion pathway, biomass type, biomass locations, facility locations, and network topology structure in the biofuel supply chain. Distributed and centralized systems were also factored into our experimental system design. In addition, the

A multi-objective optimization problem for multi-state series-parallel systems: A two-stage flow-shop manufacturing system

International Nuclear Information System (INIS)

Azadeh, A.; Maleki Shoja, B.; Ghanei, S.; Sheikhalishahi, M.

2015-01-01

This research investigates a redundancy-scheduling optimization problem for a multi-state series parallel system. The system is a flow shop manufacturing system with multi-state machines. Each manufacturing machine may have different performance rates including perfect performance, decreased performance and complete failure. Moreover, warm standby redundancy is considered for the redundancy allocation problem. Three objectives are considered for the problem: (1) minimizing system purchasing cost, (2) minimizing makespan, and (3) maximizing system reliability. Universal generating function is employed to evaluate system performance and overall reliability of the system. Since the problem is in the NP-hard class of combinatorial problems, genetic algorithm (GA) is used to find optimal/near optimal solutions. Different test problems are generated to evaluate the effectiveness and efficiency of proposed approach and compared to simulated annealing optimization method. The results show the proposed approach is capable of finding optimal/near optimal solution within a very reasonable time. - Highlights: • A redundancy-scheduling optimization problem for a multi-state series parallel system. • A flow shop with multi-state machines and warm standby redundancy. • Objectives are to optimize system purchasing cost, makespan and reliability. • Different test problems are generated and evaluated by a unique genetic algorithm. • It locates optimal/near optimal solution within a very reasonable time

Stellarator-Spheromak

International Nuclear Information System (INIS)

Moroz, P.E.

1997-03-01

A novel concept for magnetic plasma confinement, Stellarator-Spheromak (SSP), is proposed. Numerical analysis with the classical-stellarator-type outboard stellarator windings demonstrates a number of potential advantages of SSP for controlled nuclear fusion. Among the main ones are: simple and compact magnet coil configuration, absence of material structures (e.g. magnet coils or conducting walls) in the center of the torus, high rotational transform, and a possibility of MHD equilibria with very high β (pressure/magnetic pressure) of the confined plasma

Multi-objective Optimization of Process Parameters in Friction Stir Welding

DEFF Research Database (Denmark)

Tutum, Cem Celal; Hattel, Jesper Henri

The objective of this paper is to investigate optimum process parameters in Friction Stir Welding (FSW) to minimize residual stresses in the work piece and maximize production efficiency meanwhile satisfying process specific constraints as well. More specifically, the choices of tool rotational...... speed and traverse welding speed have been sought in order to achieve the goals mentioned above using an evolutionary multi-objective optimization (MOO) algorithm, i.e. non-dominated sorting genetic algorithm (NSGA-II), integrated with a transient, 2- dimensional sequentially coupled thermo...

Localized probability of improvement for kriging based multi-objective optimization

Science.gov (United States)

Li, Yinjiang; Xiao, Song; Barba, Paolo Di; Rotaru, Mihai; Sykulski, Jan K.

2017-12-01

The paper introduces a new approach to kriging based multi-objective optimization by utilizing a local probability of improvement as the infill sampling criterion and the nearest neighbor check to ensure diversification and uniform distribution of Pareto fronts. The proposed method is computationally fast and linearly scalable to higher dimensions.

Technology of solving multi-objective problems of control of systems with distributed parameters

Science.gov (United States)

Rapoport, E. Ya.; Pleshivtseva, Yu. E.

2017-07-01

A constructive technology of multi-objective optimization of control of distributed parameter plants is proposed. The technology is based on a single-criterion version in the form of the minimax convolution of normalized performance criteria. The approach under development is based on the transition to an equivalent form of the variational problem with constraints, with the problem solution being a priori Pareto-effective. Further procedures of preliminary parameterization of control actions and subsequent reduction to a special problem of semi-infinite programming make it possible to find the sought extremals with the use of their Chebyshev properties and fundamental laws of the subject domain. An example of multi-objective optimization of operation modes of an engineering thermophysics object is presented, which is of independent interest.

Enhanced Multi-Objective Optimization of Groundwater Monitoring Networks

DEFF Research Database (Denmark)

Bode, Felix; Binning, Philip John; Nowak, Wolfgang

Drinking-water well catchments include many sources for potential contaminations like gas stations or agriculture. Finding optimal positions of monitoring wells for such purposes is challenging because there are various parameters (and their uncertainties) that influence the reliability...... and optimality of any suggested monitoring location or monitoring network. The goal of this project is to develop and establish a concept to assess, design, and optimize early-warning systems within well catchments. Such optimal monitoring networks need to optimize three competing objectives: (1) a high...... be reduced to a minimum. The method is based on numerical simulation of flow and transport in heterogeneous porous media coupled with geostatistics and Monte-Carlo, wrapped up within the framework of formal multi-objective optimization. In order to gain insight into the flow and transport physics...

Feature Selection using Multi-objective Genetic Algorith m: A Hybrid Approach

OpenAIRE

Ahuja, Jyoti; GJUST - Guru Jambheshwar University of Sciecne and Technology; Ratnoo, Saroj Dahiya; GJUST - Guru Jambheshwar University of Sciecne and Technology

2015-01-01

Feature selection is an important pre-processing task for building accurate and comprehensible classification models. Several researchers have applied filter, wrapper or hybrid approaches using genetic algorithms which are good candidates for optimization problems that involve large search spaces like in the case of feature selection. Moreover, feature selection is an inherently multi-objective problem with many competing objectives involving size, predictive power and redundancy of the featu...

Thermodynamic design of Stirling engine using multi-objective particle swarm optimization algorithm

International Nuclear Information System (INIS)

Duan, Chen; Wang, Xinggang; Shu, Shuiming; Jing, Changwei; Chang, Huawei

2014-01-01

Highlights: • An improved thermodynamic model taking into account irreversibility parameter was developed. • A multi-objective optimization method for designing Stirling engine was investigated. • Multi-objective particle swarm optimization algorithm was adopted in the area of Stirling engine for the first time. - Abstract: In the recent years, the interest in Stirling engine has remarkably increased due to its ability to use any heat source from outside including solar energy, fossil fuels and biomass. A large number of studies have been done on Stirling cycle analysis. In the present study, a mathematical model based on thermodynamic analysis of Stirling engine considering regenerative losses and internal irreversibilities has been developed. Power output, thermal efficiency and the cycle irreversibility parameter of Stirling engine are optimized simultaneously using Particle Swarm Optimization (PSO) algorithm, which is more effective than traditional genetic algorithms. In this optimization problem, some important parameters of Stirling engine are considered as decision variables, such as temperatures of the working fluid both in the high temperature isothermal process and in the low temperature isothermal process, dead volume ratios of each heat exchanger, volumes of each working spaces, effectiveness of the regenerator, and the system charge pressure. The Pareto optimal frontier is obtained and the final design solution has been selected by Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP). Results show that the proposed multi-objective optimization approach can significantly outperform traditional single objective approaches

Multi-objective optimal strategy for generating and bidding in the power market

International Nuclear Information System (INIS)

Peng Chunhua; Sun Huijuan; Guo Jianfeng; Liu Gang

2012-01-01

Highlights: ► A new benefit/risk/emission comprehensive generation optimization model is established. ► A hybrid multi-objective differential evolution optimization algorithm is designed. ► Fuzzy set theory and entropy weighting method are employed to extract the general best solution. ► The proposed approach of generating and bidding is efficient for maximizing profit and minimizing both risk and emissions. - Abstract: Based on the coordinated interaction between units output and electricity market prices, the benefit/risk/emission comprehensive generation optimization model with objectives of maximal profit and minimal bidding risk and emissions is established. A hybrid multi-objective differential evolution optimization algorithm, which successfully integrates Pareto non-dominated sorting with differential evolution algorithm and improves individual crowding distance mechanism and mutation strategy to avoid premature and unevenly search, is designed to achieve Pareto optimal set of this model. Moreover, fuzzy set theory and entropy weighting method are employed to extract one of the Pareto optimal solutions as the general best solution. Several optimization runs have been carried out on different cases of generation bidding and scheduling. The results confirm the potential and effectiveness of the proposed approach in solving the multi-objective optimization problem of generation bidding and scheduling. In addition, the comparison with the classical optimization algorithms demonstrates the superiorities of the proposed algorithm such as integrality of Pareto front, well-distributed Pareto-optimal solutions, high search speed.

Multi-objective superstructure-free synthesis and optimization of thermal power plants

International Nuclear Information System (INIS)

Wang, Ligang; Lampe, Matthias; Voll, Philip; Yang, Yongping; Bardow, André

2016-01-01

The merits of superstructure-free synthesis are demonstrated for bi-objective design of thermal power plants. The design of thermal power plants is complex and thus best solved by optimization. Common optimization methods require specification of a superstructure which becomes a tedious and error-prone task for complex systems. Superstructure specification is avoided by the presented superstructure-free approach, which is shown to successfully solve the design task yielding a high-quality Pareto front of promising structural alternatives. The economic objective function avoids introducing infinite numbers of units (e.g., turbine, reheater and feedwater preheater) as favored by pure thermodynamic optimization. The number of feasible solutions found per number of mutation tries is still high even after many generations but declines after introducing highly-nonlinear cost functions leading to challenging MINLP problems. The identified Pareto-optimal solutions tend to employ more units than found in modern power plants indicating the need for cost functions to reflect current industrial practice. In summary, the multi-objective superstructure-free synthesis framework is a robust approach for very complex problems in the synthesis of thermal power plants. - Highlights: • A generalized multi-objective superstructure-free synthesis framework for thermal power plants is presented. • The superstructure-free synthesis framework is comprehensively evaluated by complex bi-objective synthesis problems. • The proposed framework is effective to explore the structural design space even for complex problems.

Multi-Objective Particle Swarm Optimization Approach for Cost-Based Feature Selection in Classification.

Science.gov (United States)

Zhang, Yong; Gong, Dun-Wei; Cheng, Jian

2017-01-01

Feature selection is an important data-preprocessing technique in classification problems such as bioinformatics and signal processing. Generally, there are some situations where a user is interested in not only maximizing the classification performance but also minimizing the cost that may be associated with features. This kind of problem is called cost-based feature selection. However, most existing feature selection approaches treat this task as a single-objective optimization problem. This paper presents the first study of multi-objective particle swarm optimization (PSO) for cost-based feature selection problems. The task of this paper is to generate a Pareto front of nondominated solutions, that is, feature subsets, to meet different requirements of decision-makers in real-world applications. In order to enhance the search capability of the proposed algorithm, a probability-based encoding technology and an effective hybrid operator, together with the ideas of the crowding distance, the external archive, and the Pareto domination relationship, are applied to PSO. The proposed PSO-based multi-objective feature selection algorithm is compared with several multi-objective feature selection algorithms on five benchmark datasets. Experimental results show that the proposed algorithm can automatically evolve a set of nondominated solutions, and it is a highly competitive feature selection method for solving cost-based feature selection problems.

A Pareto-based multi-objective optimization algorithm to design energy-efficient shading devices

International Nuclear Information System (INIS)

Khoroshiltseva, Marina; Slanzi, Debora; Poli, Irene

2016-01-01

Highlights: • We present a multi-objective optimization algorithm for shading design. • We combine Harmony search and Pareto-based procedures. • Thermal and daylighting performances of external shading were considered. • We applied the optimization process to a residential social housing in Madrid. - Abstract: In this paper we address the problem of designing new energy-efficient static daylight devices that will surround the external windows of a residential building in Madrid. Shading devices can in fact largely influence solar gains in a building and improve thermal and lighting comforts by selectively intercepting the solar radiation and by reducing the undesirable glare. A proper shading device can therefore significantly increase the thermal performance of a building by reducing its energy demand in different climate conditions. In order to identify the set of optimal shading devices that allow a low energy consumption of the dwelling while maintaining high levels of thermal and lighting comfort for the inhabitants we derive a multi-objective optimization methodology based on Harmony Search and Pareto front approaches. The results show that the multi-objective approach here proposed is an effective procedure in designing energy efficient shading devices when a large set of conflicting objectives characterizes the performance of the proposed solutions.

