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...

Multi-Objective Aerodynamic and Structural Optimization of Horizontal-Axis Wind Turbine Blades

Directory of Open Access Journals (Sweden)

Jie Zhu

2017-01-01

Full Text Available A procedure based on MATLAB combined with ANSYS is presented and utilized for the multi-objective aerodynamic and structural optimization of horizontal-axis wind turbine (HAWT blades. In order to minimize the cost of energy (COE and improve the overall performance of the blades, materials of carbon fiber reinforced plastic (CFRP combined with glass fiber reinforced plastic (GFRP are applied. The maximum annual energy production (AEP, the minimum blade mass and the minimum blade cost are taken as three objectives. Main aerodynamic and structural characteristics of the blades are employed as design variables. Various design requirements including strain, deflection, vibration and buckling limits are taken into account as constraints. To evaluate the aerodynamic performances and the structural behaviors, the blade element momentum (BEM theory and the finite element method (FEM are applied in the procedure. Moreover, the non-dominated sorting genetic algorithm (NSGA II, which constitutes the core of the procedure, is adapted for the multi-objective optimization of the blades. To prove the efficiency and reliability of the procedure, a commercial 1.5 MW HAWT blade is used as a case study, and a set of trade-off solutions is obtained. Compared with the original scheme, the optimization results show great improvements for the overall performance of the blade.

Programmable gain equalizer for multi-core fiber amplifiers

NARCIS (Netherlands)

Fontaine, N.K.; Guan, B.; Ryf, R.; Chen, H.; Koonen, A.M.J.; Ben Yoo, S.J.; Abedin, K.; Fini, J.; Taunay, T.F.; Neilson, D.T.

2014-01-01

We demonstrate a programmable gain equalizer for 7-core fiber that can independently equalize spectra or block wavelengths in each core across the C-band. It is spliced directly to a side-pumped multi-core amplifying fiber.

The Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST) Quasar Survey: Quasar Properties from Data Release Two and Three

Science.gov (United States)

Dong, X. Y.; Wu, Xue-Bing; Ai, Y. L.; Yang, J. Y.; Yang, Q.; Wang, F.; Zhang, Y. X.; Luo, A. L.; Xu, H.; Yuan, H. L.; Zhang, J. N.; Wang, M. X.; Wang, L. L.; Li, Y. B.; Zuo, F.; Hou, W.; Guo, Y. X.; Kong, X.; Chen, X. Y.; Wu, Y.; Yang, H. F.; Yang, M.

2018-05-01

This is the second installment for the Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST) Quasar Survey, which includes quasars observed from 2013 September to 2015 June. There are 9024 confirmed quasars in DR2 and 10911 in DR3. After cross-match with the Sloan Digital Sky Survey (SDSS) quasar catalogs and NED, 12126 quasars are discovered independently. Among them, 2225 quasars were released by SDSS DR12 QSO catalog in 2014 after we finalized the survey candidates. 1801 sources were identified by SDSS DR14 as QSOs. The remaining 8100 quasars are considered as newly founded, and among them, 6887 quasars can be given reliable emission line measurements and the estimated black hole masses. Quasars found in LAMOST are mostly located at low-to-moderate redshifts, with a mean value of 1.5. The highest redshift observed in DR2 and DR3 is 5. We applied emission line measurements to Hα, Hβ, Mg II, and C IV. We deduced the monochromatic continuum luminosities using photometry data, and estimated the virial black hole masses for the newly discovered quasars. Results are compiled into a quasar catalog, which will be available online.

THE PRISM MULTI-OBJECT SURVEY (PRIMUS). II. DATA REDUCTION AND REDSHIFT FITTING

Energy Technology Data Exchange (ETDEWEB)

Cool, Richard J. [MMT Observatory, Tucson, AZ 85721 (United States); Moustakas, John [Department of Physics, Siena College, 515 Loudon Rd., Loudonville, NY 12211 (United States); Blanton, Michael R.; Hogg, David W. [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); Coil, Alison L.; Aird, James; Mendez, Alexander J. [Department of Physics, Center for Astrophysics and Space Sciences, University of California, 9500 Gilman Dr., La Jolla, San Diego, CA 92093 (United States); Eisenstein, Daniel J. [Harvard-Smithsonian Center for Astrophysics, 60 Garden St, MS 20, Cambridge, MA 02138 (United States); Wong, Kenneth C. [Steward Observatory, The University of Arizona, 933 N. Cherry Ave., Tucson, AZ 85721 (United States); Zhu, Guangtun [Center for Astrophysical Sciences, Department of Physics and Astronomy, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218 (United States); Bernstein, Rebecca A. [Department of Astronomy and Astrophysics, UCA/Lick Observatory, University of California, 1156 High Street, Santa Cruz, CA 95064 (United States); Bolton, Adam S. [Department of Physics and Astronomy, University of Utah, Salt Lake City, UT 84112 (United States)

2013-04-20

The PRIsm MUlti-object Survey (PRIMUS) is a spectroscopic galaxy redshift survey to z {approx} 1 completed with a low-dispersion prism and slitmasks allowing for simultaneous observations of {approx}2500 objects over 0.18 deg{sup 2}. The final PRIMUS catalog includes {approx}130,000 robust redshifts over 9.1 deg{sup 2}. In this paper, we summarize the PRIMUS observational strategy and present the data reduction details used to measure redshifts, redshift precision, and survey completeness. The survey motivation, observational techniques, fields, target selection, slitmask design, and observations are presented in Coil et al. Comparisons to existing higher-resolution spectroscopic measurements show a typical precision of {sigma}{sub z}/(1 + z) = 0.005. PRIMUS, both in area and number of redshifts, is the largest faint galaxy redshift survey completed to date and is allowing for precise measurements of the relationship between active galactic nuclei and their hosts, the effects of environment on galaxy evolution, and the build up of galactic systems over the latter half of cosmic history.

Wavelength-dependent Crosstalk in Trench-Assisted Multi-Core Fibers

DEFF Research Database (Denmark)

Ye, Feihong; Tu, Jiajing; Saitoh, Kunimasa

2014-01-01

Analytical expressions for wavelength-dependent crosstalk in homogeneous trench-assisted multi-core fibers are derived. The calculated results from the expressions agree well with the numerical simulation results based on finite element method.......Analytical expressions for wavelength-dependent crosstalk in homogeneous trench-assisted multi-core fibers are derived. The calculated results from the expressions agree well with the numerical simulation results based on finite element method....

SU-E-J-197: A Novel Optical Interstitial Fiber Spectroscopic System for Real-Time Tissue Micro-Vascular Hemodynamics Monitoring.

Science.gov (United States)

Zhao, D; Campos, D; Yan, Y; Kimple, R; Jacques, S; van der Kogel, A; Kissick, M

2012-06-01

To demonstrate a novel interstitial optical fiber spectroscopic system, based on diffuse optical spectroscopies with spectral fitting, for the simultaneous monitoring of tumor blood volume and oxygen tension. The technique provides real-time, minimally-invasive and quantification of tissue micro-vascular hemodynamics. An optical fiber prototype probe characterizesthe optical transport in tissue between two large Numerical Aperture (NA) fibers of 200μm core diameter (BFH37-200, ThorLabs) spaced 3-mm apart. Two 21-Ga medical needles are used to protect fiber ends and to facilitate tissue penetration with minimum local blunt trauma in nude mice with xenografts. A 20W white light source (HL-2000-HP, Ocean Optics) is coupled to one fiber with SMA adapter. The other fiber is used to collect light, which is coupled into the spectrometer (QE65000 with Spectrasuite Operating software and OmniDriver, Ocean Optics). The wavelength response of the probe depends on the wavelength dependence of the light source, and of the light signal collection that includes considerable scatter, modeled with Monte-Carlo techniques (S. Jacques 2010 J. of Innov. Opt. Health Sci. 2 123-9). Measured spectra of tissue are normalized by a measured spectrum of a white standard, yielding the transmission spectrum. A head-and-neck xenograft on the flank of a live mouse is used for development. The optical fiber probe delivers and collects light at an arbitrary depth in the tumor. By spectral fitting of the measured transmission spectrum, an analysis of blood volume and oxygen tension is obtained from the fitting parameters in real time. A newly developed optical fiber spectroscopic system with an optical fiber probe takes spectroscopic techniques to a much deeper level in a tumor, which has potential applications for real-time monitoring hypoxic cell population dynamics for an eventual adaptive therapy metric of particular use in hypofractionated radiotherapy. © 2012 American Association of

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

Multi-objective Optimization of Solar-driven Hollow-fiber Membrane Distillation Systems

Energy Technology Data Exchange (ETDEWEB)

Nenoff, Tina M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Moore, Sarah E. [Univ. of Arizona, Tucson, AZ (United States); Mirchandani, Sera [Univ. of Arizona, Tucson, AZ (United States); Karanikola, Vasiliki [Univ. of Arizona, Tucson, AZ (United States); Arnold, Robert G. [Univ. of Arizona, Tucson, AZ (United States); Saez, Eduardo [Univ. of Arizona, Tucson, AZ (United States)

2017-09-01

Securing additional water sources remains a primary concern for arid regions in both the developed and developing world. Climate change is causing fluctuations in the frequency and duration of precipitation, which can be can be seen as prolonged droughts in some arid areas. Droughts decrease the reliability of surface water supplies, which forces communities to find alternate primary water sources. In many cases, ground water can supplement the use of surface supplies during periods of drought, reducing the need for above-ground storage without sacrificing reliability objectives. Unfortunately, accessible ground waters are often brackish, requiring desalination prior to use, and underdeveloped infrastructure and inconsistent electrical grid access can create obstacles to groundwater desalination in developing regions. The objectives of the proposed project are to (i) mathematically simulate the operation of hollow fiber membrane distillation systems and (ii) optimize system design for off-grid treatment of brackish water. It is anticipated that methods developed here can be used to supply potable water at many off-grid locations in semi-arid regions including parts of the Navajo Reservation. This research is a collaborative project between Sandia and the University of Arizona.

Objective-lens-free Fiber-based Position Detection with Nanometer Resolution in a Fiber Optical Trapping System.

Science.gov (United States)

Ti, Chaoyang; Ho-Thanh, Minh-Tri; Wen, Qi; Liu, Yuxiang

2017-10-13

Position detection with high accuracy is crucial for force calibration of optical trapping systems. Most existing position detection methods require high-numerical-aperture objective lenses, which are bulky, expensive, and difficult to miniaturize. Here, we report an affordable objective-lens-free, fiber-based position detection scheme with 2 nm spatial resolution and 150 MHz bandwidth. This fiber based detection mechanism enables simultaneous trapping and force measurements in a compact fiber optical tweezers system. In addition, we achieved more reliable signal acquisition with less distortion compared with objective based position detection methods, thanks to the light guiding in optical fibers and small distance between the fiber tips and trapped particle. As a demonstration of the fiber based detection, we used the fiber optical tweezers to apply a force on a cell membrane and simultaneously measure the cellular response.