Pareto-Optimal Multi-objective Inversion of Geophysical Data

Science.gov (United States)

Schnaidt, Sebastian; Conway, Dennis; Krieger, Lars; Heinson, Graham

2018-01-01

In the process of modelling geophysical properties, jointly inverting different data sets can greatly improve model results, provided that the data sets are compatible, i.e., sensitive to similar features. Such a joint inversion requires a relationship between the different data sets, which can either be analytic or structural. Classically, the joint problem is expressed as a scalar objective function that combines the misfit functions of multiple data sets and a joint term which accounts for the assumed connection between the data sets. This approach suffers from two major disadvantages: first, it can be difficult to assess the compatibility of the data sets and second, the aggregation of misfit terms introduces a weighting of the data sets. We present a pareto-optimal multi-objective joint inversion approach based on an existing genetic algorithm. The algorithm treats each data set as a separate objective, avoiding forced weighting and generating curves of the trade-off between the different objectives. These curves are analysed by their shape and evolution to evaluate data set compatibility. Furthermore, the statistical analysis of the generated solution population provides valuable estimates of model uncertainty.

USING CLOSE WHITE DWARF + M DWARF STELLAR PAIRS TO CONSTRAIN THE FLARE RATES IN CLOSE STELLAR BINARIES

Energy Technology Data Exchange (ETDEWEB)

Morgan, Dylan P.; West, Andrew A. [Astronomy Department, Boston University, 725 Commonwealth Ave, Boston, MA 02215 (United States); Becker, Andrew C., E-mail: dpmorg@bu.edu [Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195 (United States)

2016-05-01

We present a study of the statistical flare rates of M dwarfs (dMs) with close white dwarf (WD) companions (WD+dM; typical separations <1 au). Our previous analysis demonstrated that dMs with close WD companions are more magnetically active than their field counterparts. One likely implication of having a close binary companion is increased stellar rotation through disk-disruption, tidal effects, and/or angular momentum exchange; increased stellar rotation has long been associated with an increase in stellar activity. Previous studies show a strong correlation between dMs that are magnetically active (showing H α in emission) and the frequency of stellar flare rates. We examine the difference between the flare rates observed in close WD+dM binary systems and field dMs. Our sample consists of a subset of 181 close WD+dM pairs from Morgan et al. observed in the Sloan Digital Sky Survey Stripe 82, where we obtain multi-epoch observations in the Sloan ugriz -bands. We find an increase in the overall flaring fraction in the close WD+dM pairs (0.09 ± 0.03%) compared to the field dMs (0.0108 ± 0.0007%) and a lower flaring fraction for active WD+dMs (0.05 ± 0.03%) compared to active dMs (0.28 ± 0.05%). We discuss how our results constrain both the single and binary dM flare rates. Our results also constrain dM multiplicity, our knowledge of the Galactic transient background, and may be important for the habitability of attending planets around dMs with close companions.

Multi-objective reliability optimization of series-parallel systems with a choice of redundancy strategies

International Nuclear Information System (INIS)

Safari, Jalal

2012-01-01

This paper proposes a variant of the Non-dominated Sorting Genetic Algorithm (NSGA-II) to solve a novel mathematical model for multi-objective redundancy allocation problems (MORAP). Most researchers about redundancy allocation problem (RAP) have focused on single objective optimization, while there has been some limited research which addresses multi-objective optimization. Also all mathematical multi-objective models of general RAP assume that the type of redundancy strategy for each subsystem is predetermined and known a priori. In general, active redundancy has traditionally received greater attention; however, in practice both active and cold-standby redundancies may be used within a particular system design. The choice of redundancy strategy then becomes an additional decision variable. Thus, the proposed model and solution method are to select the best redundancy strategy, type of components, and levels of redundancy for each subsystem that maximizes the system reliability and minimize total system cost under system-level constraints. This problem belongs to the NP-hard class. This paper presents a second-generation Multiple-Objective Evolutionary Algorithm (MOEA), named NSGA-II to find the best solution for the given problem. The proposed algorithm demonstrates the ability to identify a set of optimal solutions (Pareto front), which provides the Decision Maker (DM) with a complete picture of the optimal solution space. After finding the Pareto front, a procedure is used to select the best solution from the Pareto front. Finally, the advantages of the presented multi-objective model and of the proposed algorithm are illustrated by solving test problems taken from the literature and the robustness of the proposed NSGA-II is discussed.

Image de-noising based on mathematical morphology and multi-objective particle swarm optimization

Science.gov (United States)

Dou, Liyun; Xu, Dan; Chen, Hao; Liu, Yicheng

2017-07-01

To overcome the problem of image de-noising, an efficient image de-noising approach based on mathematical morphology and multi-objective particle swarm optimization (MOPSO) is proposed in this paper. Firstly, constructing a series and parallel compound morphology filter based on open-close (OC) operation and selecting a structural element with different sizes try best to eliminate all noise in a series link. Then, combining multi-objective particle swarm optimization (MOPSO) to solve the parameters setting of multiple structural element. Simulation result shows that our algorithm can achieve a superior performance compared with some traditional de-noising algorithm.

Multi-objective optimization of water quality, pumps operation, and storage sizing of water distribution systems.

Science.gov (United States)

Kurek, Wojciech; Ostfeld, Avi

2013-01-30

A multi-objective methodology utilizing the Strength Pareto Evolutionary Algorithm (SPEA2) linked to EPANET for trading-off pumping costs, water quality, and tanks sizing of water distribution systems is developed and demonstrated. The model integrates variable speed pumps for modeling the pumps operation, two water quality objectives (one based on chlorine disinfectant concentrations and one on water age), and tanks sizing cost which are assumed to vary with location and diameter. The water distribution system is subject to extended period simulations, variable energy tariffs, Kirchhoff's laws 1 and 2 for continuity of flow and pressure, tanks water level closure constraints, and storage-reliability requirements. EPANET Example 3 is employed for demonstrating the methodology on two multi-objective models, which differ in the imposed water quality objective (i.e., either with disinfectant or water age considerations). Three-fold Pareto optimal fronts are presented. Sensitivity analysis on the storage-reliability constraint, its influence on pumping cost, water quality, and tank sizing are explored. The contribution of this study is in tailoring design (tank sizing), pumps operational costs, water quality of two types, and reliability through residual storage requirements, in a single multi-objective framework. The model was found to be stable in generating multi-objective three-fold Pareto fronts, while producing explainable engineering outcomes. The model can be used as a decision tool for both pumps operation, water quality, required storage for reliability considerations, and tank sizing decision-making. Copyright © 2012 Elsevier Ltd. All rights reserved.

Young Stellar Variability of GM Cephei by Circumstellar Dust Clumps

Science.gov (United States)

Huang, Po-Chieh; Chen, Wen-Ping; Hu, Chia-Ling; Burkhonov, Otabek; Ehgamberdiev, Shuhrat; Liu, Jinzhong; Naito, Hiroyuki; Pakstiene, Erika; Qvam, Jan Kare Trandem; Rätz, Stefanie; Semkov, Evgeni

2018-04-01

UX Orionis stars are a sub-type of Herbig Ae/be or T Tauri stars exhibiting sporadic extinction of stellar light due to circumstellar dust obscuration. GM Cep is such an UX Orionis star in the young (∼ 4 Myr) open cluster Trumpler 37 at ∼ 900 pc, showing a prominent infrared access, H-alpha emission, and flare activity. Our multi-color photometric monitoring from 2009 to 2016 showed (i) sporadic brightening on a time scale of days due to young stellar accretion, (ii) cyclic, but not strictly periodical, occultation events, each lasting for a couple months, with a probable recurrence time of about two years, (iii) normal dust reddening as the star became redder when dimmer, (iv) the unusual "blueing" phenomena near the brightness minima, during which the star appeared bluer when dimmer, and (v) a noticeable polarization, from 3 to 9 percent in g', r', and i' -bands. The occultation events may be caused by dust clumps, signifying the density inhomogeneity in a young stellar disk from grain coagulation to planetesimal formation. The level of polarization was anti-correlated with the brightness in the bright state, when the dust clump backscattered stellar light. We discussed two potential hypotheses: orbiting dust clumps versus dust clumps along a spiral arm structure.

A long baseline global stereo matching based upon short baseline estimation

Science.gov (United States)

Li, Jing; Zhao, Hong; Li, Zigang; Gu, Feifei; Zhao, Zixin; Ma, Yueyang; Fang, Meiqi

2018-05-01

In global stereo vision, balancing the matching efficiency and computing accuracy seems to be impossible because they contradict each other. In the case of a long baseline, this contradiction becomes more prominent. In order to solve this difficult problem, this paper proposes a novel idea to improve both the efficiency and accuracy in global stereo matching for a long baseline. In this way, the reference images located between the long baseline image pairs are firstly chosen to form the new image pairs with short baselines. The relationship between the disparities of pixels in the image pairs with different baselines is revealed by considering the quantized error so that the disparity search range under the long baseline can be reduced by guidance of the short baseline to gain matching efficiency. Then, the novel idea is integrated into the graph cuts (GCs) to form a multi-step GC algorithm based on the short baseline estimation, by which the disparity map under the long baseline can be calculated iteratively on the basis of the previous matching. Furthermore, the image information from the pixels that are non-occluded under the short baseline but are occluded for the long baseline can be employed to improve the matching accuracy. Although the time complexity of the proposed method depends on the locations of the chosen reference images, it is usually much lower for a long baseline stereo matching than when using the traditional GC algorithm. Finally, the validity of the proposed method is examined by experiments based on benchmark datasets. The results show that the proposed method is superior to the traditional GC method in terms of efficiency and accuracy, and thus it is suitable for long baseline stereo matching.

A Unified Algorithm for Channel Imbalance and Antenna Phase Center Position Calibration of a Single-Pass Multi-Baseline TomoSAR System

Directory of Open Access Journals (Sweden)

Yuncheng Bu

2018-03-01

Full Text Available The multi-baseline synthetic aperture radar (SAR tomography (TomoSAR system is employed in such applications as disaster remote sensing, urban 3-D reconstruction, and forest carbon storage estimation. This is because of its 3-D imaging capability in a single-pass platform. However, a high 3-D resolution of TomoSAR is based on the premise that the channel imbalance and antenna phase center (APC position are precisely known. If this is not the case, the 3-D resolution performance will be seriously degraded. In this paper, a unified algorithm for channel imbalance and APC position calibration of a single-pass multi-baseline TomoSAR system is proposed. Based on the maximum likelihood method, as well as the least squares and the damped Newton method, we can calibrate the channel imbalance and APC position. The algorithm is suitable for near-field conditions, and no phase unwrapping operation is required. The effectiveness of the proposed algorithm has been verified by simulation and experimental results.

Multi-period multi-objective electricity generation expansion planning problem with Monte-Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Tekiner, Hatice [Industrial Engineering, College of Engineering and Natural Sciences, Istanbul Sehir University, 2 Ahmet Bayman Rd, Istanbul (Turkey); Coit, David W. [Department of Industrial and Systems Engineering, Rutgers University, 96 Frelinghuysen Rd., Piscataway, NJ (United States); Felder, Frank A. [Edward J. Bloustein School of Planning and Public Policy, Rutgers University, Piscataway, NJ (United States)

2010-12-15

A new approach to the electricity generation expansion problem is proposed to minimize simultaneously multiple objectives, such as cost and air emissions, including CO{sub 2} and NO{sub x}, over a long term planning horizon. In this problem, system expansion decisions are made to select the type of power generation, such as coal, nuclear, wind, etc., where the new generation asset should be located, and at which time period expansion should take place. We are able to find a Pareto front for the multi-objective generation expansion planning problem that explicitly considers availability of the system components over the planning horizon and operational dispatching decisions. Monte-Carlo simulation is used to generate numerous scenarios based on the component availabilities and anticipated demand for energy. The problem is then formulated as a mixed integer linear program, and optimal solutions are found based on the simulated scenarios with a combined objective function considering the multiple problem objectives. The different objectives are combined using dimensionless weights and a Pareto front can be determined by varying these weights. The mathematical model is demonstrated on an example problem with interesting results indicating how expansion decisions vary depending on whether minimizing cost or minimizing greenhouse gas emissions or pollutants is given higher priority. (author)

Multi-Objective Optimization Considering Battery Degradation for a Multi-Mode Power-Split Electric Vehicle

Directory of Open Access Journals (Sweden)

Xuerui Ma

2017-07-01

Full Text Available A multi-mode power-split (MMPS hybrid electric vehicle (HEV has two planetary gearsets and clutches/grounds which results in several operation modes with enhanced electric drive capability and better fuel economy. Basically, the battery storage system is involved in different operation modes to satisfy the power demand and minimize the fuel consumption, whereas the complicated operation modes with frequent charging/discharging will absolutely influence the battery life because of degradation. In this paper, firstly, we introduce the solid electrolyte interface (SEI film growth model based on the previous study of the battery degradation principles and was verified according to the test data. We consider both the fuel economy and battery degradation as a multi-objective problem for MMPS HEV by normalization with a weighting factor. An instantaneous optimization is implemented based on the equivalent fuel consumption concept. Then the control strategy is implemented on a simulation framework integrating the MMPS powertrain model and the SEI film growth map model over some typical driving cycles, such as New European Driving Cycle (NEDC and Urban Dynamometer Driving Schedule (UDDS. Finally, the result demonstrates that these two objectives are conflicting and the trade-off reduces the battery degradation with fuel sacrifice. Additionally, the analysis reveals how the mode selection will reflect the battery degradation.