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

Novel Crosstalk Measurement Method for Multi-Core Fiber Fan-In/Fan-Out Devices

DEFF Research Database (Denmark)

Ye, Feihong; Ono, Hirotaka; Abe, Yoshiteru

2016-01-01

We propose a new crosstalk measurement method for multi-core fiber fan-in/fan-out devices utilizing the Fresnel reflection. Compared with the traditional method using core-to-core coupling between a multi-core fiber and a single-mode fiber, the proposed method has the advantages of high reliability...

Multi-antibody biosensing with Topas microstructured polymer optical fiber

DEFF Research Database (Denmark)

Emiliyanov, Grigoriy Andreev; Bang, Ole; Hoiby, Poul E.

We present a Topas based microstructured polymer optical fiber multi-antibody biosensor. This polymer allows localized activation of sensor layers on the inner side of the air holes. This concept is used to create two different sensor sections in the same fiber. Simultaneous detection of two kinds...

Thermal poling of multi-wire array optical fiber

DEFF Research Database (Denmark)

Huang, Lin; An, Honglin; Hayashi, Juliano G.

2018-01-01

We demonstrate in this paper thermal poling of multi-wire array fibers, which extends poling of fibers with two anodes to similar to 50 and similar to 500 wire array anodes. The second harmonic microscopy observations show that second order nonlinearity (SON) layers are developed surrounding all...... the rings of wires in the similar to 50 anode array fiber with poling of 1.8kV, 250 degrees C and 30min duration, and the outer rings of the similar to 500 anode array fiber at lower poling temperature. Our simulations based on a two-dimensional charge dynamics model confirm this can be explained...

Nessie - A versatile multi-fiber feed on the KPNO Mayall 4-meter telescope

Science.gov (United States)

Barden, Samuel C.; Massey, Philip

A multi-fiber instrument utilizing the KPNO 4-meter Lockheed Cassegrain Camera as plate holder for fiber-optic plugboards is described. Up to 49 fibers can be positioned on objects in a 40 arc-minute field of view with a minimum separation of 50 arc-seconds. The plugboards, made of Benalex, hold the fibers normal to the flat plane for better alignment with the telescope pupil, but at a depth which follows the curvature of the focal plane. Two 20 meter cables exist, one for optimal observations in the blue, the other for observations redward of 7000 A. These cables feed the light into the Cryocam, the RC spectrograph, or the Echelle which are located in the large coude room during the observations. Sample observations are presented along with some evaluation of the system stability due to the spectrograph being removed from the telescope. A review of the problems in the astrometry for the plates is also given.

The DEIMOS 10K Spectroscopic Survey Catalog of the COSMOS Field

Science.gov (United States)

Hasinger, G.; Capak, P.; Salvato, M.; Barger, A. J.; Cowie, L. L.; Faisst, A.; Hemmati, S.; Kakazu, Y.; Kartaltepe, J.; Masters, D.; Mobasher, B.; Nayyeri, H.; Sanders, D.; Scoville, N. Z.; Suh, H.; Steinhardt, C.; Yang, Fengwei

2018-05-01

We present a catalog of 10,718 objects in the COSMOS field, observed through multi-slit spectroscopy with the Deep Imaging Multi-Object Spectrograph (DEIMOS) on the Keck II telescope in the wavelength range ∼5500–9800 Å. The catalog contains 6617 objects with high-quality spectra (two or more spectral features), and 1798 objects with a single spectroscopic feature confirmed by the photometric redshift. For 2024 typically faint objects, we could not obtain reliable redshifts. The objects have been selected from a variety of input catalogs based on multi-wavelength observations in the field, and thus have a diverse selection function, which enables the study of the diversity in the galaxy population. The magnitude distribution of our objects is peaked at I AB ∼ 23 and K AB ∼ 21, with a secondary peak at K AB ∼ 24. We sample a broad redshift distribution in the range 0 0.65 with chance probabilities 10 Mpc. An object-to-object comparison with a multitude of other spectroscopic samples in the same field shows that our DEIMOS sample is among the best in terms of fraction of spectroscopic failures and relative redshift accuracy. We have determined the fraction of spectroscopic blends to about 0.8% in our sample. This is likely a lower limit and at any rate well below the most pessimistic expectations. Interestingly, we find evidence for strong lensing of Lyα background emitters within the slits of 12 of our target galaxies, increasing their apparent density by about a factor of 4. The data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

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.

Micro-vision servo control of a multi-axis alignment system for optical fiber assembly

International Nuclear Information System (INIS)

Chen, Weihai; Yu, Fei; Qu, Jianliang; Chen, Wenjie; Zhang, Jianbin

2017-01-01

This paper describes a novel optical fiber assembly system featuring a multi-axis alignment function based on micro-vision feedback control. It consists of an active parallel alignment mechanism, a passive compensation mechanism, a micro-gripper and a micro-vision servo control system. The active parallel alignment part is a parallelogram-based design with remote-center-of-motion (RCM) function to achieve precise rotation without fatal lateral motion. The passive mechanism, with five degrees of freedom (5-DOF), is used to implement passive compensation for multi-axis errors. A specially designed 1-DOF micro-gripper mounted onto the active parallel alignment platform is adopted to grasp and rotate the optical fiber. A micro-vision system equipped with two charge-coupled device (CCD) cameras is introduced to observe the small field of view and obtain multi-axis errors for servo feedback control. The two CCD cameras are installed in an orthogonal arrangement—thus the errors can be easily measured via the captured images. Meanwhile, a series of tracking and measurement algorithms based on specific features of the target objects are developed. Details of the force and displacement sensor information acquisition in the assembly experiment are also provided. An experiment demonstrates the validity of the proposed visual algorithm by achieving the task of eliminating errors and inserting an optical fiber to the U-groove accurately. (paper)

High-Capacity Multi-Core Fibers for Space-Division Multiplexing

DEFF Research Database (Denmark)

Ye, Feihong

The transmission capacity of the present optical fiber communication systems based on time division multiplexing (TDM) and wavelength-division multiplexing (WDM) using single-mode fibers (SMFs) is reaching its limit of around 100 Tbit/s per fiber due to the fiber nonlinearities, fiber fuse...... phenomenon and the optical amplifier bandwidth. To meet the ever increasing global data traffic growth and to overcome the looming capacity crunch, a new multiplexing technology using new optical fibers is urgently needed. Space-division multiplexing (SDM) is a promising scheme to overcome the capacity limit...... of the present SMF-based systems. Among the proposed SDM schemes, the one based on uncoupled multi-core fibers (MCFs) having multiple cores in a mutual cladding has proven effective in substantially increasing the transmission capacity per fiber with least system complexity as demonstrated in several state...

Core-to-core uniformity improvement in multi-core fiber Bragg gratings

Science.gov (United States)

Lindley, Emma; Min, Seong-Sik; Leon-Saval, Sergio; Cvetojevic, Nick; Jovanovic, Nemanja; Bland-Hawthorn, Joss; Lawrence, Jon; Gris-Sanchez, Itandehui; Birks, Tim; Haynes, Roger; Haynes, Dionne

2014-07-01

Multi-core fiber Bragg gratings (MCFBGs) will be a valuable tool not only in communications but also various astronomical, sensing and industry applications. In this paper we address some of the technical challenges of fabricating effective multi-core gratings by simulating improvements to the writing method. These methods allow a system designed for inscribing single-core fibers to cope with MCFBG fabrication with only minor, passive changes to the writing process. Using a capillary tube that was polished on one side, the field entering the fiber was flattened which improved the coverage and uniformity of all cores.

Superpixel-based segmentation of muscle fibers in multi-channel microscopy.

Science.gov (United States)

Nguyen, Binh P; Heemskerk, Hans; So, Peter T C; Tucker-Kellogg, Lisa

2016-12-05

Confetti fluorescence and other multi-color genetic labelling strategies are useful for observing stem cell regeneration and for other problems of cell lineage tracing. One difficulty of such strategies is segmenting the cell boundaries, which is a very different problem from segmenting color images from the real world. This paper addresses the difficulties and presents a superpixel-based framework for segmentation of regenerated muscle fibers in mice. We propose to integrate an edge detector into a superpixel algorithm and customize the method for multi-channel images. The enhanced superpixel method outperforms the original and another advanced superpixel algorithm in terms of both boundary recall and under-segmentation error. Our framework was applied to cross-section and lateral section images of regenerated muscle fibers from confetti-fluorescent mice. Compared with "ground-truth" segmentations, our framework yielded median Dice similarity coefficients of 0.92 and higher. Our segmentation framework is flexible and provides very good segmentations of multi-color muscle fibers. We anticipate our methods will be useful for segmenting a variety of tissues in confetti fluorecent mice and in mice with similar multi-color labels.

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.

Multi-resonance peaks fiber Bragg gratings based on largely-chirped structure

Science.gov (United States)

Chen, Chao; Zhang, Xuan-Yu; Wei, Wei-Hua; Chen, Yong-Yi; Qin, Li; Ning, Yong-Qiang; Yu, Yong-Sen

2018-04-01

A composite fiber Bragg grating (FBG) with multi-resonance peaks (MRPs) has been realized by using femtosecond (fs) laser point-by-point inscription in single-mode fiber. This device contains a segment of largely-chirped gratings with the ultrahigh chirp coefficients and a segment of uniform high-order gratings. The observed MRPs are distributed in an ultra-broadband wavelength range from 1200 nm to 1700 nm in the form of quasi-period or multi-peak-group. For the 8th-order MRPs-FBG, we studied the axial strain and high-temperature sensing characteristics of different resonance peaks experimentally. Moreover, we have demonstrated a multi-wavelength fiber lasers with three-wavelength stable output by using a 9th-order MRPs-FBG as the wavelength selector. This work is significant for the fabrication and functionalization of FBGs with complicated spectra characteristics.

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.

Multi-channel fiber optic dew and humidity sensor

Science.gov (United States)

Limodehi, Hamid E.; Mozafari, Morteza; Amiri, Hesam; Légaré, François

2018-03-01

In this article, we introduce a multi-channel fiber optic dew and humidity sensor which works using a novel method based on relation between surface plasmon resonance (SPR) and water vapor condensation. The proposed sensor can instantly detect moisture or dew formation through its fiber optic channels, separately situated in different places. It enables to simultaneously measure the ambient Relative Humidity (RH) and dew point temperature of several environments with accuracy of 5%.

A Multi-Fiber Spectroscopic Search for Low-mass Young Stars in Orion OB1

Science.gov (United States)

Loerincs, Jacqueline; Briceno, Cesar; Calvet, Nuria; Mateo, Mario L.; Hernandez, Jesus

2017-01-01

We present here results of a low resolution spectroscopic followup of candidate low-mass pre-main sequence stars in the Orion OB1 association. Our targets were selected from the CIDA Variability Survey of Orion (CVSO), and we used the Michigan/Magellan Fiber Spectrograph (M2FS) on the Magellan Clay 6.5m telescope to obtain spectra of 500 candidate T Tauri stars distributed in seven 0.5 deg diameter fields, adding to a total area of ~5.5 deg2. We identify young stars by looking at the distinctive Hα 6563 Å emission and Lithium Li I 6707 Å absorption features characteristic of young low mass pre-main sequence stars. Furthermore, by measuring the strength of their Hα emission lines, confirmed T Tauri stars can be classified as either Classical T Tauris (CTTS) or Weak-line T Tauris (WTTS), which give indication of whether the star is actively accreting material from a gas and dust disk surrounding the star, which may be the precursor of a planetary system. We confirm a total of 90 T Tauri stars, of which 50% are newly identified young members of Orion; out of the 49 new detections,15 are accreting CTTS, and of these all but one are found in the OB1b sub-region. This result is in line with our previous findings that this region is much younger than the more extended Orion OB1a sub-association. The M2FS results add to our growing census of young stars in Orion, that is allowing us to characterize in a systematic and consistent way the distribution of stellar ages across the entire complex, in order to building a complete picture of star formation in this, one of nearest most active sites of star birth.