Multi-Objective Sensitivity Analyses for Power Generation Mix: Malaysia Case Study

OpenAIRE

Siti Mariam Mohd Shokri; Nofri Yenita Dahlan; Hasmaini Mohamad

2017-01-01

This paper presents an optimization framework to determine long-term optimal generation mix for Malaysia Power Sector using Dynamic Programming (DP) technique. Several new candidate units with a pre-defined MW capacity were included in the model for generation expansion planning from coal, natural gas, hydro and renewable energy (RE). Four objective cases were considered, 1) economic cost, 2) environmental, 3) reliability and 4) multi-objectives that combining the three cases. Results show th...

Multi-objective optimization and exergetic-sustainability of an irreversible nano scale Braysson cycle operating with Ma

Directory of Open Access Journals (Sweden)

Mohammad H. Ahmadi

2016-06-01

Full Text Available Nano technology is developed in this decade and changes the way of life. Moreover, developing nano technology has effect on the performance of the materials and consequently improves the efficiency and robustness of them. So, nano scale thermal cycles will be probably engaged in the near future. In this paper, a nano scale irreversible Braysson cycle is studied thermodynamically for optimizing the performance of the Braysson cycle. In the aforementioned cycle an ideal Maxwell–Boltzmann gas is used as a working fluid. Furthermore, three different plans are used for optimizing with multi-objectives; though, the outputs of the abovementioned plans are assessed autonomously. Throughout the first plan, with the purpose of maximizing the ecological coefficient of performance and energy efficiency of the system, multi-objective optimization algorithms are used. Furthermore, in the second plan, two objective functions containing the ecological coefficient of performance and the dimensionless Maximum available work are maximized synchronously by utilizing multi-objective optimization approach. Finally, throughout the third plan, three objective functions involving the dimensionless Maximum available work, the ecological coefficient of performance and energy efficiency of the system are maximized synchronously by utilizing multi-objective optimization approach. The multi-objective evolutionary approach based on the non-dominated sorting genetic algorithm approach is used in this research. Making a decision is performed by three different decision makers comprising linear programming approaches for multidimensional analysis of preference and an approach for order of preference by comparison with ideal answer and Bellman–Zadeh. Lastly, analysis of error is employed to determine deviation of the outcomes gained from each plan.

Design of homo-organic acid producing strains using multi-objective optimization

DEFF Research Database (Denmark)

Kim, Tae Yong; Park, Jong Myoung; Kim, Hyun Uk

2015-01-01

Production of homo-organic acids without byproducts is an important challenge in bioprocess engineering to minimize operation cost for separation processes. In this study, we used multi-objective optimization to design Escherichia coli strains with the goals of maximally producing target organic ...

Fuzzy preference based interactive fuzzy physical programming and its application in multi-objective optimization

International Nuclear Information System (INIS)

Zhang, Xu; Huang, Hong Zhong; Yu, Lanfeng

2006-01-01

Interactive Fuzzy Physical Programming (IFPP) developed in this paper is a new efficient multi-objective optimization method, which retains the advantages of physical programming while considering the fuzziness of the designer's preferences. The fuzzy preference function is introduced based on the model of linear physical programming, which is used to guide the search for improved solutions by interactive decision analysis. The example of multi-objective optimization design of the spindle of internal grinder demonstrates that the improved preference conforms to the subjective desires of the designer

Multi objective optimization of line pack management of gas pipeline system

International Nuclear Information System (INIS)

Chebouba, A

2015-01-01

This paper addresses the Line Pack Management of the ''GZ1 Hassi R'mell-Arzew'' gas pipeline. For a gas pipeline system, the decision-making on the gas line pack management scenarios usually involves a delicate balance between minimization of the fuel consumption in the compression stations and maximizing gas line pack. In order to select an acceptable Line Pack Management of Gas Pipeline scenario from these two angles for ''GZ1 Hassi R'mell- Arzew'' gas pipeline, the idea of multi-objective decision-making has been introduced. The first step in developing this approach is the derivation of a numerical method to analyze the flow through the pipeline under transient isothermal conditions. In this paper, the solver NSGA-II of the modeFRONTIER, coupled with a matlab program was used for solving the multi-objective problem

ABSENCE OF SIGNIFICANT COOL DISKS IN YOUNG STELLAR OBJECTS EXHIBITING REPETITIVE OPTICAL OUTBURSTS

Energy Technology Data Exchange (ETDEWEB)

Liu, Hauyu Baobab; Hirano, Naomi; Takami, Michihiro; Dong, Ruobing [Academia Sinica Institute of Astronomy and Astrophysics, P.O. Box 23-141, Taipei 106, Taiwan (China); Galván-Madrid, Roberto; Rodríguez, Luis F.; Carrasco-González, Carlos [Instituto de Radioastronomía y Astrofísica, UNAM, A.P. 3-72, Xangari, Morelia, 58089 (Mexico); Vorobyov, Eduard I. [Department of Astrophysics, University of Vienna, Tuerkenschanzstrasse 17, A-1180, Vienna (Austria); Kóspál, Ágnes [Konkoly Observatory, Research Centre for Astronomy and Earth Sciences, Hungarian Academy of Sciences, P.O. Box 67, 1525 Budapest (Hungary); Dunham, Michael M. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, MS 78, Cambridge, MA 02138 (United States); Henning, Thomas [Max-Planck-Institut für Astronomie Königstuhl, 17 D-69117 Heidelberg (Germany); Hashimoto, Jun [National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588 Japan (Japan); Hasegawa, Yasuhiro, E-mail: baobabyoo@gmail.com [Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109 (United States)

2016-01-10

We report Submillimeter Array 1.3 mm high angular resolution observations toward the four EXor-type outbursting young stellar objects VY Tau, V1118 Ori, V1143 Ori, and NY Ori. The data mostly show low dust masses M{sub dust} in the associated circumstellar disks. Among the sources, NY Ori possesses a relatively massive disk with M{sub dust} ∼ 9 × 10{sup −4}M{sub ⊙}. V1118 Ori has a marginal detection equivalent to M{sub dust} ∼ 6 × 10{sup −5}M{sub ⊙}. V1143 Ori has a non-detection also equivalent to M{sub dust} < 6 × 10{sup −5}M{sub ⊙}. For the nearest source, VY Tau, we get a surprising non-detection that provides a stringent upper limit M{sub dust} < 6 × 10{sup −6}M{sub ⊙}. We interpret our findings as suggesting that the gas and dust reservoirs that feed the short-duration, repetitive optical outbursts seen in some EXors may be limited to the small-scale, innermost region of their circumstellar disks. This hot dust may have escaped our detection limits. Follow-up, more sensitive millimeter observations are needed to improve our understanding of the triggering mechanisms of EXor-type outbursts.

YOUNG STELLAR OBJECTS IN THE LARGE MAGELLANIC CLOUD STAR-FORMING REGION N206

International Nuclear Information System (INIS)

Romita, Krista Alexandra; Meixner, M.; Sewilo, M.; Shiao, B.; Carlson, Lynn Redding; Whitney, B.; Babler, B.; Meade, M.; Indebetouw, R.; Hora, J. L.

2010-01-01

We present analysis of the energetic star-forming region Henize 206 (N206) located near the southern edge of the Large Magellanic Cloud (LMC) based on photometric data from the Spitzer Surveying the Agents of Galaxy Evolution (SAGE-LMC; IRAC 3.6, 4.5, 5.8, 8.0 μm and MIPS 24 μm), Infrared Survey Facility near-infrared survey (J, H, K s ), and the Magellanic Clouds Photometric Survey (MCPS UBVI) covering a wavelength range of 0.36-24 μm. Young stellar object (YSO) candidates are identified based upon their location in infrared color-magnitude space and classified by the shapes of their spectral energy distributions in comparison with a pre-computed grid of YSO models. We identify 116 YSO candidates: 102 are well characterized by the YSO models, predominately Stage I, and 14 may be multiple sources or young sources with transition disks. Careful examination of the individual sources and their surrounding environment allows us to identify a factor of ∼14.5 more YSO candidates than have already been identified. The total mass of these well-fit YSO candidates is ∼520 M sun . We calculate a current star formation rate of 0.27 x 10 -1 M sun yr -1 kpc -2 . The distribution of YSO candidates appears to follow shells of neutral material in the interstellar medium.

Multi-Objective Bidding Strategy for Genco Using Non-Dominated Sorting Particle Swarm Optimization

Science.gov (United States)

Saksinchai, Apinat; Boonchuay, Chanwit; Ongsakul, Weerakorn

2010-06-01

This paper proposes a multi-objective bidding strategy for a generation company (GenCo) in uniform price spot market using non-dominated sorting particle swarm optimization (NSPSO). Instead of using a tradeoff technique, NSPSO is introduced to solve the multi-objective strategic bidding problem considering expected profit maximization and risk (profit variation) minimization. Monte Carlo simulation is employed to simulate rivals' bidding behavior. Test results indicate that the proposed approach can provide the efficient non-dominated solution front effectively. In addition, it can be used as a decision making tool for a GenCo compromising between expected profit and price risk in spot market.

STELLAR ATMOSPHERES, ATMOSPHERIC EXTENSION, AND FUNDAMENTAL PARAMETERS: WEIGHING STARS USING THE STELLAR MASS INDEX

Energy Technology Data Exchange (ETDEWEB)

Neilson, Hilding R.; Lester, John B. [Department of Astronomy and Astrophysics, University of Toronto, 50 St. George Street, Toronto, ON, M5S 3H4 (Canada); Baron, Fabien; Norris, Ryan; Kloppenborg, Brian, E-mail: neilson@astro.utoronto.ca [Center for High Angular Resolution Astronomy, Department of Physics and Astronomy, Georgia State University, P.O. Box 5060, Atlanta, GA 30302-5060 (United States)

2016-10-20

One of the great challenges of understanding stars is measuring their masses. The best methods for measuring stellar masses include binary interaction, asteroseismology, and stellar evolution models, but these methods are not ideal for red giant and supergiant stars. In this work, we propose a novel method for inferring stellar masses of evolved red giant and supergiant stars using interferometric and spectrophotometric observations combined with spherical model stellar atmospheres to measure what we call the stellar mass index, defined as the ratio between the stellar radius and mass. The method is based on the correlation between different measurements of angular diameter, used as a proxy for atmospheric extension, and fundamental stellar parameters. For a given star, spectrophotometry measures the Rosseland angular diameter while interferometric observations generally probe a larger limb-darkened angular diameter. The ratio of these two angular diameters is proportional to the relative extension of the stellar atmosphere, which is strongly correlated to the star’s effective temperature, radius, and mass. We show that these correlations are strong and can lead to precise measurements of stellar masses.

Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm

Directory of Open Access Journals (Sweden)

M. Balasubbareddy

2015-12-01

Full Text Available A novel optimization algorithm is proposed to solve single and multi-objective optimization problems with generation fuel cost, emission, and total power losses as objectives. The proposed method is a hybridization of the conventional cuckoo search algorithm and arithmetic crossover operations. Thus, the non-linear, non-convex objective function can be solved under practical constraints. The effectiveness of the proposed algorithm is analyzed for various cases to illustrate the effect of practical constraints on the objectives' optimization. Two and three objective multi-objective optimization problems are formulated and solved using the proposed non-dominated sorting-based hybrid cuckoo search algorithm. The effectiveness of the proposed method in confining the Pareto front solutions in the solution region is analyzed. The results for single and multi-objective optimization problems are physically interpreted on standard test functions as well as the IEEE-30 bus test system with supporting numerical and graphical results and also validated against existing methods.

The fundamentals of stellar astrophysics

International Nuclear Information System (INIS)

Collins, G.W. II.