The LUVOIR Ultraviolet Multi-Object Spectrograph (LUMOS): instrument definition and design

Science.gov (United States)

France, Kevin; Fleming, Brian; West, Garrett; McCandliss, Stephan R.; Bolcar, Matthew R.; Harris, Walter; Moustakas, Leonidas; O'Meara, John M.; Pascucci, Ilaria; Rigby, Jane; Schiminovich, David; Tumlinson, Jason

2017-08-01

The Large Ultraviolet/Optical/Infrared Surveyor (LUVOIR) is one of four large mission concepts currently undergoing community study for consideration by the 2020 Astronomy and Astrophysics Decadal Survey. LUVOIR is being designed to pursue an ambitious program of exoplanetary discovery and characterization, cosmic origins astrophysics, and planetary science. The LUVOIR study team is investigating two large telescope apertures (9- and 15-meter primary mirror diameters) and a host of science instruments to carry out the primary mission goals. Many of the exoplanet, cosmic origins, and planetary science goals of LUVOIR require high-throughput, imaging spectroscopy at ultraviolet (100 - 400 nm) wavelengths. The LUVOIR Ultraviolet Multi-Object Spectrograph, LUMOS, is being designed to support all of the UV science requirements of LUVOIR, from exoplanet host star characterization to tomography of circumgalactic halos to water plumes on outer solar system satellites. LUMOS offers point source and multi-object spectroscopy across the UV bandpass, with multiple resolution modes to support different science goals. The instrument will provide low (R = 8,000 - 18,000) and medium (R = 30,000 - 65,000) resolution modes across the far-ultraviolet (FUV: 100 - 200 nm) and nearultraviolet (NUV: 200 - 400 nm) windows, and a very low resolution mode (R = 500) for spectroscopic investigations of extremely faint objects in the FUV. Imaging spectroscopy will be accomplished over a 3 × 1.6 arcminute field-of-view by employing holographically-ruled diffraction gratings to control optical aberrations, microshutter arrays (MSA) built on the heritage of the Near Infrared Spectrograph (NIRSpec) on the James Webb Space Telescope (JWST), advanced optical coatings for high-throughput in the FUV, and next generation large-format photon-counting detectors. The spectroscopic capabilities of LUMOS are augmented by an FUV imaging channel (100 - 200nm, 13 milliarcsecond angular resolution, 2 × 2

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)

Morphological and spectroscopic analysis of cellulose nanocrystals extracted from oil palm empty fruit bunch fiber

Energy Technology Data Exchange (ETDEWEB)

Dasan, Y. K., E-mail: aamir.bhat@petronas.com.my; Bhat, A. H., E-mail: aamir.bhat@petronas.com.my [Department of Fundamental and Applied Sciences, Universiti Teknologi PETRONAS, 31750, Bandar Seri Iskandar, Perak (Malaysia); Faiz, A., E-mail: faizahmad@petronas.com.my [Department of Mechanical Engineering, Universiti Teknologi PETRONAS, 31750, Bandar Seri Iskandar, Perak (Malaysia)

2015-07-22

This work evaluates the use of oil palm empty fruit bunch (OPEFB) fiber as a source of cellulose to obtain nanocrystalline cellulose (CNC) by acid hydrolysis reaction. The raw OPEFB fibers were pretreated with aqueous Sodium hydroxide at 80°C followed by bleaching treatment and further hydrolyzed with Sulphuric acid at 45°C with limited range of hydrolysis time and acid concentration. The resulting CNC’s were characterized for spectroscopic, crystallographic and morphological properties using Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffractometer (XRD), Transmission Electron Microscope (TEM) and Atomic Force Microscopy (AFM). Finding of this study shows that the properties of CNC’s are strongly dependent on the hydrolysis time and acid concentration.

Multi-kW single fiber laser based on an extra large mode area fiber design

Science.gov (United States)

Langner, Andreas; Such, Mario; Schötz, Gerhard; Just, Florian; Leich, Martin; Schwuchow, Anka; Grimm, Stephan; Zimer, Hagen; Kozak, Marcin; Wedel, Björn; Rehmann, Georg; Bachert, Charley; Krause, Volker

2012-02-01

The quality of Yb-doped fused bulk silica produced by sintering of Yb-doped fused silica granulates has improved greatly in the past five years [1 - 4]. In particular, the refractive index and doping level homogeneity of such materials are excellent and we achieved excellent background fiber attenuation of the active core material down to about 20 dB/km at 1200 nm. The improvement of the Yb-doped fused bulk silica has enabled the development of multi-kW fiber laser systems based on a single extra large multimode laser fiber (XLMA fiber). When a single active fiber is used in combination with the XLMA multimode fiber of 1200 μm diameter simple and robust high power fiber laser setups without complex fiber coupling and fiber combiner systems become possible. In this papper, we will discuss in detail the development of the core material based on Yb-doped bulk silica and the characterization of Yb-doped fibers with different core compositions. We will also report on the excellent performance of a 4 kW fiber laser based on a single XLMA-fiber and show the first experimental welding results of steel sheets achieved with such a laser.

ProtoDESI: First On-Sky Technology Demonstration for the Dark Energy Spectroscopic Instrument

Science.gov (United States)

Fagrelius, Parker; Abareshi, Behzad; Allen, Lori; Ballester, Otger; Baltay, Charles; Besuner, Robert; Buckley-Geer, Elizabeth; Butler, Karen; Cardiel, Laia; Dey, Arjun; Duan, Yutong; Elliott, Ann; Emmet, William; Gershkovich, Irena; Honscheid, Klaus; Illa, Jose M.; Jimenez, Jorge; Joyce, Richard; Karcher, Armin; Kent, Stephen; Lambert, Andrew; Lampton, Michael; Levi, Michael; Manser, Christopher; Marshall, Robert; Martini, Paul; Paat, Anthony; Probst, Ronald; Rabinowitz, David; Reil, Kevin; Robertson, Amy; Rockosi, Connie; Schlegel, David; Schubnell, Michael; Serrano, Santiago; Silber, Joseph; Soto, Christian; Sprayberry, David; Summers, David; Tarlé, Greg; Weaver, Benjamin A.

2018-02-01

The Dark Energy Spectroscopic Instrument (DESI) is under construction to measure the expansion history of the universe using the baryon acoustic oscillations technique. The spectra of 35 million galaxies and quasars over 14,000 square degrees will be measured during a 5-year survey. A new prime focus corrector for the Mayall telescope at Kitt Peak National Observatory will deliver light to 5,000 individually targeted fiber-fed robotic positioners. The fibers in turn feed ten broadband multi-object spectrographs. We describe the ProtoDESI experiment, that was installed and commissioned on the 4-m Mayall telescope from 2016 August 14 to September 30. ProtoDESI was an on-sky technology demonstration with the goal to reduce technical risks associated with aligning optical fibers with targets using robotic fiber positioners and maintaining the stability required to operate DESI. The ProtoDESI prime focus instrument, consisting of three fiber positioners, illuminated fiducials, and a guide camera, was installed behind the existing Mosaic corrector on the Mayall telescope. A fiber view camera was mounted in the Cassegrain cage of the telescope and provided feedback metrology for positioning the fibers. ProtoDESI also provided a platform for early integration of hardware with the DESI Instrument Control System that controls the subsystems, provides communication with the Telescope Control System, and collects instrument telemetry data. Lacking a spectrograph, ProtoDESI monitored the output of the fibers using a fiber photometry camera mounted on the prime focus instrument. ProtoDESI was successful in acquiring targets with the robotically positioned fibers and demonstrated that the DESI guiding requirements can be met.

Multiple Iterations of Bundle Adjustment for the Position Measurement of Fiber Tips on LAMOST

Directory of Open Access Journals (Sweden)

Feng Mingchi

2014-08-01

Full Text Available In the astronomical observation process of multi-object fiber spectroscopic telescope, the position measurement of fiber tips on the focal plane is difficult and critical, and is directly related to subsequent observation and ultimate data quality. The fibers should precisely align with the celestial target. Hence, the precise coordinates of the fiber tips are obligatory for tracking the celestial target. The accurate movement trajectories of the fiber tips on the focal surface of the telescope are the critical problem for the control of the fiber positioning mechanism. According to the special structure of the LAMOST telescope and the composition of the initial position error, this paper aims at developing a high precision and robust measurement method based on multiple iterations of bundle adjustment with a few control points. The measurement theory of the proposed methodology has been analyzed, and the measurement accuracy has been evaluated. The experimental results indicate that the new method is more accurate and more reliable than the polynomial fitting method. The maximum position error of the novel measurement algorithm of fiber tips with simulated and real data is 65.3 μm, and most of the position errors conform to the accuracy requirement (40 μm.

The VIMOS Ultra Deep Survey first data release: Spectra and spectroscopic redshifts of 698 objects up to zspec 6 in CANDELS

Science.gov (United States)

Tasca, L. A. M.; Le Fèvre, O.; Ribeiro, B.; Thomas, R.; Moreau, C.; Cassata, P.; Garilli, B.; Le Brun, V.; Lemaux, B. C.; Maccagni, D.; Pentericci, L.; Schaerer, D.; Vanzella, E.; Zamorani, G.; Zucca, E.; Amorin, R.; Bardelli, S.; Cassarà, L. P.; Castellano, M.; Cimatti, A.; Cucciati, O.; Durkalec, A.; Fontana, A.; Giavalisco, M.; Grazian, A.; Hathi, N. P.; Ilbert, O.; Paltani, S.; Pforr, J.; Scodeggio, M.; Sommariva, V.; Talia, M.; Tresse, L.; Vergani, D.; Capak, P.; Charlot, S.; Contini, T.; de la Torre, S.; Dunlop, J.; Fotopoulou, S.; Guaita, L.; Koekemoer, A.; López-Sanjuan, C.; Mellier, Y.; Salvato, M.; Scoville, N.; Taniguchi, Y.; Wang, P. W.

2017-04-01

This paper describes the first data release (DR1) of the VIMOS Ultra Deep Survey (VUDS). The VUDS-DR1 is the release of all low-resolution spectroscopic data obtained in 276.9 arcmin2 of the CANDELS-COSMOS and CANDELS-ECDFS survey areas, including accurate spectroscopic redshifts zspec and individual spectra obtained with VIMOS on the ESO-VLT. A total of 698 objects have a measured redshift, with 677 galaxies, two type-I AGN, and a small number of 19 contaminating stars. The targets of the spectroscopic survey are selected primarily on the basis of their photometric redshifts to ensure a broad population coverage. About 500 galaxies have zspec > 2, 48of which have zspec > 4; the highest reliable redshifts reach beyond zspec = 6. This data set approximately doubles the number of galaxies with spectroscopic redshifts at z > 3 in these fields. We discuss the general properties of the VUDS-DR1 sample in terms of the spectroscopic redshift distribution, the distribution of Lyman-α equivalent widths, and physical properties including stellar masses M⋆ and star formation rates derived from spectral energy distribution fitting with the knowledge of zspec. We highlight the properties of the most massive star-forming galaxies, noting the wide range in spectral properties, with Lyman-α in emission or in absorption, and in imaging properties with compact, multi-component, or pair morphologies. We present the catalogue database and data products. All VUDS-DR1 data are publicly available and can be retrieved from a dedicated query-based database. Future VUDS data releases will follow this VUDS-DR1 to give access to the spectra and associated measurement of 8000 objects in the full 1 square degree of the VUDS survey. Based on data obtained with the European Southern Observatory Very Large Telescope, Paranal, Chile, under Large Program 185.A-0791. http://cesam.lam.fr/vuds

Tunable and switchable multi-wavelength erbium-doped fiber laser with highly nonlinear photonic crystal fiber and polarization controllers

International Nuclear Information System (INIS)

Liu, X M; Lin, A; Zhao, W; Lu, K Q; Wang, Y S; Zhang, T Y; Chung, Y

2008-01-01

We have proposed a novel multi-wavelength erbium-doped fiber laser by using two polarization controllers and a sampled chirped fiber Bragg grating(SC-FBG). On the assistance of SC-FBG, the proposed fiber lasers with excellent stability and uniformity are tunable and switchable by adjusting the polarization controllers. Our laser can stably lase two waves and up to eight waves simultaneously at room temperature

A New and Simple Method for Crosstalk Estimation in Homogeneous Trench-Assisted Multi-Core Fibers

DEFF Research Database (Denmark)

Ye, Feihong; Tu, Jiajing; Saitoh, Kunimasa

2014-01-01

A new and simple method for inter-core crosstalk estimation in homogeneous trench-assisted multi-core fibers is presented. The crosstalk calculated by this method agrees well with experimental measurement data for two kinds of fabricated 12-core fibers.......A new and simple method for inter-core crosstalk estimation in homogeneous trench-assisted multi-core fibers is presented. The crosstalk calculated by this method agrees well with experimental measurement data for two kinds of fabricated 12-core fibers....

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

Multiparameter-dependent spontaneous emission in PbSe quantum dot-doped liquid-core multi-mode fiber

International Nuclear Information System (INIS)

Zhang, Lei; Zhang, Yu; Wu, Hua; Zhang, Tieqiang; Gu, Pengfei; Chu, Hairong; Cui, Tian; Wang, Yiding; Zhang, Hanzhuang; Zhao, Jun; Yu, William W.

2013-01-01

A theoretical model was established in this paper to analyze the properties of 3.50 and 4.39 nm PbSe quantum dot-doped liquid-core multi-mode fiber. This model was applicable to both single- and multi-mode fiber. The three-level system-based light-propagation equations and rate equations were used to calculate the guided spontaneous emission spectra. Considering the multi-mode in the fiber, the normalized intensity distribution of transversal model was improved and simplified. The detailed calculating results were thus obtained and explained using the above-mentioned model. The redshift of the peak position and the evolution of the emission power were observed and analyzed considering the influence of the fiber length, fiber diameter, doping concentration, and the pump power. The redshift increased with the increases of fiber length, fiber diameter, and doping concentration. The optimal fiber length, fiber diameter, and doping concentration were analyzed and confirmed, and the related spontaneous emission power was obtained. Besides, the normalized emission intensity increased with the increase of pump power in a nearly linear way. The calculating results fitted well to the experimental data

4MOST: the 4-metre Multi-Object Spectroscopic Telescope project at preliminary design review

NARCIS (Netherlands)

de Jong, Roelof S.; Barden, Samuel C.; Bellido-Tirado, Olga; Brynnel, Joar G.; Frey, Steffen; Giannone, Domenico; Haynes, Roger; Johl, Diana; Phillips, Daniel; Schnurr, Olivier; Walcher, Jakob C.; Winkler, Roland; Ansorge, Wolfgang R.; Feltzing, Sofia; McMahon, Richard G.; Baker, Gabriella; Caillier, Patrick; Dwelly, Tom; Gaessler, Wolfgang; Iwert, Olaf; Mandel, Holger G.; Piskunov, Nikolai A.; Pragt, Johan H.; Walton, Nicholas A.; Bensby, Thomas; Bergemann, Maria; Chiappini, Cristina; Christlieb, Norbert; Cioni, Maria-Rosa L.; Driver, Simon; Finoguenov, Alexis; Helmi, Amina; Irwin, Michael J.; Kitaura, Francisco-Shu; Kneib, Jean-Paul; Liske, Jochen; Merloni, Andrea; Minchev, Ivan; Richard, Johan; Starkenburg, Else

2016-01-01

We present an overview of the 4MOST project at the Preliminary Design Review. 4MOST is a major new wide-field, high-multiplex spectroscopic survey facility under development for the VISTA telescope of ESO. 4MOST has a broad range of science goals ranging from Galactic Archaeology and stellar physics

Novel Wireless-Communicating Textiles Made from Multi-Material and Minimally-Invasive Fibers

Directory of Open Access Journals (Sweden)

Stepan Gorgutsa

2014-10-01

Full Text Available The ability to integrate multiple materials into miniaturized fiber structures enables the realization of novel biomedical textile devices with higher-level functionalities and minimally-invasive attributes. In this work, we present novel textile fabrics integrating unobtrusive multi-material fibers that communicate through 2.4 GHz wireless networks with excellent signal quality. The conductor elements of the textiles are embedded within the fibers themselves, providing electrical and chemical shielding against the environment, while preserving the mechanical and cosmetic properties of the garments. These multi-material fibers combine insulating and conducting materials into a well-defined geometry, and represent a cost-effective and minimally-invasive approach to sensor fabrics and bio-sensing textiles connected in real time to mobile communications infrastructures, suitable for a variety of health and life science applications.

DMD-based multi-object spectrograph on Galileo telescope

Science.gov (United States)

Zamkotsian, Frederic; Spano, Paolo; Lanzoni, Patrick; Bon, William; Riva, Marco; Nicastro, Luciano; Molinari, Emilio; Di Marcantonio, Paolo; Zerbi, Filippo; Valenziano, Luca

2013-03-01

Next-generation infrared astronomical instrumentation for ground-based and space telescopes could be based on MOEMS programmable slit masks for multi-object spectroscopy (MOS). This astronomical technique is used extensively to investigate the formation and evolution of galaxies. We propose to develop a 2048x1080 DMD-based MOS instrument to be mounted on the Galileo telescope and called BATMAN. A two-arm instrument has been designed for providing in parallel imaging and spectroscopic capabilities. The two arms with F/4 on the DMD are mounted on a common bench, and an upper bench supports the detectors thanks to two independent hexapods. Very good optical quality on the DMD and the detectors will be reached. ROBIN, a BATMAN demonstrator, has been designed, realized and integrated. It permits to determine the instrument integration procedure, including optics and mechanics integration, alignment procedure and optical quality. First images have been obtained and measured. A DMD pattern manager has been developed in order to generate any slit mask according to the list of objects to be observed; spectra have been generated and measured. Observation strategies will be studied and demonstrated for the scientific optimization strategy over the whole FOV. BATMAN on the sky is of prime importance for characterizing the actual performance of this new family of MOS instruments, as well as investigating the operational procedures on astronomical objects. This instrument will be placed on the Telescopio Nazionale Galileo at the beginning of next year, in 2014.

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.

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...

Effect of hybrid fiber reinforcement on the cracking process in fiber reinforced cementitious composites

DEFF Research Database (Denmark)

Pereira, Eduardo B.; Fischer, Gregor; Barros, Joaquim A.O.

2012-01-01

The simultaneous use of different types of fibers as reinforcement in cementitious matrix composites is typically motivated by the underlying principle of a multi-scale nature of the cracking processes in fiber reinforced cementitious composites. It has been hypothesized that while undergoing...... tensile deformations in the composite, the fibers with different geometrical and mechanical properties restrain the propagation and further development of cracking at different scales from the micro- to the macro-scale. The optimized design of the fiber reinforcing systems requires the objective...... materials is carried out by assessing directly their tensile stress-crack opening behavior. The efficiency of hybrid fiber reinforcements and the multi-scale nature of cracking processes are discussed based on the experimental results obtained, as well as the micro-mechanisms underlying the contribution...

The LAMOST spectroscopic survey of stars in the Kepler field of view: Activity indicators and stellar parameters

Science.gov (United States)

Molenda-Żakowicz, Joanna; Frasca, Antonio; De Cat, Peter; Catanzaro, Giovanni

2017-09-01

We summarize the results of the completed first round of the LAMOST-Kepler project, and describe the status of its on-going second round. As a result of the first round of this project, the atmospheric parameters (Teff, log g, and [Fe/H]), the spectral classification (spectral type and luminosity class), and the radial velocities (RV) have been measured for 51,385 stars. For 4031 stars, we were able to measure the projected rotational velocity, while the minimum detectable v sin i was 120 km s-1. For 8821 stars with more than one observation, we computed the χ-square probability that the detected RV variations have a random occurrence. Finally, we classified 442 stars as chromospherically active on the basis of the analysis of their Hα and Ca II-IRT fluxes. All our results have been obtained from the low-resolution (R ˜ 1800) spectroscopic observations acquired with the LAMOST instrument. Based on observations collected with the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) located at the Xinglong Observatory, China.

Fiber-ring laser-based intracavity photoacoustic spectroscopy for trace gas sensing.

Science.gov (United States)

Wang, Qiang; Wang, Zhen; Chang, Jun; Ren, Wei

2017-06-01

We demonstrated a novel trace gas sensing method based on fiber-ring laser intracavity photoacoustic spectroscopy. This spectroscopic technique is a merging of photoacoustic spectroscopy (PAS) with a fiber-ring cavity for sensitive and all-fiber gas detection. A transmission-type PAS gas cell (resonant frequency f0=2.68  kHz) was placed inside the fiber-ring laser to fully utilize the intracavity laser power. The PAS signal was excited by modulating the laser wavelength at f0/2 using a custom-made fiber Bragg grating-based modulator. We used this spectroscopic technique to detect acetylene (C2H2) at 1531.6 nm as a proof of principle. With a low Q-factor (4.9) of the PAS cell, our sensor achieved a good linear response (R2=0.996) to C2H2 concentration and a minimum detection limit of 390 ppbv at 2-s response time.

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...