1989-01-01

A broad overview of theoretical stellar astrophysics is presented in a textbook intended for graduate students. Chapters are devoted to fundamental principles, assumptions, theorems, and polytropes; energy sources and sinks; the flow of energy through the star and the construction of stellar models; the theory of stellar evolution; relativistic stellar structure; the structure of distorted stars; stellar pulsation and oscillation. Also discussed are the flow of radiation through the stellar atmosphere, the solution of the radiative-transfer equation, the environment of the radiation field, the construction of a stellar model atmosphere, the formation and shape of spectral lines, LTE breakdown, illuminated and extended stellar atmospheres, and the transfer of polarized radiation. Diagrams, graphs, and sample problems are provided. 164 refs

Loading pattern optimization by multi-objective simulated annealing with screening technique

International Nuclear Information System (INIS)

Tong, K. P.; Hyun, C. L.; Hyung, K. J.; Chang, H. K.

2006-01-01

This paper presents a new multi-objective function which is made up of the main objective term as well as penalty terms related to the constraints. All the terms are represented in the same functional form and the coefficient of each term is normalized so that each term has equal weighting in the subsequent simulated annealing optimization calculations. The screening technique introduced in the previous work is also adopted in order to save computer time in 3-D neutronics evaluation of trial loading patterns. For numerical test of the new multi-objective function in the loading pattern optimization, the optimum loading patterns for the initial and the cycle 7 reload PWR core of Yonggwang Unit 4 are calculated by the simulated annealing algorithm with screening technique. A total of 10 optimum loading patterns are obtained for the initial core through 10 independent simulated annealing optimization runs. For the cycle 7 reload core one optimum loading pattern has been obtained from a single simulated annealing optimization run. More SA optimization runs will be conducted to optimum loading patterns for the cycle 7 reload core and results will be presented in the further work. (authors)

Multi-objective optimization in systematic conservation planning and the representation of genetic variability among populations.

Science.gov (United States)

Schlottfeldt, S; Walter, M E M T; Carvalho, A C P L F; Soares, T N; Telles, M P C; Loyola, R D; Diniz-Filho, J A F

2015-06-18

Biodiversity crises have led scientists to develop strategies for achieving conservation goals. The underlying principle of these strategies lies in systematic conservation planning (SCP), in which there are at least 2 conflicting objectives, making it a good candidate for multi-objective optimization. Although SCP is typically applied at the species level (or hierarchically higher), it can be used at lower hierarchical levels, such as using alleles as basic units for analysis, for conservation genetics. Here, we propose a method of SCP using a multi-objective approach. We used non-dominated sorting genetic algorithm II in order to identify the smallest set of local populations of Dipteryx alata (baru) (a Brazilian Cerrado species) for conservation, representing the known genetic diversity and using allele frequency information associated with heterozygosity and Hardy-Weinberg equilibrium. We worked in 3 variations for the problem. First, we reproduced a previous experiment, but using a multi-objective approach. We found that the smallest set of populations needed to represent all alleles under study was 7, corroborating the results of the previous study, but with more distinct solutions. In the 2nd and 3rd variations, we performed simultaneous optimization of 4 and 5 objectives, respectively. We found similar but refined results for 7 populations, and a larger portfolio considering intra-specific diversity and persistence with populations ranging from 8-22. This is the first study to apply multi-objective algorithms to an SCP problem using alleles at the population level as basic units for analysis.

Multi-objective optimization of an underwater compressed air energy storage system using genetic algorithm

International Nuclear Information System (INIS)

Cheung, Brian C.; Carriveau, Rupp; Ting, David S.K.

2014-01-01

This paper presents the findings from a multi-objective genetic algorithm optimization study on the design parameters of an underwater compressed air energy storage system (UWCAES). A 4 MWh UWCAES system was numerically simulated and its energy, exergy, and exergoeconomics were analysed. Optimal system configurations were determined that maximized the UWCAES system round-trip efficiency and operating profit, and minimized the cost rate of exergy destruction and capital expenditures. The optimal solutions obtained from the multi-objective optimization model formed a Pareto-optimal front, and a single preferred solution was selected using the pseudo-weight vector multi-criteria decision making approach. A sensitivity analysis was performed on interest rates to gauge its impact on preferred system designs. Results showed similar preferred system designs for all interest rates in the studied range. The round-trip efficiency and operating profit of the preferred system designs were approximately 68.5% and $53.5/cycle, respectively. The cost rate of the system increased with interest rates. - Highlights: • UWCAES system configurations were developed using multi-objective optimization. • System was optimized for energy efficiency, exergy, and exergoeconomics • Pareto-optimal solution surfaces were developed at different interest rates. • Similar preferred system configurations were found at all interest rates studied

Multi-objective PID Optimization for Speed Control of an Isolated Steam Turbine using Gentic Algorithm

OpenAIRE

Sanjay Kr. Singh; D. Boolchandani; S.G. Modani; Nitish Katal

2014-01-01

This study focuses on multi-objective optimization of the PID controllers for optimal speed control for an isolated steam turbine. In complex operations, optimal tuning plays an imperative role in maintaining the product quality and process safety. This study focuses on the comparison of the optimal PID tuning using Multi-objective Genetic Algorithm (NSGA-II) against normal genetic algorithm and Ziegler Nichols methods for the speed control of an isolated steam turbine. Isolated steam turbine...

MULTI-OBJECTIVE OPTIMISATION OF LASER CUTTING USING CUCKOO SEARCH ALGORITHM

Directory of Open Access Journals (Sweden)

M. MADIĆ

2015-03-01

Full Text Available Determining of optimal laser cutting conditions for improving cut quality characteristics is of great importance in process planning. This paper presents multi-objective optimisation of the CO2 laser cutting process considering three cut quality characteristics such as surface roughness, heat affected zone (HAZ and kerf width. It combines an experimental design by using Taguchi’s method, modelling the relationships between the laser cutting factors (laser power, cutting speed, assist gas pressure and focus position and cut quality characteristics by artificial neural networks (ANNs, formulation of the multiobjective optimisation problem using weighting sum method, and solving it by the novel meta-heuristic cuckoo search algorithm (CSA. The objective is to obtain optimal cutting conditions dependent on the importance order of the cut quality characteristics for each of four different case studies presented in this paper. The case studies considered in this study are: minimisation of cut quality characteristics with equal priority, minimisation of cut quality characteristics with priority given to surface roughness, minimisation of cut quality characteristics with priority given to HAZ, and minimisation of cut quality characteristics with priority given to kerf width. The results indicate that the applied CSA for solving the multi-objective optimisation problem is effective, and that the proposed approach can be used for selecting the optimal laser cutting factors for specific production requirements.

Multi-objective generation scheduling with hybrid energy resources

Science.gov (United States)

Trivedi, Manas

In economic dispatch (ED) of electric power generation, the committed generating units are scheduled to meet the load demand at minimum operating cost with satisfying all unit and system equality and inequality constraints. Generation of electricity from the fossil fuel releases several contaminants into the atmosphere. So the economic dispatch objective can no longer be considered alone due to the environmental concerns that arise from the emissions produced by fossil fueled electric power plants. This research is proposing the concept of environmental/economic generation scheduling with traditional and renewable energy sources. Environmental/economic dispatch (EED) is a multi-objective problem with conflicting objectives since emission minimization is conflicting with fuel cost minimization. Production and consumption of fossil fuel and nuclear energy are closely related to environmental degradation. This causes negative effects to human health and the quality of life. Depletion of the fossil fuel resources will also be challenging for the presently employed energy systems to cope with future energy requirements. On the other hand, renewable energy sources such as hydro and wind are abundant, inexhaustible and widely available. These sources use native resources and have the capacity to meet the present and the future energy demands of the world with almost nil emissions of air pollutants and greenhouse gases. The costs of fossil fuel and renewable energy are also heading in opposite directions. The economic policies needed to support the widespread and sustainable markets for renewable energy sources are rapidly evolving. The contribution of this research centers on solving the economic dispatch problem of a system with hybrid energy resources under environmental restrictions. It suggests an effective solution of renewable energy to the existing fossil fueled and nuclear electric utilities for the cheaper and cleaner production of electricity with hourly

A new multi-objective optimization model for preventive maintenance and replacement scheduling of multi-component systems

Science.gov (United States)

Moghaddam, Kamran S.; Usher, John S.

2011-07-01

In this article, a new multi-objective optimization model is developed to determine the optimal preventive maintenance and replacement schedules in a repairable and maintainable multi-component system. In this model, the planning horizon is divided into discrete and equally-sized periods in which three possible actions must be planned for each component, namely maintenance, replacement, or do nothing. The objective is to determine a plan of actions for each component in the system while minimizing the total cost and maximizing overall system reliability simultaneously over the planning horizon. Because of the complexity, combinatorial and highly nonlinear structure of the mathematical model, two metaheuristic solution methods, generational genetic algorithm, and a simulated annealing are applied to tackle the problem. The Pareto optimal solutions that provide good tradeoffs between the total cost and the overall reliability of the system can be obtained by the solution approach. Such a modeling approach should be useful for maintenance planners and engineers tasked with the problem of developing recommended maintenance plans for complex systems of components.

"Slit Mask Design for the Giant Magellan Telescope Multi-object Astronomical and Cosmological Spectrograph"

Science.gov (United States)

Williams, Darius; Marshall, Jennifer L.; Schmidt, Luke M.; Prochaska, Travis; DePoy, Darren L.

2018-01-01

The Giant Magellan Telescope Multi-object Astronomical and Cosmological Spectrograph (GMACS) is currently in development for the Giant Magellan Telescope (GMT). GMACS will employ slit masks with a usable diameter of approximately 0.450 m for the purpose of multi-slit spectroscopy. Of significant importance are the design constraints and parameters of the multi-object slit masks themselves as well as the means for mapping astronomical targets to physical mask locations. Analytical methods are utilized to quantify deformation effects on a potential slit mask due to thermal expansion and vignetting of target light cones. Finite element analysis (FEA) is utilized to simulate mask flexure in changing gravity vectors. The alpha version of the mask creation program for GMACS, GMACS Mask Simulator (GMS), a derivative of the OSMOS Mask Simulator (OMS), is introduced.

Processing Technology Selection for Municipal Sewage Treatment Based on a Multi-Objective Decision Model under Uncertainty.

Science.gov (United States)

Chen, Xudong; Xu, Zhongwen; Yao, Liming; Ma, Ning

2018-03-05

This study considers the two factors of environmental protection and economic benefits to address municipal sewage treatment. Based on considerations regarding the sewage treatment plant construction site, processing technology, capital investment, operation costs, water pollutant emissions, water quality and other indicators, we establish a general multi-objective decision model for optimizing municipal sewage treatment plant construction. Using the construction of a sewage treatment plant in a suburb of Chengdu as an example, this paper tests the general model of multi-objective decision-making for the sewage treatment plant construction by implementing a genetic algorithm. The results show the applicability and effectiveness of the multi-objective decision model for the sewage treatment plant. This paper provides decision and technical support for the optimization of municipal sewage treatment.

An Improved Multi-Objective Artificial Bee Colony Optimization Algorithm with Regulation Operators

Directory of Open Access Journals (Sweden)

Jiuyuan Huo

2017-02-01

Full Text Available To achieve effective and accurate optimization for multi-objective optimization problems, a multi-objective artificial bee colony algorithm with regulation operators (RMOABC inspired by the intelligent foraging behavior of honey bees was proposed in this paper. The proposed algorithm utilizes the Pareto dominance theory and takes advantage of adaptive grid and regulation operator mechanisms. The adaptive grid technique is used to adaptively assess the Pareto front maintained in an external archive and the regulation operator is used to balance the weights of the local search and the global search in the evolution of the algorithm. The performance of RMOABC was evaluated in comparison with other nature inspired algorithms includes NSGA-II and MOEA/D. The experiments results demonstrated that the RMOABC approach has better accuracy and minimal execution time.

A multi-objective chaotic particle swarm optimization for environmental/economic dispatch

International Nuclear Information System (INIS)

Cai Jiejin; Ma Xiaoqian; Li Qiong; Li Lixiang; Peng Haipeng

2009-01-01

A multi-objective chaotic particle swarm optimization (MOCPSO) method has been developed to solve the environmental/economic dipatch (EED) problems considering both economic and environmental issues. The proposed MOCPSO method has been applied in two test power systems. Compared with the conventional multi-objective particle swarm optimization (MOPSO) method, for the compromising minimum fuel cost and emission case, the fuel cost and pollutant emission obtained from MOCPSO method can be reduced about 50.08 $/h and 2.95 kg/h, respectively, in test system 1, about 0.02 $/h and 1.11 kg/h, respectively, in test system 2. The MOCPSO method also results in higher quality solutions for the minimum fuel cost case and the minimum emission case in both of the test power systems. Hence, MOCPSO method can result in great environmental and economic effects. For EED problems, the MOCPSO method is more feasible and more effective alternative approach than the conventional MOPSO method.

Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach

International Nuclear Information System (INIS)

Wei, F.; Wu, Q.H.; Jing, Z.X.; Chen, J.J.; Zhou, X.X.

2016-01-01

This paper proposes a comprehensive framework including a multi-objective interval optimization model and evidential reasoning (ER) approach to solve the unit sizing problem of small-scale integrated energy systems, with uncertain wind and solar energies integrated. In the multi-objective interval optimization model, interval variables are introduced to tackle the uncertainties of the optimization problem. Aiming at simultaneously considering the cost and risk of a business investment, the average and deviation of life cycle cost (LCC) of the integrated energy system are formulated. In order to solve the problem, a novel multi-objective optimization algorithm, MGSOACC (multi-objective group search optimizer with adaptive covariance matrix and chaotic search), is developed, employing adaptive covariance matrix to make the search strategy adaptive and applying chaotic search to maintain the diversity of group. Furthermore, ER approach is applied to deal with multiple interests of an investor at the business decision making stage and to determine the final unit sizing solution from the Pareto-optimal solutions. This paper reports on the simulation results obtained using a small-scale direct district heating system (DH) and a small-scale district heating and cooling system (DHC) optimized by the proposed framework. The results demonstrate the superiority of the multi-objective interval optimization model and ER approach in tackling the unit sizing problem of integrated energy systems considering the integration of uncertian wind and solar energies. - Highlights: • Cost and risk of investment in small-scale integrated energy systems are considered. • A multi-objective interval optimization model is presented. • A novel multi-objective optimization algorithm (MGSOACC) is proposed. • The evidential reasoning (ER) approach is used to obtain the final optimal solution. • The MGSOACC and ER can tackle the unit sizing problem efficiently.

Initiative Optimization Operation Strategy and Multi-objective Energy Management Method for Combined Cooling Heating and Power

Institute of Scientific and Technical Information of China (English)

Feng Zhao; Chenghui Zhang; Bo Sun

2016-01-01

This paper proposed an initiative optimization operation strategy and multi-objective energy management method for combined cooling heating and power(CCHP) with storage systems.Initially,the initiative optimization operation strategy of CCHP system in the cooling season,the heating season and the transition season was formulated.The energy management of CCHP system was optimized by the multi-objective optimization model with maximum daily energy efficiency,minimum daily carbon emissions and minimum daily operation cost based on the proposed initiative optimization operation strategy.Furthermore,the pareto optimal solution set was solved by using the niche particle swarm multi-objective optimization algorithm.Ultimately,the most satisfactory energy management scheme was obtained by using the technique for order preference by similarity to ideal solution(TOPSIS) method.A case study of CCHP system used in a hospital in the north of China validated the effectiveness of this method.The results showed that the satisfactory energy management scheme of CCHP system was obtained based on this initiative optimization operation strategy and multi-objective energy management method.The CCHP system has achieved better energy efficiency,environmental protection and economic benefits.

Single-objective vs. multi-objective autocalibration in modelling total suspended solids and phosphorus in a small agricultural watershed with SWAT.

Science.gov (United States)

Rasolomanana, Santatriniaina Denise; Lessard, Paul; Vanrolleghem, Peter A

2012-01-01

To obtain greater precision in modelling small agricultural watersheds, a shorter simulation time step is beneficial. A daily time step better represents the dynamics of pollutants in the river and provides more realistic simulation results. However, with a daily evaluation performance, good fits are rarely obtained. With the Shuffled Complex Evolution (SCE) method embedded in the Soil and Water Assessment Tool (SWAT), two calibration approaches are available, single-objective or multi-objective optimization. The goal of the present study is to evaluate which approach can improve the daily performance with SWAT, in modelling flow (Q), total suspended solids (TSS) and total phosphorus (TP). The influence of weights assigned to the different variables included in the objective function has also been tested. The results showed that: (i) the model performance depends not only on the choice of calibration approach, but essentially on the influential parameters; (ii) the multi-objective calibration estimating at once all parameters related to all measured variables is the best approach to model Q, TSS and TP; (iii) changing weights does not improve model performance; and (iv) with a single-objective optimization, an excellent water quality modelling performance may hide a loss of performance of predicting flows and unbalanced internal model components.

A probabilistic multi objective CLSC model with Genetic algorithm-ε_Constraint approach

Directory of Open Access Journals (Sweden)

Alireza TaheriMoghadam

2014-05-01

Full Text Available In this paper an uncertain multi objective closed-loop supply chain is developed. The first objective function is maximizing the total profit. The second objective function is minimizing the use of row materials. In the other word, the second objective function is maximizing the amount of remanufacturing and recycling. Genetic algorithm is used for optimization and for finding the pareto optimal line, Epsilon-constraint method is used. Finally a numerical example is solved with proposed approach and performance of the model is evaluated in different sizes. The results show that this approach is effective and useful for managerial decisions.

Multi-objective optimization design method of radiation shielding

International Nuclear Information System (INIS)

Yang Shouhai; Wang Weijin; Lu Daogang; Chen Yixue

2012-01-01

Due to the shielding design goals of diversification and uncertain process of many factors, it is necessary to develop an optimization design method of intelligent shielding by which the shielding scheme selection will be achieved automatically and the uncertainties of human impact will be reduced. For economical feasibility to achieve a radiation shielding design for automation, the multi-objective genetic algorithm optimization of screening code which combines the genetic algorithm and discrete-ordinate method was developed to minimize the costs, size, weight, and so on. This work has some practical significance for gaining the optimization design of shielding. (authors)

Multi-objective optimization of GENIE Earth system models.

Science.gov (United States)

Price, Andrew R; Myerscough, Richard J; Voutchkov, Ivan I; Marsh, Robert; Cox, Simon J

2009-07-13

The tuning of parameters in climate models is essential to provide reliable long-term forecasts of Earth system behaviour. We apply a multi-objective optimization algorithm to the problem of parameter estimation in climate models. This optimization process involves the iterative evaluation of response surface models (RSMs), followed by the execution of multiple Earth system simulations. These computations require an infrastructure that provides high-performance computing for building and searching the RSMs and high-throughput computing for the concurrent evaluation of a large number of models. Grid computing technology is therefore essential to make this algorithm practical for members of the GENIE project.

Multi-objective optimization problems concepts and self-adaptive parameters with mathematical and engineering applications

CERN Document Server

Lobato, Fran Sérgio

2017-01-01

This book is aimed at undergraduate and graduate students in applied mathematics or computer science, as a tool for solving real-world design problems. The present work covers fundamentals in multi-objective optimization and applications in mathematical and engineering system design using a new optimization strategy, namely the Self-Adaptive Multi-objective Optimization Differential Evolution (SA-MODE) algorithm. This strategy is proposed in order to reduce the number of evaluations of the objective function through dynamic update of canonical Differential Evolution parameters (population size, crossover probability and perturbation rate). The methodology is applied to solve mathematical functions considering test cases from the literature and various engineering systems design, such as cantilevered beam design, biochemical reactor, crystallization process, machine tool spindle design, rotary dryer design, among others.

Thermo-economic and environmental analyses based multi-objective optimization of vapor compression–absorption cascaded refrigeration system using NSGA-II technique

International Nuclear Information System (INIS)

Jain, Vaibhav; Sachdeva, Gulshan; Kachhwaha, Surendra Singh; Patel, Bhavesh

2016-01-01

Highlights: • It addresses multi-objective optimization study on cascaded refrigeration system. • Cascaded system is a promising decarburizing and energy efficient technology. • NSGA-II technique is used for multi-objective optimization. • Total annual product cost and irreversibility rate are simultaneously optimized. - Abstract: Present work optimizes the performance of 170 kW vapor compression–absorption cascaded refrigeration system (VCACRS) based on combined thermodynamic, economic and environmental parameters using Non-dominated Sort Genetic Algorithm-II (NSGA-II) technique. Two objective functions including the total irreversibility rate (as a thermodynamic criterion) and the total product cost (as an economic criterion) of the system are considered simultaneously for multi-objective optimization of VCACRS. The capital and maintenance costs of the system components, the operational cost, and the penalty cost due to CO_2 emission are included in the total product cost of the system. Three optimized systems including a single-objective thermodynamic optimized, a single-objective economic optimized and a multi-objective optimized are analyzed and compared. The results showed that the multi-objective design considers the combined thermodynamic and total product cost criteria better than the two individual single-objective thermodynamic and total product cost optimized designs.

THE RELATION BETWEEN STAR FORMATION RATE AND STELLAR MASS FOR GALAXIES AT 3.5 ≤ z ≤ 6.5 IN CANDELS

International Nuclear Information System (INIS)

Salmon, Brett; Papovich, Casey; Tilvi, Vithal; Finkelstein, Steven L.; Finlator, Kristian; Behroozi, Peter; Lu, Yu; Wechsler, Risa H.; Dahlen, Tomas; Ferguson, Henry C.; Davé, Romeel; Dekel, Avishai; Dickinson, Mark; Giavalisco, Mauro; Long, James; Mobasher, Bahram; Reddy, Naveen; Somerville, Rachel S.

2015-01-01

Distant star-forming galaxies show a correlation between their star formation rates (SFRs) and stellar masses, and this has deep implications for galaxy formation. Here, we present a study on the evolution of the slope and scatter of the SFR-stellar mass relation for galaxies at 3.5 ≤ z ≤ 6.5 using multi-wavelength photometry in GOODS-S from the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) and Spitzer Extended Deep Survey. We describe an updated, Bayesian spectral-energy distribution fitting method that incorporates effects of nebular line emission, star formation histories that are constant or rising with time, and different dust-attenuation prescriptions (starburst and Small Magellanic Cloud). From z = 6.5 to z = 3.5 star-forming galaxies in CANDELS follow a nearly unevolving correlation between stellar mass and SFR that follows SFR ∼ M ⋆ a with a =0.54 ± 0.16 at z ∼ 6 and 0.70 ± 0.21 at z ∼ 4. This evolution requires a star formation history that increases with decreasing redshift (on average, the SFRs of individual galaxies rise with time). The observed scatter in the SFR-stellar mass relation is tight, σ(log SFR/M ☉ yr –1 ) < 0.3-0.4 dex, for galaxies with log M * /M ☉ > 9 dex. Assuming that the SFR is tied to the net gas inflow rate (SFR ∼ M-dot gas ), then the scatter in the gas inflow rate is also smaller than 0.3–0.4 dex for star-forming galaxies in these stellar mass and redshift ranges, at least when averaged over the timescale of star formation. We further show that the implied star formation history of objects selected on the basis of their co-moving number densities is consistent with the evolution in the SFR-stellar mass relation

Evolution of binaries with compact objects in globular clusters

OpenAIRE

Ivanova, Natalia

2017-01-01

Dynamical interactions that take place between objects in dense stellar systems lead to frequent formation of exotic stellar objects, unusual binaries, and systems of higher multiplicity. They are most important for the formation of binaries with neutron stars and black holes, which are usually observationally revealed in mass-transferring binaries. Here we review the current understanding of compact object's retention, of the metallicity dependence on the formation of low-mass X-ray binaries...

A multi-objective approach to improve SWAT model calibration in alpine catchments

Science.gov (United States)

Tuo, Ye; Marcolini, Giorgia; Disse, Markus; Chiogna, Gabriele

2018-04-01

Multi-objective hydrological model calibration can represent a valuable solution to reduce model equifinality and parameter uncertainty. The Soil and Water Assessment Tool (SWAT) model is widely applied to investigate water quality and water management issues in alpine catchments. However, the model calibration is generally based on discharge records only, and most of the previous studies have defined a unique set of snow parameters for an entire basin. Only a few studies have considered snow observations to validate model results or have taken into account the possible variability of snow parameters for different subbasins. This work presents and compares three possible calibration approaches. The first two procedures are single-objective calibration procedures, for which all parameters of the SWAT model were calibrated according to river discharge alone. Procedures I and II differ from each other by the assumption used to define snow parameters: The first approach assigned a unique set of snow parameters to the entire basin, whereas the second approach assigned different subbasin-specific sets of snow parameters to each subbasin. The third procedure is a multi-objective calibration, in which we considered snow water equivalent (SWE) information at two different spatial scales (i.e. subbasin and elevation band), in addition to discharge measurements. We tested these approaches in the Upper Adige river basin where a dense network of snow depth measurement stations is available. Only the set of parameters obtained with this multi-objective procedure provided an acceptable prediction of both river discharge and SWE. These findings offer the large community of SWAT users a strategy to improve SWAT modeling in alpine catchments.