Multi-material micro-electromechanical fibers with bendable functional domains

Science.gov (United States)

Nguyen-Dang, Tung; Page, Alexis G.; Qu, Yunpeng; Volpi, Marco; Yan, Wei; Sorin, Fabien

2017-04-01

The integration of increasingly complex functionalities within thermally drawn multi-material fibers is heralding a novel path towards advanced soft electronics and smart fabrics. Fibers capable of electronic, optoelectronic, piezoelectric or energy harvesting functions are created by assembling new materials in intimate contact within increasingly complex architectures. Thus far, however, the opportunities associated with the integration of cantilever-like structures with freely moving functional domains within multi-material fibers have not been explored. Used extensively in the micro-electromechanical system (MEMS) technology, electro-mechanical transductance from moving and bendable domains is used in a myriad of applications. In this article we demonstrate the thermal drawing of micro-electromechanical fibers (MEMF) that can detect and localize pressure with high accuracy along their entire length. This ability results from an original cantilever-like design where a freestanding electrically conductive polymer composite film bends under an applied pressure. As it comes into contact with another conducting domain, placed at a prescribed position in the fiber cross-section, an electrical signal is generated. We show that by a judicious choice of materials and electrical connectivity, this signal can be uniquely related to a position along the fiber axis. We establish a model that predicts the position of a local touch from the measurement of currents generated in the 1D MEMF device, and demonstrate an excellent agreement with the experimental data. This ability to detect and localize touch over large areas, curved surfaces and textiles holds significant opportunities in robotics and prosthetics, flexible electronic interfaces, and medical textiles. , which features invited work from the best early-career researchers working within the scope of J. Phys. D. This project is part of the Journal of Physics series’ 50th anniversary celebrations in 2017. Fabien Sorin

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.

Theoretical Investigation of Inter-core Crosstalk Properties in Homogeneous Trench-Assisted Multi-Core Fibers

DEFF Research Database (Denmark)

Ye, Feihong; Morioka, Toshio; Tu, Jiajing

2014-01-01

We derive analytical expressions for inter-core crosstalk, its dependence on core pitch and wavelength in homogeneous trench-assisted multi-core fibers. They are in excellent agreement with numerical simulation results.......We derive analytical expressions for inter-core crosstalk, its dependence on core pitch and wavelength in homogeneous trench-assisted multi-core fibers. They are in excellent agreement with numerical simulation results....

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.

Novel hollow fiber compressor for high power, multi-mJ ultrafast lasers

International Nuclear Information System (INIS)

Nagy, T.; Simon, P.; Schweinberger, W.; Sommer, A.; Schultze, M.; Kienberger, R.; Krausz, F.

2010-01-01

Complete text of publication follows. The current trends in ultrafast laser development include, besides the reduction of the pulse duration, also the up-scaling of the pulse energy and the increase of the repetition rate. Recently, multi-mJ, multi-kHz lasers delivering sub-30 fs pulses have become available. The compression of the output pulses of such lasers to sub-5 fs duration is a challenging task. In order to maintain good temporal contrast and beam profile, the preferred way for spectral broadening is to use noble-gas-filled hollow fibers. For launching multi-mJ pulses in the waveguide, its inner diameter has to be large in order to keep the intensity at low levels so that the ionization losses are still tolerable. For optimal in-coupling the differential pressure scheme is very favourable, which, however requires longer waveguide lengths to compensate for the reduced effective interaction length caused by the pressure gradient. Recently, a novel hollow fiber construction has been developed comprising a waveguide formed by a stretched flexible capillary tube. This special construction resolves the usual strong limitation of the length of the waveguide, provides excellent straightness, and inherently supports the differential pressure scheme. The only drawback of the flexible fiber unit to date was its susceptibility to thermal damage in case of high average power input beams. To solve this problem we present a novel composite fiber unit, which consists of a thick-walled taper followed by a long flexible fiber. This construction combines the advantages of both types: the high resistibility of the taper and the free length-scalability of a flexible fiber. In order to demonstrate the potential of the new fiber design, a 2 m long composite fiber with an inner diameter of 320 μm was placed at the output of a CPA Ti:Sa laser system comprising an oscillator, a grating-prism (grism) stretcher, two multi-pass amplifier stages and a compressor combining bulk glass

Multi-Stress Monitoring System with Fiber-Optic Mandrels and Fiber Bragg Grating Sensors in a Sagnac Loop.

Science.gov (United States)

Kim, Hyunjin; Sampath, Umesh; Song, Minho

2015-07-29

Fiber Bragg grating sensors are placed in a fiber-optic Sagnac loop to combine the grating temperature sensors and the fiber-optic mandrel acoustic emission sensors in single optical circuit. A wavelength-scanning fiber-optic laser is used as a common light source for both sensors. A fiber-optic attenuator is placed at a specific position in the Sagnac loop in order to separate buried Bragg wavelengths from the Sagnac interferometer output. The Bragg wavelength shifts are measured with scanning band-pass filter demodulation and the mandrel output is analyzed by applying a fast Fourier transform to the interference signal. This hybrid-scheme could greatly reduce the size and the complexity of optical circuitry and signal processing unit, making it suitable for low cost multi-stress monitoring of large scale power systems.

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..

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...

A multi-scale investigation of the mechanical behavior of durable sisal fiber cement composites

OpenAIRE

Silva, Flávio de Andrade; Toledo Filho, Romildo D.; Mobasher, Barzin; Chawla, Nikhilesh

2010-01-01

Durable sisal fiber cement composites reinforced with long unidirectional aligned fibers were developed and their mechanical behavior was characterized in a multi-scale level. Tensile tests were performed in individual sisal fibers. Weibull statistics were used to quantify the degree of variability in fiber strength at different gage lengths. The fiber-matrix pull-out behavior was evaluated at several curing ages and embedded lengths. The composite's mechanical response was measured under dir...

Sky Subtraction with Fiber-Fed Spectrograph

Science.gov (United States)

Rodrigues, Myriam

2017-09-01

"Historically, fiber-fed spectrographs had been deemed inadequate for the observation of faint targets, mainly because of the difficulty to achieve high accuracy on the sky subtraction. The impossibility to sample the sky in the immediate vicinity of the target in fiber instruments has led to a commonly held view that a multi-object fibre spectrograph cannot achieve an accurate sky subtraction under 1% contrary to their slit counterpart. The next generation of multi-objects spectrograph at the VLT (MOONS) and the planed MOS for the E-ELT (MOSAIC) are fiber-fed instruments, and are aimed to observed targets fainter than the sky continuum level. In this talk, I will present the state-of-art on sky subtraction strategies and data reduction algorithm specifically developed for fiber-fed spectrographs. I will also present the main results of an observational campaign to better characterise the sky spatial and temporal variations ( in particular the continuum and faint sky lines)."

Smart-phone based computational microscopy using multi-frame contact imaging on a fiber-optic array.

Science.gov (United States)

Navruz, Isa; Coskun, Ahmet F; Wong, Justin; Mohammad, Saqib; Tseng, Derek; Nagi, Richie; Phillips, Stephen; Ozcan, Aydogan

2013-10-21

We demonstrate a cellphone based contact microscopy platform, termed Contact Scope, which can image highly dense or connected samples in transmission mode. Weighing approximately 76 grams, this portable and compact microscope is installed on the existing camera unit of a cellphone using an opto-mechanical add-on, where planar samples of interest are placed in contact with the top facet of a tapered fiber-optic array. This glass-based tapered fiber array has ~9 fold higher density of fiber optic cables on its top facet compared to the bottom one and is illuminated by an incoherent light source, e.g., a simple light-emitting-diode (LED). The transmitted light pattern through the object is then sampled by this array of fiber optic cables, delivering a transmission image of the sample onto the other side of the taper, with ~3× magnification in each direction. This magnified image of the object, located at the bottom facet of the fiber array, is then projected onto the CMOS image sensor of the cellphone using two lenses. While keeping the sample and the cellphone camera at a fixed position, the fiber-optic array is then manually rotated with discrete angular increments of e.g., 1-2 degrees. At each angular position of the fiber-optic array, contact images are captured using the cellphone camera, creating a sequence of transmission images for the same sample. These multi-frame images are digitally fused together based on a shift-and-add algorithm through a custom-developed Android application running on the smart-phone, providing the final microscopic image of the sample, visualized through the screen of the phone. This final computation step improves the resolution and also removes spatial artefacts that arise due to non-uniform sampling of the transmission intensity at the fiber optic array surface. We validated the performance of this cellphone based Contact Scope by imaging resolution test charts and blood smears.

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

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...

Multi-Objective Structural Optimization Design of Horizontal-Axis Wind Turbine Blades Using the Non-Dominated Sorting Genetic Algorithm II and Finite Element Method

Directory of Open Access Journals (Sweden)

Jie Zhu

2014-02-01

Full Text Available A multi-objective optimization method for the structural design of horizontal-axis wind turbine (HAWT blades is presented. The main goal is to minimize the weight and cost of the blade which uses glass fiber reinforced plastic (GFRP coupled with carbon fiber reinforced plastic (CFRP materials. The number and the location of layers in the spar cap, the width of the spar cap and the position of the shear webs are employed as the design variables, while the strain limit, blade/tower clearance limit and vibration limit are taken into account as the constraint conditions. The optimization of the design of a commercial 1.5 MW HAWT blade is carried out by combining FEM analysis and a multi-objective evolutionary algorithm under ultimate (extreme flap-wise load and edge-wise load conditions. The best solutions are described and the comparison of the obtained results with the original design is performed to prove the efficiency and applicability of the method.

Scaling Fiber Lasers to Large Mode Area: An Investigation of Passive Mode-Locking Using a Multi-Mode Fiber.

Science.gov (United States)

Ding, Edwin; Lefrancois, Simon; Kutz, Jose Nathan; Wise, Frank W

2011-01-01

The mode-locking of dissipative soliton fiber lasers using large mode area fiber supporting multiple transverse modes is studied experimentally and theoretically. The averaged mode-locking dynamics in a multi-mode fiber are studied using a distributed model. The co-propagation of multiple transverse modes is governed by a system of coupled Ginzburg-Landau equations. Simulations show that stable and robust mode-locked pulses can be produced. However, the mode-locking can be destabilized by excessive higher-order mode content. Experiments using large core step-index fiber, photonic crystal fiber, and chirally-coupled core fiber show that mode-locking can be significantly disturbed in the presence of higher-order modes, resulting in lower maximum single-pulse energies. In practice, spatial mode content must be carefully controlled to achieve full pulse energy scaling. This paper demonstrates that mode-locking performance is very sensitive to the presence of multiple waveguide modes when compared to systems such as amplifiers and continuous-wave lasers.

Tuning the dispersion and single/multi-modeness of a hole-assisted fiber by the hole's geometrical parameters

NARCIS (Netherlands)

Uranus, H.P.; Hoekstra, Hugo; van Groesen, Embrecht W.C.

2008-01-01

Using a vectorial finite element mode solver developed earlier, we studied a hole-assisted multi-ring fiber. We report the role of the hole’s geometrical parameters in tuning the waveguide dispersion and the single/multi-modeness of the particular fiber. By correctly selecting the hole’s size and

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.