Probing the Dusty Stellar Populations of the Local Volume Galaxies with JWST /MIRI

Energy Technology Data Exchange (ETDEWEB)

Jones, Olivia C.; Meixner, Margaret [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD, 21218 (United States); Justtanont, Kay [Department of Earth and Space Sciences, Chalmers University of Technology, Onsala Space Observatory, SE-439 92 Onsala (Sweden); Glasse, Alistair [UK Astronomy Technology Centre, Royal Observatory, Edinburgh, Blackford Hill, Edinburgh EH9 3HJ (United Kingdom)

2017-05-20

The Mid-Infrared Instrument (MIRI) for the James Webb Space Telescope ( JWST ) will revolutionize our understanding of infrared stellar populations in the Local Volume. Using the rich Spitzer -IRS spectroscopic data set and spectral classifications from the Surveying the Agents of Galaxy Evolution (SAGE)–Spectroscopic survey of more than 1000 objects in the Magellanic Clouds, the Grid of Red Supergiant and Asymptotic Giant Branch Star Model (grams), and the grid of YSO models by Robitaille et al., we calculate the expected flux densities and colors in the MIRI broadband filters for prominent infrared stellar populations. We use these fluxes to explore the JWST /MIRI colors and magnitudes for composite stellar population studies of Local Volume galaxies. MIRI color classification schemes are presented; these diagrams provide a powerful means of identifying young stellar objects, evolved stars, and extragalactic background galaxies in Local Volume galaxies with a high degree of confidence. Finally, we examine which filter combinations are best for selecting populations of sources based on their JWST colors.

A multi-objective framework to predict flows of ungauged rivers within regions of sparse hydrometeorologic observation

Science.gov (United States)

Alipour, M.; Kibler, K. M.

2017-12-01

Despite advances in flow prediction, managers of ungauged rivers located within broad regions of sparse hydrometeorologic observation still lack prescriptive methods robust to the data challenges of such regions. We propose a multi-objective streamflow prediction framework for regions of minimum observation to select models that balance runoff efficiency with choice of accurate parameter values. We supplement sparse observed data with uncertain or low-resolution information incorporated as `soft' a priori parameter estimates. The performance of the proposed framework is tested against traditional single-objective and constrained single-objective calibrations in two catchments in a remote area of southwestern China. We find that the multi-objective approach performs well with respect to runoff efficiency in both catchments (NSE = 0.74 and 0.72), within the range of efficiencies returned by other models (NSE = 0.67 - 0.78). However, soil moisture capacity estimated by the multi-objective model resonates with a priori estimates (parameter residuals of 61 cm versus 289 and 518 cm for maximum soil moisture capacity in one catchment, and 20 cm versus 246 and 475 cm in the other; parameter residuals of 0.48 versus 0.65 and 0.7 for soil moisture distribution shape factor in one catchment, and 0.91 versus 0.79 and 1.24 in the other). Thus, optimization to a multi-criteria objective function led to very different representations of soil moisture capacity as compared to models selected by single-objective calibration, without compromising runoff efficiency. These different soil moisture representations may translate into considerably different hydrological behaviors. The proposed approach thus offers a preliminary step towards greater process understanding in regions of severe data limitations. For instance, the multi-objective framework may be an adept tool to discern between models of similar efficiency to select models that provide the "right answers for the right reasons

Multi-Objective Sustainable Operation of the Three Gorges Cascaded Hydropower System Using Multi-Swarm Comprehensive Learning Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Xiang Yu

2016-06-01

Full Text Available Optimal operation of hydropower reservoir systems often needs to optimize multiple conflicting objectives simultaneously. The conflicting objectives result in a Pareto front, which is a set of non-dominated solutions. Non-dominated solutions cannot outperform each other on all the objectives. An optimization framework based on the multi-swarm comprehensive learning particle swarm optimization algorithm is proposed to solve the multi-objective operation of hydropower reservoir systems. Through adopting search techniques such as decomposition, mutation and differential evolution, the algorithm tries to derive multiple non-dominated solutions reasonably distributed over the true Pareto front in one single run, thereby facilitating determining the final tradeoff. The long-term sustainable planning of the Three Gorges cascaded hydropower system consisting of the Three Gorges Dam and Gezhouba Dam located on the Yangtze River in China is studied. Two conflicting objectives, i.e., maximizing hydropower generation and minimizing deviation from the outflow lower target to realize the system’s economic, environmental and social benefits during the drought season, are optimized simultaneously. Experimental results demonstrate that the optimization framework helps to robustly derive multiple feasible non-dominated solutions with satisfactory convergence, diversity and extremity in one single run for the case studied.

Multi-objective optimization of solid waste flows: environmentally sustainable strategies for municipalities.

Science.gov (United States)

Minciardi, Riccardo; Paolucci, Massimo; Robba, Michela; Sacile, Roberto

2008-11-01

An approach to sustainable municipal solid waste (MSW) management is presented, with the aim of supporting the decision on the optimal flows of solid waste sent to landfill, recycling and different types of treatment plants, whose sizes are also decision variables. This problem is modeled with a non-linear, multi-objective formulation. Specifically, four objectives to be minimized have been taken into account, which are related to economic costs, unrecycled waste, sanitary landfill disposal and environmental impact (incinerator emissions). An interactive reference point procedure has been developed to support decision making; these methods are considered appropriate for multi-objective decision problems in environmental applications. In addition, interactive methods are generally preferred by decision makers as they can be directly involved in the various steps of the decision process. Some results deriving from the application of the proposed procedure are presented. The application of the procedure is exemplified by considering the interaction with two different decision makers who are assumed to be in charge of planning the MSW system in the municipality of Genova (Italy).

An Integrated Method for Interval Multi-Objective Planning of a Water Resource System in the Eastern Part of Handan

Directory of Open Access Journals (Sweden)

Meiqin Suo

2017-07-01

Full Text Available In this study, an integrated solving method is proposed for interval multi-objective planning. The proposed method is based on fuzzy linear programming and an interactive two-step method. It cannot only provide objectively optimal values for multiple objectives at the same time, but also effectively offer a globally optimal interval solution. Meanwhile, the degree of satisfaction related to different objective functions would be obtained. Then, the integrated solving method for interval multi-objective planning is applied to a case study of planning multi-water resources joint scheduling under uncertainty in the eastern part of Handan, China. The solutions obtained are useful for decision makers in easing the contradiction between supply of multi-water resources and demand from different water users. Moreover, it can provide the optimal comprehensive benefits of economy, society, and the environment.

Cancer microarray data feature selection using multi-objective binary particle swarm optimization algorithm

Science.gov (United States)

Annavarapu, Chandra Sekhara Rao; Dara, Suresh; Banka, Haider

2016-01-01

Cancer investigations in microarray data play a major role in cancer analysis and the treatment. Cancer microarray data consists of complex gene expressed patterns of cancer. In this article, a Multi-Objective Binary Particle Swarm Optimization (MOBPSO) algorithm is proposed for analyzing cancer gene expression data. Due to its high dimensionality, a fast heuristic based pre-processing technique is employed to reduce some of the crude domain features from the initial feature set. Since these pre-processed and reduced features are still high dimensional, the proposed MOBPSO algorithm is used for finding further feature subsets. The objective functions are suitably modeled by optimizing two conflicting objectives i.e., cardinality of feature subsets and distinctive capability of those selected subsets. As these two objective functions are conflicting in nature, they are more suitable for multi-objective modeling. The experiments are carried out on benchmark gene expression datasets, i.e., Colon, Lymphoma and Leukaemia available in literature. The performance of the selected feature subsets with their classification accuracy and validated using 10 fold cross validation techniques. A detailed comparative study is also made to show the betterment or competitiveness of the proposed algorithm. PMID:27822174

Processing Technology Selection for Municipal Sewage Treatment Based on a Multi-Objective Decision Model under Uncertainty

Directory of Open Access Journals (Sweden)

Xudong Chen

2018-03-01

Full Text Available This study considers the two factors of environmental protection and economic benefits to address municipal sewage treatment. Based on considerations regarding the sewage treatment plant construction site, processing technology, capital investment, operation costs, water pollutant emissions, water quality and other indicators, we establish a general multi-objective decision model for optimizing municipal sewage treatment plant construction. Using the construction of a sewage treatment plant in a suburb of Chengdu as an example, this paper tests the general model of multi-objective decision-making for the sewage treatment plant construction by implementing a genetic algorithm. The results show the applicability and effectiveness of the multi-objective decision model for the sewage treatment plant. This paper provides decision and technical support for the optimization of municipal sewage treatment.

Compact stellarators as reactors

International Nuclear Information System (INIS)

Lyon, J.F.; Valanju, P.; Zarnstorff, M.C.; Hirshman, S.; Spong, D.A.; Strickler, D.; Williamson, D.E.; Ware, A.

2001-01-01

Two types of compact stellarators are examined as reactors: two- and three-field-period (M=2 and 3) quasi-axisymmetric devices with volume-average =4-5% and M=2 and 3 quasi-poloidal devices with =10-15%. These low-aspect-ratio stellarator-tokamak hybrids differ from conventional stellarators in their use of the plasma-generated bootstrap current to supplement the poloidal field from external coils. Using the ARIES-AT model with B max =12T on the coils gives Compact Stellarator reactors with R=7.3-8.2m, a factor of 2-3 smaller R than other stellarator reactors for the same assumptions, and neutron wall loadings up to 3.7MWm -2 . (author)

The dependence of halo mass on galaxy size at fixed stellar mass using weak lensing

Science.gov (United States)

Charlton, Paul J. L.; Hudson, Michael J.; Balogh, Michael L.; Khatri, Sumeet

2017-12-01

Stellar mass has been shown to correlate with halo mass, with non-negligible scatter. The stellar mass-size and luminosity-size relationships of galaxies also show significant scatter in galaxy size at fixed stellar mass. It is possible that, at fixed stellar mass and galaxy colour, the halo mass is correlated with galaxy size. Galaxy-galaxy lensing allows us to measure the mean masses of dark matter haloes for stacked samples of galaxies. We extend the analysis of the galaxies in the CFHTLenS catalogue by fitting single Sérsic surface brightness profiles to the lens galaxies in order to recover half-light radius values, allowing us to determine halo masses for lenses according to their size. Comparing our halo masses and sizes to baselines for that stellar mass yields a differential measurement of the halo mass-galaxy size relationship at fixed stellar mass, defined as Mh(M_{*}) ∝ r_{eff}^{η }(M_{*}). We find that, on average, our lens galaxies have an η = 0.42 ± 0.12, i.e. larger galaxies live in more massive dark matter haloes. The η is strongest for high-mass luminous red galaxies. Investigation of this relationship in hydrodynamical simulations suggests that, at a fixed M*, satellite galaxies have a larger η and greater scatter in the Mh and reff relationship compared to central galaxies.

A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

Science.gov (United States)

Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

2015-06-01

The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi-objective mixed integer nonlinear programming formulation is linearized by defining new variables and adding new constraints to the model. By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.

The Science Case for Multi-Object Spectroscopy on the European ELT

NARCIS (Netherlands)

Evans, Chris; Puech, Mathieu; Afonso, Jose; Almaini, Omar; Amram, Philippe; Aussel, Hervé; Barbuy, Beatriz; Basden, Alistair; Bastian, Nate; Battaglia, Giuseppina; Biller, Beth; Bonifacio, Piercarlo; Bouché, Nicholas; Bunker, Andy; Caffau, Elisabetta; Charlot, Stephane; Cirasuolo, Michele; Clenet, Yann; Combes, Francoise; Conselice, Chris; Contini, Thierry; Cuby, Jean-Gabriel; Dalton, Gavin; Davies, Ben; de Koter, Alex; Disseau, Karen; Dunlop, Jim; Epinat, Benoît; Fiore, Fabrizio; Feltzing, Sofia; Ferguson, Annette; Flores, Hector; Fontana, Adriano; Fusco, Thierry; Gadotti, Dimitri; Gallazzi, Anna; Gallego, Jesus; Giallongo, Emanuele; Gonçalves, Thiago; Gratadour, Damien; Guenther, Eike; Hammer, Francois; Hill, Vanessa; Huertas-Company, Marc; Ibata, Roridgo; Kaper, Lex; Korn, Andreas; Larsen, Søren; Le Fèvre, Olivier; Lemasle, Bertrand; Maraston, Claudia; Mei, Simona; Mellier, Yannick; Morris, Simon; Östlin, Göran; Paumard, Thibaut; Pello, Roser; Pentericci, Laura; Peroux, Celine; Petitjean, Patrick; Rodrigues, Myriam; Rodríguez-Muñoz, Lucía; Rouan, Daniel; Sana, Hugues; Schaerer, Daniel; Telles, Eduardo; Trager, Scott; Tresse, Laurence; Welikala, Niraj; Zibetti, Stefano; Ziegler, Bodo

2015-01-01

This White Paper presents the scientific motivations for a multi-object spectrograph (MOS) on the European Extremely Large Telescope (E-ELT). The MOS case draws on all fields of contemporary astronomy, from extra-solar planets, to the study of the halo of the Milky Way and its satellites, and from

Multi-objective optimization of a series–parallel system using GPSIA

International Nuclear Information System (INIS)

Okafor, Ekene Gabriel; Sun Youchao

2012-01-01

The optimal solution of a multi-objective optimization problem (MOP) corresponds to a Pareto set that is characterized by a tradeoff between objectives. Genetic Pareto Set Identification Algorithm (GPSIA) proposed for reliability-redundant MOPs is a hybrid technique which combines genetic and heuristic principles to generate non-dominated solutions. Series–parallel system with active redundancy is studied in this paper. Reliability and cost were the research objective functions subject to cost and weight constraints. The results reveal an evenly distributed non-dominated front. The distances between successive Pareto points were used to evaluate the general performance of the method. Plots were also used to show the computational results for the type of system studied and the robustness of the technique is discussed in comparison with NSGA-II and SPEA-2.

THE PALOMAR TRANSIENT FACTORY ORION PROJECT: ECLIPSING BINARIES AND YOUNG STELLAR OBJECTS

International Nuclear Information System (INIS)

Van Eyken, Julian C.; Ciardi, David R.; Akeson, Rachel L.; Beichman, Charles A.; Von Braun, Kaspar; Gelino, Dawn M.; Kane, Stephen R.; Plavchan, Peter; RamIrez, Solange V.; Rebull, Luisa M.; Stauffer, John R.; Hoard, D. W.; Boden, Andrew F.; Howell, Steve B.; Bloom, Joshua S.; Cenko, S. Bradley; Kasliwal, Mansi M.; Kulkarni, Shrinivas R.; Law, Nicholas M.; Nugent, Peter E.

2011-01-01

The Palomar Transient Factory (PTF) Orion project is one of the experiments within the broader PTF survey, a systematic automated exploration of the sky for optical transients. Taking advantage of the wide (3. 0 5 x 2. 0 3) field of view available using the PTF camera installed at the Palomar 48 inch telescope, 40 nights were dedicated in 2009 December to 2010 January to perform continuous high-cadence differential photometry on a single field containing the young (7-10 Myr) 25 Ori association. Little is known empirically about the formation of planets at these young ages, and the primary motivation for the project is to search for planets around young stars in this region. The unique data set also provides for much ancillary science. In this first paper, we describe the survey and the data reduction pipeline, and present some initial results from an inspection of the most clearly varying stars relating to two of the ancillary science objectives: detection of eclipsing binaries and young stellar objects. We find 82 new eclipsing binary systems, 9 of which are good candidate 25 Ori or Orion OB1a association members. Of these, two are potential young W UMa type systems. We report on the possible low-mass (M-dwarf primary) eclipsing systems in the sample, which include six of the candidate young systems. Forty-five of the binary systems are close (mainly contact) systems, and one of these shows an orbital period among the shortest known for W UMa binaries, at 0.2156509 ± 0.0000071 days, with flat-bottomed primary eclipses, and a derived distance that appears consistent with membership in the general Orion association. One of the candidate young systems presents an unusual light curve, perhaps representing a semi-detached binary system with an inflated low-mass primary or a star with a warped disk, and may represent an additional young Orion member. Finally, we identify 14 probable new classical T-Tauri stars in our data, along with one previously known (CVSO 35) and

Investigation on multi-objective performance optimization algorithm application of fan based on response surface method and entropy method

Science.gov (United States)

Zhang, Li; Wu, Kexin; Liu, Yang

2017-12-01

A multi-objective performance optimization method is proposed, and the problem that single structural parameters of small fan balance the optimization between the static characteristics and the aerodynamic noise is solved. In this method, three structural parameters are selected as the optimization variables. Besides, the static pressure efficiency and the aerodynamic noise of the fan are regarded as the multi-objective performance. Furthermore, the response surface method and the entropy method are used to establish the optimization function between the optimization variables and the multi-objective performances. Finally, the optimized model is found when the optimization function reaches its maximum value. Experimental data shows that the optimized model not only enhances the static characteristics of the fan but also obviously reduces the noise. The results of the study will provide some reference for the optimization of multi-objective performance of other types of rotating machinery.

An Efficacious Multi-Objective Fuzzy Linear Programming Approach for Optimal Power Flow Considering Distributed Generation.

Science.gov (United States)

Warid, Warid; Hizam, Hashim; Mariun, Norman; Abdul-Wahab, Noor Izzri

2016-01-01

This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF) problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve. Fuzzy membership functions for these objectives are designed with extreme targets, whereas the inequality constraints are treated as hard constraints. The multi-objective fuzzy optimal power flow (OPF) formulation was converted into a crisp OPF in a successive linear programming (SLP) framework and solved using an efficient interior point method (IPM). To test the efficacy of the proposed approach, simulations are performed on the IEEE 30-busand IEEE 118-bus test systems. The MFLP optimization is solved for several optimization cases. The obtained results are compared with those presented in the literature. A unique solution with a high satisfaction for the assigned targets is gained. Results demonstrate the effectiveness of the proposed MFLP technique in terms of solution optimality and rapid convergence. Moreover, the results indicate that using the optimal DG location with the MFLP algorithm provides the solution with the highest quality.

Design optimization of axial flow hydraulic turbine runner: Part II - multi-objective constrained optimization method

Science.gov (United States)

Peng, Guoyi; Cao, Shuliang; Ishizuka, Masaru; Hayama, Shinji

2002-06-01

This paper is concerned with the design optimization of axial flow hydraulic turbine runner blade geometry. In order to obtain a better design plan with good performance, a new comprehensive performance optimization procedure has been presented by combining a multi-variable multi-objective constrained optimization model with a Q3D inverse computation and a performance prediction procedure. With careful analysis of the inverse design of axial hydraulic turbine runner, the total hydraulic loss and the cavitation coefficient are taken as optimization objectives and a comprehensive objective function is defined using the weight factors. Parameters of a newly proposed blade bound circulation distribution function and parameters describing positions of blade leading and training edges in the meridional flow passage are taken as optimization variables.The optimization procedure has been applied to the design optimization of a Kaplan runner with specific speed of 440 kW. Numerical results show that the performance of designed runner is successfully improved through optimization computation. The optimization model is found to be validated and it has the feature of good convergence. With the multi-objective optimization model, it is possible to control the performance of designed runner by adjusting the value of weight factors defining the comprehensive objective function. Copyright

Stellar magnetic activity

International Nuclear Information System (INIS)

Schrijver, C.J.

1986-01-01

The stellar emission in the chromospheric Ca II H+K lines is compared with the coronal soft X-ray emission, measuring the effects of non-radiative heating in the outer atmosphere at temperatures differing two orders of magnitude. The comparison of stellar flux densities in Ca II H+K and X-rays is extended to fluxes from the transition-region and the high-temperature chromosphere. The stellar magnetic field is probably generated in the differentially rotating convective envelope. The relation between rotation rate and the stellar level of activity measured in chromospheric, transition-region, and coronal radiative diagnostics is discovered. X-ray observations of the binary λ Andromedae are discussed. The departure of M-type dwarfs from the main relations, and the implications for the structure of the chromospheres of these stars are discussed. Variations of the average surface flux densities of the Sun during the 11-year activity cycle agree with flux-flux relations derived for other cool stars, suggesting that the interpretation of the stellar relations may be furthered by studying the solar analogue in more detail. (Auth.)

Evolution of Galaxy Luminosity and Stellar-Mass Functions since $z=1$ with the Dark Energy Survey Science Verification Data

Energy Technology Data Exchange (ETDEWEB)

Capozzi, D.; et al.

2017-07-27

We present the first study of the evolution of the galaxy luminosity and stellar-mass functions (GLF and GSMF) carried out by the Dark Energy Survey (DES). We describe the COMMODORE galaxy catalogue selected from Science Verification images. This catalogue is made of $\\sim 4\\times 10^{6}$ galaxies at $0stellar mass functions are characterised by a double-Schechter shape at $z<0.2$. Both functions agree well with those based on spectroscopic redshifts. The DES GSMF agrees especially with those measured for the GAlaxy Mass Assembly and the PRism MUlti-object Survey out to $z\\sim1$. At $0.2stellar-mass densities respectively to be constant ($\\rho_{\\rm L}\\propto (1+z)^{-0.12\\pm0.11}$) and decreasing ($\\rho_{\\rm Mstar}\\propto (1+z)^{-0.5\\pm0.1}$) with $z$. This indicates that, while at higher redshift galaxies have less stellar mass, their luminosities do not change substantially because of their younger and brighter stellar populations. Finally, we also find evidence for a top-down mass-dependent evolution of the GSMF.

Multi-objective based on parallel vector evaluated particle swarm optimization for optimal steady-state performance of power systems

DEFF Research Database (Denmark)

Vlachogiannis, Ioannis (John); Lee, K Y

2009-01-01

In this paper the state-of-the-art extended particle swarm optimization (PSO) methods for solving multi-objective optimization problems are represented. We emphasize in those, the co-evolution technique of the parallel vector evaluated PSO (VEPSO), analysed and applied in a multi-objective problem...

Design, construction and validation of the UST-1 modular stellarator

Energy Technology Data Exchange (ETDEWEB)

Queral, V., E-mail: vicentemanuel.queral@ciemat.es

2016-11-15

Highlights: • A small and simple low cost two period modular stellarator is reviewed. • It is defined as a monolithic circular surface torus with carved grooves. • The grooves are accurately mechanised by a new toroidal milling machine. • A very simple e-beam field mapping system has been built and utilized. - Abstract: Stellarator advancement is hindered, among others, by the requirement of geometric complexity at high accuracy and the still scarce universities and research centres following the stellarator line. In this framework, the objectives of the small UST-1 stellarator development were to: (i) explore and test the performance of one possible accurate construction method for stellarators (ii) encourage universities and small fusion research centres to build simple and economical stellarators (iii) educative purpose. Therefore, UST-1 was properly designed to be easily built by a milling machine working on toroidal coordinates, being the winding surface circular poloidally and toroidally. The coil frame is a sole monolithic toroidal thick surface equipped with grooves mechanised by the toroidal milling machine. Only one double pancake is wound in each groove so as to compress the conductor on the laterals of the groove in order to speed up and simplify the winding process. The physics design, the conceptual engineering design and the construction process of UST-1 is presented. The toroidal milling machine is described. The e-beam field line mapping experiments carried out to validate the resulting magnetic configuration are reported. The developed construction method has been proved for the small UST-1 stellarator. Small stellarators are valuable for quick tests of diagnostics, educative purposes, assessment of new confinement concepts, turbulence studies and other applications.

Design, construction and validation of the UST-1 modular stellarator

International Nuclear Information System (INIS)

Queral, V.

2016-01-01

Highlights: • A small and simple low cost two period modular stellarator is reviewed. • It is defined as a monolithic circular surface torus with carved grooves. • The grooves are accurately mechanised by a new toroidal milling machine. • A very simple e-beam field mapping system has been built and utilized. - Abstract: Stellarator advancement is hindered, among others, by the requirement of geometric complexity at high accuracy and the still scarce universities and research centres following the stellarator line. In this framework, the objectives of the small UST-1 stellarator development were to: (i) explore and test the performance of one possible accurate construction method for stellarators (ii) encourage universities and small fusion research centres to build simple and economical stellarators (iii) educative purpose. Therefore, UST-1 was properly designed to be easily built by a milling machine working on toroidal coordinates, being the winding surface circular poloidally and toroidally. The coil frame is a sole monolithic toroidal thick surface equipped with grooves mechanised by the toroidal milling machine. Only one double pancake is wound in each groove so as to compress the conductor on the laterals of the groove in order to speed up and simplify the winding process. The physics design, the conceptual engineering design and the construction process of UST-1 is presented. The toroidal milling machine is described. The e-beam field line mapping experiments carried out to validate the resulting magnetic configuration are reported. The developed construction method has been proved for the small UST-1 stellarator. Small stellarators are valuable for quick tests of diagnostics, educative purposes, assessment of new confinement concepts, turbulence studies and other applications.