Study of interaction of butyl p-hydroxybenzoate with human serum albumin by molecular modeling and multi-spectroscopic method

Energy Technology Data Exchange (ETDEWEB)

Wang Qin, E-mail: wqing07@lzu.c [Department of Chemistry, Lanzhou University, Lanzhou 730000 (China); Zhang Yaheng, E-mail: zhangyah04@lzu.c [Department of Chemistry, Lanzhou University, Lanzhou 730000 (China); Sun Huijun, E-mail: sun.hui.jun-04@163.co [Department of Chemistry, Lanzhou University, Lanzhou 730000 (China); Chen Hongli, E-mail: hlchen@lzu.edu.c [Department of Chemistry, Lanzhou University, Lanzhou 730000 (China); Chen Xingguo, E-mail: chenxg@lzu.edu.c [Department of Chemistry, Lanzhou University, Lanzhou 730000 (China)

2011-02-15

Study of the interaction between butyl p-hydroxybenzoate (butoben) and human serum albumin (HSA) has been performed by molecular modeling and multi-spectroscopic method. The interaction mechanism was predicted through molecular modeling first, then the binding parameters were confirmed using a series of spectroscopic methods, including fluorescence spectroscopy, UV-visible absorbance spectroscopy, circular dichroism (CD) spectroscopy and Fourier transform infrared (FT-IR) spectroscopy. The thermodynamic parameters of the reaction, standard enthalpy {Delta}H{sup 0} and entropy {Delta}S{sup 0}, have been calculated to be -29.52 kJ mol{sup -1} and -24.23 J mol{sup -1} K{sup -1}, respectively, according to the Van't Hoff equation, which suggests the van der Waals force and hydrogen bonds are the predominant intermolecular forces in stabilizing the butoben-HSA complex. Results obtained by spectroscopic methods are consistent with that of the molecular modeling study. In addition, alteration of secondary structure of HSA in the presence of butoben was evaluated using the data obtained from UV-visible absorbance, CD and FT-IR spectroscopies. - Research highlights: The interaction between butyl p-hydroxybenzoate with HSA has been investigated for the first time. Molecular modeling study can provide theoretical direction for experimental design. Multi-spectroscopic method can provide the binding parameters and thermodynamic parameters. These results are important for food safety and human health when using parabens as a preservative.

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

Electrostatic chuck consisting of polymeric electrostatic inductive fibers for handling of objects with rough surfaces

International Nuclear Information System (INIS)

Dhelika, Radon; Sawai, Kenji; Saito, Shigeki; Takahashi, Kunio; Takarada, Wataru; Kikutani, Takeshi

2013-01-01

An electrostatic chuck (ESC) is a type of reversible dry adhesive which clamps objects by means of electrostatic force. Currently an ESC is used only for objects having flat surfaces because the attractive force is reduced for rough surfaces. An ESC that can handle objects with rough surfaces will expand its applications to MEMS (micro electro mechanical system) or optical parts handling. An ESC consisting of compliant electrostatic inductive fibers which conform to the profile of the surface has been proposed for such use. This paper aims at furthering previous research by observing the attractive force/pressure generated, both theoretically and experimentally, through step-by-step fabrication and analysis. Additionally, how the proposed fiber ESC behaves toward rough surfaces is also observed. The attractive force/pressure of the fiber ESC is theoretically investigated using a robust mechano-electrostatic model. Subsequently, a prototype of the fiber ESC consisting of ten fibers arranged at an angle is employed to experimentally observe its attractive force/pressure for objects with rough surfaces. The attractive force of the surface which is modeled as a sinusoidal wave with various amplitudes is observed, through which the feasibility of a fiber ESC is justified. (paper)

Development of a TiO2-coated optical fiber reactor for water decontamination

International Nuclear Information System (INIS)

Danion, A.

2004-09-01

The objective of this study was to built and to study a photo-reactor composed by TiO 2 -coated optical fibers for water decontamination. The physico-chemical characteristics and the optical properties of the TiO 2 coating were first studied. Then, the influences of different parameters as the coating thickness, the coating length and the coating volume were investigated both on the light transmission in the TiO 2 - coated fiber and on the photo-catalytic activity of the fiber for a model compound (malic acid). The photo-catalytic degradation of malic acid was optimized using the experimental design methodology allowing to build a multi-fiber reactor comprising 57 optical fibers. The photo-degradation of malic acid was conducted in the multi-fiber reactor and it was demonstrated that the multi-fiber reactor was more efficient than the single-fiber reactor at the same fibers density. Finally, the multi-fiber reactor was applied to the photo-degradation of a fungicide, called fenamidone, and a degradation pathway was proposed. (author)

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

Simple analytical expression for crosstalk estimation in homogeneous trench-assisted multi-core fibers

DEFF Research Database (Denmark)

Ye, Feihong; Tu, Jiajing; Saitoh, Kunimasa

2014-01-01

An analytical expression for the mode coupling coe cient in homogeneous trench-assisted multi-core fibers is derived, which has a sim- ple relationship with the one in normal step-index structures. The amount of inter-core crosstalk reduction (in dB) with trench-assisted structures compared...... to the one with normal step-index structures can then be written by a simple expression. Comparison with numerical simulations confirms that the obtained analytical expression has very good accuracy for crosstalk estimation. The crosstalk properties in trench-assisted multi-core fibers, such as crosstalk...... dependence on core pitch and wavelength-dependent crosstalk, can be obtained by this simple analytical expression....

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.

Subaru Weak-Lensing Survey II: Multi-Object Spectroscopy and Cluster Masses

Science.gov (United States)

Hamana, Takashi; Miyazaki, Satoshi; Kashikawa, Nobunari; Ellis, Richard S.; Massey, Richard J.; Refregier, Alexandre; Taylor, James E.

2009-08-01

We present the first results of a multi-object spectroscopic campaign to follow up cluster candidates located via weak lensing. Our main goals are to search for spatial concentrations of galaxies that are plausible optical counterparts of the weak-lensing signals, and to determine the cluster redshifts from those of member galaxies. Around each of 36 targeted cluster candidates, we obtained 15-32 galaxy redshifts. For 28 of these targets, we confirmed a secure cluster identification, with more than five spectroscopic galaxies within a velocity of ±3000km s-1. This includes three cases where two clusters at different redshifts are projected along the same line-of-sight. In 6 of the 8 unconfirmed targets, we found multiple small galaxy concentrations at different redshifts, each containing at least three spectroscopic galaxies. The weak-lensing signal around those systems was thus probably created by the projection of groups or small clusters along the same line-of-sight. In both of the remaining two targets, a single small galaxy concentration was found. In some candidate super-cluster systems, we found additional evidence of filaments connecting the main density peak to an additional nearby structure. For a subsample of our most cleanly measured clusters, we investigated the statistical relation between their weak-lensing mass (MNFW, σSIS) and the velocity dispersion of their member galaxies (σv), comparing our sample with optically and X-ray selected samples from the literature. Our lensing-selected clusters are consistent with σv = σSIS, with a similar scatter to that of optically and X-ray selected clusters. We also derived an empirical relation between the cluster mass and the galaxy velocity dispersion, M200E(z) = 11.0 × 1014 × (σv/1000km s-1)3.0 h-1 Modot, which is in reasonable agreement with predictions of N-body simulations in the Λ CDM cosmology.

Multi-dimensional fiber-optic radiation sensor for ocular proton therapy dosimetry

International Nuclear Information System (INIS)

Jang, K.W.; Yoo, W.J.; Moon, J.; Han, K.T.; Park, B.G.; Shin, D.; Park, S-Y.; Lee, B.

2012-01-01

In this study, we fabricated a multi-dimensional fiber-optic radiation sensor, which consists of organic scintillators, plastic optical fibers and a water phantom with a polymethyl methacrylate structure for the ocular proton therapy dosimetry. For the purpose of sensor characterization, we measured the spread out Bragg-peak of 120 MeV proton beam using a one-dimensional sensor array, which has 30 fiber-optic radiation sensors with a 1.5 mm interval. A uniform region of spread out Bragg-peak using the one-dimensional fiber-optic radiation sensor was obtained from 20 to 25 mm depth of a phantom. In addition, the Bragg-peak of 109 MeV proton beam was measured at the depth of 11.5 mm of a phantom using a two-dimensional sensor array, which has 10×3 sensor array with a 0.5 mm interval.

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)

Wavelength-Dependence of Inter-Core Crosstalk in Homogeneous Multi-Core Fibers

DEFF Research Database (Denmark)

Ye, Feihong; Saitoh, Kunimasa; Takenaga, Katsuhiro

2016-01-01

The wavelength dependence of inter-core crosstalk in homogeneous multi-core fibers (MCFs) is investigated, and the corresponding analytical expressions are derived. The derived analytical expressions can be used to determine the crosstalk at any wavelength necessary for designing future MCF...

BATMAN: a DMD-based multi-object spectrograph on Galileo telescope

Science.gov (United States)

Zamkotsian, Frederic; Spano, Paolo; Lanzoni, Patrick; Ramarijaona, Harald; Moschetti, Manuele; Riva, Marco; Bon, William; Nicastro, Luciano; Molinari, Emilio; Cosentino, Rosario; Ghedina, Adriano; Gonzalez, Manuel; Di Marcantonio, Paolo; Coretti, Igor; Cirami, Roberto; Zerbi, Filippo; Valenziano, Luca

2014-07-01

Next-generation infrared astronomical instrumentation for ground-based and space telescopes could be based on MOEMS programmable slit masks for multi-object spectroscopy (MOS). This astronomical technique is used extensively to investigate the formation and evolution of galaxies. We are developing a 2048x1080 Digital-Micromirror-Device-based (DMD) MOS instrument to be mounted on the Galileo telescope and called BATMAN. A two-arm instrument has been designed for providing in parallel imaging and spectroscopic capabilities. The field of view (FOV) is 6.8 arcmin x 3.6 arcmin with a plate scale of 0.2 arcsec per micromirror. The wavelength range is in the visible and the spectral resolution is R=560 for 1 arcsec object (typical slit size). The two arms will have 2k x 4k CCD detectors. ROBIN, a BATMAN demonstrator, has been designed, realized and integrated. It permits to determine the instrument integration procedure, including optics and mechanics integration, alignment procedure and optical quality. First images and spectra have been obtained and measured: typical spot diameters are within 1.5 detector pixels, and spectra generated by one micro-mirror slits are displayed with this optical quality over the whole visible wavelength range. Observation strategies are studied and demonstrated for the scientific optimization strategy over the whole FOV. BATMAN on the sky is of prime importance for characterizing the actual performance of this new family of MOS instruments, as well as investigating the operational procedures on astronomical objects. This instrument will be placed on the Telescopio Nazionale Galileo mid-2015.

Towards single step production of multi-layer inorganic hollow fibers

NARCIS (Netherlands)

de Jong, J.; Benes, Nieck Edwin; Koops, G.H.; Wessling, Matthias

2004-01-01

In this work we propose a generic synthesis route for the single step production of multi-layer inorganic hollow fibers, based on polymer wet spinning combined with a heat treatment. With this new method, membranes with a high surface area per unit volume ratio can be produced, while production time

Brightness enhancement of a multi-mode ribbon fiber using transmitting Bragg gratings

Science.gov (United States)

Anderson, B. M.; Venus, G.; Ott, D.; Divliansky, I.; Dawson, J. W.; Drachenberg, D. R.; Messerly, M. J.; Pax, P. H.; Tassano, J. B.; Glebov, L. B.