Multi-objective optimization of riparian buffer networks; valuing present and future benefits

Science.gov (United States)

Multi-objective optimization has emerged as a popular approach to support water resources planning and management. This approach provides decision-makers with a suite of management options which are generated based on metrics that represent different social, economic, and environ...

Modeling Multi-wavelength Stellar Astrometry. III. Determination of the Absolute Masses of Exoplanets and Their Host Stars

Science.gov (United States)

Coughlin, J. L.; López-Morales, Mercedes

2012-05-01

Astrometric measurements of stellar systems are becoming significantly more precise and common, with many ground- and space-based instruments and missions approaching 1 μas precision. We examine the multi-wavelength astrometric orbits of exoplanetary systems via both analytical formulae and numerical modeling. Exoplanets have a combination of reflected and thermally emitted light that causes the photocenter of the system to shift increasingly farther away from the host star with increasing wavelength. We find that, if observed at long enough wavelengths, the planet can dominate the astrometric motion of the system, and thus it is possible to directly measure the orbits of both the planet and star, and thus directly determine the physical masses of the star and planet, using multi-wavelength astrometry. In general, this technique works best for, though is certainly not limited to, systems that have large, high-mass stars and large, low-mass planets, which is a unique parameter space not covered by other exoplanet characterization techniques. Exoplanets that happen to transit their host star present unique cases where the physical radii of the planet and star can be directly determined via astrometry alone. Planetary albedos and day-night contrast ratios may also be probed via this technique due to the unique signature they impart on the observed astrometric orbits. We develop a tool to examine the prospects for near-term detection of this effect, and give examples of some exoplanets that appear to be good targets for detection in the K to N infrared observing bands, if the required precision can be achieved.

MODELING MULTI-WAVELENGTH STELLAR ASTROMETRY. III. DETERMINATION OF THE ABSOLUTE MASSES OF EXOPLANETS AND THEIR HOST STARS

International Nuclear Information System (INIS)

Coughlin, J. L.; López-Morales, Mercedes

2012-01-01

Astrometric measurements of stellar systems are becoming significantly more precise and common, with many ground- and space-based instruments and missions approaching 1 μas precision. We examine the multi-wavelength astrometric orbits of exoplanetary systems via both analytical formulae and numerical modeling. Exoplanets have a combination of reflected and thermally emitted light that causes the photocenter of the system to shift increasingly farther away from the host star with increasing wavelength. We find that, if observed at long enough wavelengths, the planet can dominate the astrometric motion of the system, and thus it is possible to directly measure the orbits of both the planet and star, and thus directly determine the physical masses of the star and planet, using multi-wavelength astrometry. In general, this technique works best for, though is certainly not limited to, systems that have large, high-mass stars and large, low-mass planets, which is a unique parameter space not covered by other exoplanet characterization techniques. Exoplanets that happen to transit their host star present unique cases where the physical radii of the planet and star can be directly determined via astrometry alone. Planetary albedos and day-night contrast ratios may also be probed via this technique due to the unique signature they impart on the observed astrometric orbits. We develop a tool to examine the prospects for near-term detection of this effect, and give examples of some exoplanets that appear to be good targets for detection in the K to N infrared observing bands, if the required precision can be achieved.

sunstardb: A Database for the Study of Stellar Magnetism and the Solar-stellar Connection

Science.gov (United States)

Egeland, Ricky

2018-05-01

The “solar-stellar connection” began as a relatively small field of research focused on understanding the processes that generate magnetic fields in stars and sometimes lead to a cyclic pattern of long-term variability in activity, as demonstrated by our Sun. This area of study has recently become more broadly pertinent to questions of exoplanet habitability and exo-space weather, as well as stellar evolution. In contrast to other areas of stellar research, individual stars in the solar-stellar connection often have a distinct identity and character in the literature, due primarily to the rarity of the decades-long time-series that are necessary for studying stellar activity cycles. Furthermore, the underlying stellar dynamo is not well understood theoretically, and is thought to be sensitive to several stellar properties, e.g., luminosity, differential rotation, and the depth of the convection zone, which in turn are often parameterized by other more readily available properties. Relevant observations are scattered throughout the literature and existing stellar databases, and consolidating information for new studies is a tedious and laborious exercise. To accelerate research in this area I developed sunstardb, a relational database of stellar properties and magnetic activity proxy time-series keyed by individual named stars. The organization of the data eliminates the need for the problematic catalog cross-matching operations inherent when building an analysis data set from heterogeneous sources. In this article I describe the principles behind sunstardb, the data structures and programming interfaces, as well as use cases from solar-stellar connection research.

Multi-objective optimization of a type of ellipse-parabola shaped superelastic flexure hinge

Directory of Open Access Journals (Sweden)

Z. Du

2016-05-01

Full Text Available Flexure hinges made of superelastic materials is a promising candidate to enhance the movability of compliant mechanisms. In this paper, we focus on the multi-objective optimization of a type of ellipse-parabola shaped superelastic flexure hinge. The objective is to determine a set of optimal geometric parameters that maximizes the motion range and the relative compliance of the flexure hinge and minimizes the relative rotation error during the deformation as well. Firstly, the paper presents a new type of ellipse-parabola shaped flexure hinge which is constructed by an ellipse arc and a parabola curve. Then, the static responses of superelastic flexure hinges are solved via non-prismatic beam elements derived by the co-rotational approach. Finite element analysis (FEA and experiment tests are performed to verify the modeling method. Finally, a multi-objective optimization is performed and the Pareto frontier is found via the NSGA-II algorithm.

Multi-objective optimization under uncertainty for sheet metal forming

Directory of Open Access Journals (Sweden)

Lafon Pascal

2016-01-01

Full Text Available Aleatory uncertainties in material properties, blank thickness and friction condition are inherent and irreducible variabilities in sheet metal forming. Optimal design configurations, which are obtained by conventional design optimization methods, are not always able to meet the desired targets due to the effect of uncertainties. This paper proposes a multi-objective robust design optimization that aims to tackle this problem. Results obtained on a U shape draw bending benchmark show that spring-back effect can be controlled by optimizing process parameters.

A sustainable manufacturing system design: A fuzzy multi-objective optimization model.

Science.gov (United States)

Nujoom, Reda; Mohammed, Ahmed; Wang, Qian

2017-08-10

In the past decade, there has been a growing concern about the environmental protection in public society as governments almost all over the world have initiated certain rules and regulations to promote energy saving and minimize the production of carbon dioxide (CO 2 ) emissions in many manufacturing industries. The development of sustainable manufacturing systems is considered as one of the effective solutions to minimize the environmental impact. Lean approach is also considered as a proper method for achieving sustainability as it can reduce manufacturing wastes and increase the system efficiency and productivity. However, the lean approach does not include environmental waste of such as energy consumption and CO 2 emissions when designing a lean manufacturing system. This paper addresses these issues by evaluating a sustainable manufacturing system design considering a measurement of energy consumption and CO 2 emissions using different sources of energy (oil as direct energy source to generate thermal energy and oil or solar as indirect energy source to generate electricity). To this aim, a multi-objective mathematical model is developed incorporating the economic and ecological constraints aimed for minimization of the total cost, energy consumption, and CO 2 emissions for a manufacturing system design. For the real world scenario, the uncertainty in a number of input parameters was handled through the development of a fuzzy multi-objective model. The study also addresses decision-making in the number of machines, the number of air-conditioning units, and the number of bulbs involved in each process of a manufacturing system in conjunction with a quantity of material flow for processed products. A real case study was used for examining the validation and applicability of the developed sustainable manufacturing system model using the fuzzy multi-objective approach.

EURISOL-DS Multi-MW Target Comparative Neutronic Performance of the Baseline Configuration vs. the Hg-Jet Option

CERN Document Server

Herrera-Martínez, A

2006-01-01

This technical report summarises the comparative study between several design options for the Multi-MW target station performed within Task #2 of the European Isotope Separation On-Line Radioactive Ion Beam Facility Design Study (EURISOL DS) [1]. Previous analyses were carried out, using the Monte Carlo code FLUKA [2], to determine optimal values for relevant parameters in the target design [3] and to analyse a preliminary Multi-MW target assembly configuration [4]. The second report showed that the aimed fission rates, i.e. ~1015 fissions/s, could be achieved with such a configuration. Nevertheless, a preliminary study of the target assembly integration [5] suggested reducing some of the dimensions. Moreover, the yields of specific isotopes have yet to be assessed and compared to other target configurations. This note presents a detailed comparison of the baseline configuration and the Hg-jet option, in terms of primary and neutron distribution, power densities and fission product yields. A scaled-down versi...

Intersection signal control multi-objective optimization based on genetic algorithm

OpenAIRE

Zhanhong Zhou; Ming Cai

2014-01-01

A signal control intersection increases not only vehicle delay, but also vehicle emissions and fuel consumption in that area. Because more and more fuel and air pollution problems arise recently, an intersection signal control optimization method which aims at reducing vehicle emissions, fuel consumption and vehicle delay is required heavily. This paper proposed a signal control multi-object optimization method to reduce vehicle emissions, fuel consumption and vehicle delay simultaneously at ...

Multi-objective three stage design optimization for island microgrids

International Nuclear Information System (INIS)

Sachs, Julia; Sawodny, Oliver

2016-01-01

Highlights: • An enhanced multi-objective three stage design optimization for microgrids is given. • Use of an optimal control problem for the calculation of the optimal operation. • The inclusion of a detailed battery model with CC/CV charging control. • The determination of a representative profile with optimized number of days. • The proposed method finds its direct application in a design tool for microgids. - Abstract: Hybrid off-grid energy systems enable a cost efficient and reliable energy supply to rural areas around the world. The main potential for a low cost operation and uninterrupted power supply lies in the optimal sizing and operation of such microgrids. In particular, sudden variations in load demand or in the power supply from renewables underline the need for an optimally sized system. This paper presents an efficient multi-objective model based optimization approach for the optimal sizing of all components and the determination of the best power electronic layout. The presented method is divided into three optimization problems to minimize economic and environmental objectives. This design optimization includes detailed components models and an optimized energy dispatch strategy which enables the optimal design of the energy system with respect to an adequate control for the specific configuration. To significantly reduce the computation time without loss of accuracy, the presented method contains the determination of a representative load profile using a k-means clustering method. The k-means algorithm itself is embedded in an optimization problem for the calculation of the optimal number of clusters. The benefits in term of reduced computation time, inclusion of optimal energy dispatch and optimization of power electronic architecture, of the presented optimization method are illustrated using a case study.

Stellar population in star formation regions of galaxies

Science.gov (United States)

Gusev, Alexander S.; Shimanovskaya, Elena V.; Shatsky, Nikolai I.; Sakhibov, Firouz; Piskunov, Anatoly E.; Kharchenko, Nina V.

2018-05-01

We developed techniques for searching young unresolved star groupings (clusters, associations, and their complexes) and of estimating their physical parameters. Our study is based on spectroscopic, spectrophotometric, and UBVRI photometric observations of 19 spiral galaxies. In the studied galaxies, we found 1510 objects younger than 10 Myr and present their catalogue. Having combined photometric and spectroscopic data, we derived extinctions, chemical abundances, sizes, ages, and masses of these groupings. We discuss separately the specific cases, when the gas extinction does not agree with the interstellar one. We assume that this is due to spatial offset of Hii clouds with respect to the related stellar population.We developed a method to estimate age of stellar population of the studied complexes using their morphology and the relation with associated H emission region. In result we obtained the estimates of chemical abundances for 80, masses for 63, and ages for 57 young objects observed in seven galaxies.

Multi-objective optimization of water supply network rehabilitation with non-dominated sorting Genetic Algorithm-Ⅱ

Institute of Scientific and Technical Information of China (English)

Xi JIN; Jie ZHANG; Jin-liang GAO; Wen-yan WU

2008-01-01

Through the transformation of hydraulic constraints into the objective functions associated with a water supply network rehabilitation problem, a non-dominated sorting Genetic Aigorithm-Ⅱ (NSGA-Ⅱ) can be used to solve the altered multi-objective optimization model. The introduction of NSGA-Ⅱ into water supply network optimal rehabilitation problem solves the conflict between one fitness value of standard genetic algorithm (SGA) and multi-objectives of rehabilitation problem. And the uncertainties brought by using weight coefficients or punish functions in conventional methods are controlled. And also by introduction of artificial inducement mutation (AIM) operation, the convergence speed of population is accelerated; this operation not only improves the convergence speed, but also improves the rationality and feasibility of solutions.

Multi-objective particle swarm and genetic algorithm for the optimization of the LANSCE linac operation

International Nuclear Information System (INIS)