2015-03-01

Increasing the dimensions of a waveguide provides the simplest means of reducing detrimental nonlinear effects, but such systems are inherently multi-mode, reducing the brightness of the system. Furthermore, using rectangular dimensions allows for improved heat extraction, as well as uniform temperature profile within the core. We propose a method of using the angular acceptance of a transmitting Bragg grating (TBG) to filter the fundamental mode of a fiber laser resonator, and as a means to increase the brightness of multi-mode fiber laser. Numerical modeling is used to calculate the diffraction losses needed to suppress the higher order modes in a laser system with saturable gain. The model is tested by constructing an external cavity resonator using an ytterbium doped ribbon fiber with core dimensions of 107.8μm by 8.3μm as the active medium. We show that the TBG increases the beam quality of the system from M2 = 11.3 to M2 = 1.45, while reducing the slope efficiency from 76% to 53%, overall increasing the brightness by 5.1 times.

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

Spectroscopic investigations on oxidized multi-walled carbon nanotubes

Energy Technology Data Exchange (ETDEWEB)

Anandhi, C. M. S.; Premkumar, S.; Asath, R. Mohamed; Mathavan, T.; Benial, A. Milton Franklin, E-mail: miltonfranklin@yahoo.com [Department of Physics, N.M.S.S.V.N. College, Madurai-625 019, Tamil Nadu (India)

2016-05-06

The pristine multi-walled carbon nanotubes (MWCNTs) were oxidized by the ultrasonication process. The oxidized MWCNTs were characterized by the X-ray diffraction (XRD), ultraviolet–visible (UV-Vis) and Fourier transform -Raman (FT-Raman) spectroscopic techniques. The XRD analysis confirms that the oxidized MWCNTs exist in a hexagonal structure and the sharp XRD peak corresponds to the (002) Bragg’s reflection plane, which indicates that the MWCNTs have higher crystalline nature. The UV-Vis analysis confirms that the MWCNTs functionalized with the carboxylic acid. The red shift was observed corresponds to the D band in the Raman spectrum, which reveals that the reduced disordered graphitic structure of oxidized MWCNTs. The strong Raman peak was observed at 2563 cm{sup -1} corresponds to the overtone of the D band, which is the characteristic vibrational mode of oxidized MWCNTs. The carboxylic acid functionalization of MWCNTs enhances the dispersibility, which paves the way for potential applications in the field of biosensors and targeted drug delivery.

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...

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.

Ultra-Weak Fiber Bragg Grating Sensing Network Coated with Sensitive Material for Multi-Parameter Measurements

Directory of Open Access Journals (Sweden)

Wei Bai

2017-06-01

Full Text Available A multi-parameter measurement system based on ultra-weak fiber Bragg grating (UFBG array with sensitive material was proposed and experimentally demonstrated. The UFBG array interrogation principle is time division multiplex technology with two semiconductor optical amplifiers as timing units. Experimental results showed that the performance of the proposed UFBG system is almost equal to that of traditional FBG, while the UFBG array system has obvious superiority with potential multiplexing ability for multi-point and multi-parameter measurement. The system experimented on a 144 UFBG array with the reflectivity of UFBG ~0.04% for the four target parameters: hydrogen, humidity, temperature and salinity. Moreover, a uniform solution was customized to divide the cross-sensitivity between temperature and other target parameters. It is expected that this scheme will be capable of handling thousands of multi-parameter sensors in a single fiber.

Ultra-Weak Fiber Bragg Grating Sensing Network Coated with Sensitive Material for Multi-Parameter Measurements.

Science.gov (United States)

Bai, Wei; Yang, Minghong; Hu, Chenyuan; Dai, Jixiang; Zhong, Xuexiang; Huang, Shuai; Wang, Gaopeng

2017-06-26

A multi-parameter measurement system based on ultra-weak fiber Bragg grating (UFBG) array with sensitive material was proposed and experimentally demonstrated. The UFBG array interrogation principle is time division multiplex technology with two semiconductor optical amplifiers as timing units. Experimental results showed that the performance of the proposed UFBG system is almost equal to that of traditional FBG, while the UFBG array system has obvious superiority with potential multiplexing ability for multi-point and multi-parameter measurement. The system experimented on a 144 UFBG array with the reflectivity of UFBG ~0.04% for the four target parameters: hydrogen, humidity, temperature and salinity. Moreover, a uniform solution was customized to divide the cross-sensitivity between temperature and other target parameters. It is expected that this scheme will be capable of handling thousands of multi-parameter sensors in a single fiber.

Fabrication and formation mechanism of poly (L-lactic acid ultrafine multi-porous hollow fiber by electrospinning

Directory of Open Access Journals (Sweden)

Q. Z. Yu

2013-01-01

Full Text Available Poly(L-lactic acid (PLLA ultrafine multi-porous hollow fibers are fabricated by electrospinning with methylene dichloride as solvent. The Kirkendall effect has been widely applied for the fabrication of hollow structure in metals and inorganic materials. In this study, a conceptual extension is proposed for the formation mechanism: the development of porous hollow fiber undergoes three stages. The initial stage is the generation of small voids or pits on the surface of the fiber via surface diffusion and phase separation; the second stage is the formation of multi-pores penetrating the core of the fiber through the interaction of Kirkendall effect, surface diffusion and phase separation; the third stage is dominated by surface diffusion of the core material along the pore surface. To explore the formation conditions, the factors including ambient temperature, relativity humidity (R. H., molecular weight and fiber diameter are studied. The longitudinal and cross sectional morphologies of these fibers are examined by scanning electron micrograph (SEM. The results show that the prerequisite for the formation of uniform porous hollow PLLA fibers include moderate ambient temperature (10~20°C and appropriate molecular weight for the PLLA, as well as the diameter of the fiber in the range of several micrometers to about 100 nanometers.

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.

Spectroscopic Surveys with the ELT: A Gigantic Step into the Deep Universe

Science.gov (United States)

Evans, C.; Puech, M.; Hammer, F.; Gallego, J.; Sánchez, A.; García, L.; Iglesias, J.

2018-03-01

The Phase A design of MOSAIC, a powerful multi-object spectrograph intended for ESO's Extremely Large Telescope, concluded in late 2017. With the design complete, a three-day workshop was held last October in Toledo to discuss the breakthrough spectroscopic surveys that MOSAIC can deliver across a broad range of contemporary astronomy.

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.

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 ...

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.

A fiber optic temperature sensor based on multi-core microstructured fiber with coupled cores for a high temperature environment

Science.gov (United States)

Makowska, A.; Markiewicz, K.; Szostkiewicz, L.; Kolakowska, A.; Fidelus, J.; Stanczyk, T.; Wysokinski, K.; Budnicki, D.; Ostrowski, L.; Szymanski, M.; Makara, M.; Poturaj, K.; Tenderenda, T.; Mergo, P.; Nasilowski, T.

2018-02-01

Sensors based on fiber optics are irreplaceable wherever immunity to strong electro-magnetic fields or safe operation in explosive atmospheres is needed. Furthermore, it is often essential to be able to monitor high temperatures of over 500°C in such environments (e.g. in cooling systems or equipment monitoring in power plants). In order to meet this demand, we have designed and manufactured a fiber optic sensor with which temperatures up to 900°C can be measured. The sensor utilizes multi-core fibers which are recognized as the dedicated medium for telecommunication or shape sensing, but as we show may be also deployed advantageously in new types of fiber optic temperature sensors. The sensor presented in this paper is based on a dual-core microstructured fiber Michelson interferometer. The fiber is characterized by strongly coupled cores, hence it acts as an all-fiber coupler, but with an outer diameter significantly wider than a standard fused biconical taper coupler, which significantly increases the coupling region's mechanical reliability. Owing to the proposed interferometer imbalance, effective operation and high-sensitivity can be achieved. The presented sensor is designed to be used at high temperatures as a result of the developed low temperature chemical process of metal (copper or gold) coating. The hermetic metal coating can be applied directly to the silica cladding of the fiber or the fiber component. This operation significantly reduces the degradation of sensors due to hydrolysis in uncontrolled atmospheres and high temperatures.

MoS2-wrapped microfiber-based multi-wavelength soliton fiber laser

Science.gov (United States)

Lu, Feifei

2017-11-01

The single-, dual- and triple-wavelength passively mode-locked erbium-doped fiber lasers are demonstrated with MoS2 and polarization-dependent isolator (PD-ISO). The saturable absorber is fabricated by wrapping an MoS2 around a microfiber. The intracavity PD-ISO acts as a wavelength-tunable filter with a polarization controller (PC) by adjusting the linear birefringence. Single-wavelength mode-locked fiber laser can self-start with suitable pump power. With appropriate PC state, dual- and triple-wavelength operations can be observed when gains at different wavelengths reach a balance. It is noteworthy that dual-wavelength pulses exhibiting peak and dip sidebands, respectively, are demonstrated in the experiment. The proposed simple and multi-wavelength all-fiber conventional soliton lasers could possess potential applications in numerous fields, such as sensors, THz generations and optical communications.

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.

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.

Multi-pulsed intense electron beam emission from velvet, carbon fibers, carbon nano-tubes and dispenser cathodes

International Nuclear Information System (INIS)

Xia Liansheng; Yang Anmin; Chen Yi; Zhang Huang; Liu Xingguang; Li Jin; Jiang Xiaoguo; Zhang Kaizhi; Shi Jinshui; Deng Jianjun; Zhang Linwen

2010-01-01

The experimental results of studies of four kinds of cathode emitting intense electron beams are demonstrated under multi-pulsed mode based on an experimental setup including two multi-pulse high voltage sources. The tested cathodes include velvet, carbon fibers, carbon nano-tubes (CNTs) and dispenser cathodes. The results indicate that all four are able to emit multi-pulsed beams. For velvet, carbon fiber and CNTs, the electron induced cathode plasma emission may be the main process and this means that there are differences in beam parameters from pulse to pulse. For dispenser cathodes tested in the experiment, although there is a little difference from pulse to pulse for some reason, thermal-electric field emission may be the main process. (authors)

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

SPT-GMOS: A GEMINI/GMOS-SOUTH SPECTROSCOPIC SURVEY OF GALAXY CLUSTERS IN THE SPT-SZ SURVEY

International Nuclear Information System (INIS)

Bayliss, M. B.; Ruel, J.; Stubbs, C. W.; Allen, S. W.; Applegate, D. E.; Ashby, M. L. N.; Bautz, M.; Benson, B. A.; Carlstrom, J. E.; Chang, C. L.; Crawford, T. M.; Bleem, L. E.; Bocquet, S.; Brodwin, M.; Capasso, R.; Chiu, I.; Cho, H-M.; Clocchiatti, A.; Crites, A. T.; Haan, T. de

2016-01-01

We present the results of SPT-GMOS, a spectroscopic survey with the Gemini Multi-Object Spectrograph (GMOS) on Gemini South. The targets of SPT-GMOS are galaxy clusters identified in the SPT-SZ survey, a millimeter-wave survey of 2500 deg 2 of the southern sky using the South Pole Telescope (SPT). Multi-object spectroscopic observations of 62 SPT-selected galaxy clusters were performed between 2011 January and 2015 December, yielding spectra with radial velocity measurements for 2595 sources. We identify 2243 of these sources as galaxies, and 352 as stars. Of the galaxies, we identify 1579 as members of SPT-SZ galaxy clusters. The primary goal of these observations was to obtain spectra of cluster member galaxies to estimate cluster redshifts and velocity dispersions. We describe the full spectroscopic data set and resulting data products, including galaxy redshifts, cluster redshifts, and velocity dispersions, and measurements of several well-known spectral indices for each galaxy: the equivalent width, W , of [O ii] λλ 3727, 3729 and H- δ , and the 4000 Å break strength, D4000. We use the spectral indices to classify galaxies by spectral type (i.e., passive, post-starburst, star-forming), and we match the spectra against photometric catalogs to characterize spectroscopically observed cluster members as a function of brightness (relative to m ⋆ ). Finally, we report several new measurements of redshifts for ten bright, strongly lensed background galaxies in the cores of eight galaxy clusters. Combining the SPT-GMOS data set with previous spectroscopic follow-up of SPT-SZ galaxy clusters results in spectroscopic measurements for >100 clusters, or ∼20% of the full SPT-SZ sample.

SPT-GMOS: A Gemini/GMOS-South Spectroscopic Survey of Galaxy Clusters in the SPT-SZ Survey

Science.gov (United States)

Bayliss, M. B.; Ruel, J.; Stubbs, C. W.; Allen, S. W.; Applegate, D. E.; Ashby, M. L. N.; Bautz, M.; Benson, B. A.; Bleem, L. E.; Bocquet, S.; Brodwin, M.; Capasso, R.; Carlstrom, J. E.; Chang, C. L.; Chiu, I.; Cho, H.-M.; Clocchiatti, A.; Crawford, T. M.; Crites, A. T.; de Haan, T.; Desai, S.; Dietrich, J. P.; Dobbs, M. A.; Doucouliagos, A. N.; Foley, R. J.; Forman, W. R.; Garmire, G. P.; George, E. M.; Gladders, M. D.; Gonzalez, A. H.; Gupta, N.; Halverson, N. W.; Hlavacek-Larrondo, J.; Hoekstra, H.; Holder, G. P.; Holzapfel, W. L.; Hou, Z.; Hrubes, J. D.; Huang, N.; Jones, C.; Keisler, R.; Knox, L.; Lee, A. T.; Leitch, E. M.; von der Linden, A.; Luong-Van, D.; Mantz, A.; Marrone, D. P.; McDonald, M.; McMahon, J. J.; Meyer, S. S.; Mocanu, L. M.; Mohr, J. J.; Murray, S. S.; Padin, S.; Pryke, C.; Rapetti, D.; Reichardt, C. L.; Rest, A.; Ruhl, J. E.; Saliwanchik, B. R.; Saro, A.; Sayre, J. T.; Schaffer, K. K.; Schrabback, T.; Shirokoff, E.; Song, J.; Spieler, H. G.; Stalder, B.; Stanford, S. A.; Staniszewski, Z.; Stark, A. A.; Story, K. T.; Vanderlinde, K.; Vieira, J. D.; Vikhlinin, A.; Williamson, R.; Zenteno, A.

2016-11-01

We present the results of SPT-GMOS, a spectroscopic survey with the Gemini Multi-Object Spectrograph (GMOS) on Gemini South. The targets of SPT-GMOS are galaxy clusters identified in the SPT-SZ survey, a millimeter-wave survey of 2500 deg2 of the southern sky using the South Pole Telescope (SPT). Multi-object spectroscopic observations of 62 SPT-selected galaxy clusters were performed between 2011 January and 2015 December, yielding spectra with radial velocity measurements for 2595 sources. We identify 2243 of these sources as galaxies, and 352 as stars. Of the galaxies, we identify 1579 as members of SPT-SZ galaxy clusters. The primary goal of these observations was to obtain spectra of cluster member galaxies to estimate cluster redshifts and velocity dispersions. We describe the full spectroscopic data set and resulting data products, including galaxy redshifts, cluster redshifts, and velocity dispersions, and measurements of several well-known spectral indices for each galaxy: the equivalent width, W, of [O II] λλ3727, 3729 and H-δ, and the 4000 Å break strength, D4000. We use the spectral indices to classify galaxies by spectral type (i.e., passive, post-starburst, star-forming), and we match the spectra against photometric catalogs to characterize spectroscopically observed cluster members as a function of brightness (relative to m⋆). Finally, we report several new measurements of redshifts for ten bright, strongly lensed background galaxies in the cores of eight galaxy clusters. Combining the SPT-GMOS data set with previous spectroscopic follow-up of SPT-SZ galaxy clusters results in spectroscopic measurements for >100 clusters, or ∼20% of the full SPT-SZ sample.

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

Design of a novel multi channel photonic crystal fiber polarization beam splitter

Science.gov (United States)

Zhao, Yunyan; Li, Shuguang; Wang, Xinyu; Wang, Guangyao; Shi, Min; Wu, Junjun

2017-10-01

A kind of multi channel dual-core photonic crystal fiber polarization beam splitter is designed. We analyze the effects of the lattice parameters and the thickness of gold layer on the beam splitting by the finite element method. Numerical results show that the thickness of metal layer and the size of the air holes near the fiber cores are closely linked with the nature of the polarization beam splitter. We also obtain that extinction ratio can reach -73.87 dB at 1 . 55 μm wavelength and at 1 . 41 μm, 1 . 65 μm extinction ratio can reach 30.8978 dB and 31.1741 dB, respectively. The comparison of the effect on the characteristic of the photonic crystal fiber with coating no gold is also taken into account.

Characterization technique for long optical fiber cavities based on beating spectrum of multi-longitudinal mode fiber laser and beating spectrum in the RF domain

Science.gov (United States)

Adib, George A.; Sabry, Yasser M.; Khalil, Diaa

2016-03-01

The characterization of long fiber cavities is essential for many systems to predict the system practical performance. The conventional techniques for optical cavity characterization are not suitable for long fiber cavities due to the cavities' small free spectral ranges and due to the length variations caused by the environmental effects. In this work, we present a novel technique to characterize long fiber cavities using multi-longitudinal mode fiber laser source and RF spectrum analyzer. The fiber laser source is formed in a ring configuration, where the fiber laser cavity length is chosen to be 15 km to ensure that the free spectral range is much smaller than the free spectral range of the characterized passive fiber cavities. The method has been applied experimentally to characterize ring cavities with lengths of 6.2 m and 2.4 km. The results are compared to theoretical predictions with very good agreement.

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.

THE TIME DOMAIN SPECTROSCOPIC SURVEY: VARIABLE SELECTION AND ANTICIPATED RESULTS

Energy Technology Data Exchange (ETDEWEB)

Morganson, Eric; Green, Paul J. [Harvard Smithsonian Center for Astrophysics, 60 Garden St, Cambridge, MA 02138 (United States); Anderson, Scott F.; Ruan, John J. [Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195 (United States); Myers, Adam D. [Department of Physics and Astronomy, University of Wyoming, Laramie, WY 82071 (United States); Eracleous, Michael; Brandt, William Nielsen [Department of Astronomy and Astrophysics, 525 Davey Laboratory, The Pennsylvania State University, University Park, PA 16802 (United States); Kelly, Brandon [Department of Physics, Broida Hall, University of California, Santa Barbara, CA 93106-9530 (United States); Badenes, Carlos [Department of Physics and Astronomy and Pittsburgh Particle Physics, Astrophysics and Cosmology Center (PITT PACC), University of Pittsburgh, 3941 O’Hara St, Pittsburgh, PA 15260 (United States); Bañados, Eduardo [Max-Planck-Institut für Astronomie, Königstuhl 17, D-69117 Heidelberg (Germany); Blanton, Michael R. [Center for Cosmology and Particle Physics, Department of Physics, New York University, 4 Washington Place, New York, NY 10003 (United States); Bershady, Matthew A. [Department of Astronomy, University of Wisconsin, 475 N. Charter St., Madison, WI 53706 (United States); Borissova, Jura [Instituto de Física y Astronomía, Universidad de Valparaíso, Av. Gran Bretaña 1111, Playa Ancha, Casilla 5030, and Millennium Institute of Astrophysics (MAS), Santiago (Chile); Burgett, William S. [GMTO Corp, Suite 300, 251 S. Lake Ave, Pasadena, CA 91101 (United States); Chambers, Kenneth, E-mail: emorganson@cfa.harvard.edu [Institute for Astronomy, University of Hawaii at Manoa, Honolulu, HI 96822 (United States); and others

2015-06-20

We present the selection algorithm and anticipated results for the Time Domain Spectroscopic Survey (TDSS). TDSS is an Sloan Digital Sky Survey (SDSS)-IV Extended Baryon Oscillation Spectroscopic Survey (eBOSS) subproject that will provide initial identification spectra of approximately 220,000 luminosity-variable objects (variable stars and active galactic nuclei across 7500 deg{sup 2} selected from a combination of SDSS and multi-epoch Pan-STARRS1 photometry. TDSS will be the largest spectroscopic survey to explicitly target variable objects, avoiding pre-selection on the basis of colors or detailed modeling of specific variability characteristics. Kernel Density Estimate analysis of our target population performed on SDSS Stripe 82 data suggests our target sample will be 95% pure (meaning 95% of objects we select have genuine luminosity variability of a few magnitudes or more). Our final spectroscopic sample will contain roughly 135,000 quasars and 85,000 stellar variables, approximately 4000 of which will be RR Lyrae stars which may be used as outer Milky Way probes. The variability-selected quasar population has a smoother redshift distribution than a color-selected sample, and variability measurements similar to those we develop here may be used to make more uniform quasar samples in large surveys. The stellar variable targets are distributed fairly uniformly across color space, indicating that TDSS will obtain spectra for a wide variety of stellar variables including pulsating variables, stars with significant chromospheric activity, cataclysmic variables, and eclipsing binaries. TDSS will serve as a pathfinder mission to identify and characterize the multitude of variable objects that will be detected photometrically in even larger variability surveys such as Large Synoptic Survey Telescope.

Optical fiber sources and transmission controls for multi-Tb/s systems

Science.gov (United States)

Nowak, George Adelbert

The accelerating demand for bandwidth capacity in backbone links of terrestrial communications systems is projected to exceed 1Tb/s by 2002. Lightwave carrier frequencies and fused-silica optical fibers provide the natural combination of high passband frequencies and low- loss medium to satisfy this evolving demand for bandwidth capacity. This thesis addresses three key technologies for enabling multi-Tb/s optical fiber communication systems. The first technology is a broadband source based on supercontinuum generation in optical fiber. Using a single modelocked laser with output pulsewidths of 0.5psec pulses, we generate in ~2m of dispersion-shifted fiber more that 200nm of spectral continuum in the vicinity of 1550nm that is flat to better than +/- 0.5 dB over more than 60nm. The short fiber length prevents degradation of timing jitter of the seed pulses and preserves coherence of the continuum by inhibiting environmental perturbations and mapping of random noise from the vicinity of the input pulse across the continuum. Through experiments and simulations, we find that the continuum characteristics result from 3rd order dispersion effects on higher-order soliton compression. We determine optimal fiber properties to provide desired continuum broadness and flatness for given input pulsewidth and energy conditions. The second technology is a novel delay-shifted nonlinear optical loop mirror (DS-NOLM) that performs a transmission control function by serving as an intensity filter and frequency compensator for 4ps soliton transmission over 75km of standard dispersion fiber, with 25km spacing between amplifiers, by filtering the dispersive waves and compensating for Raman-induced soliton self-frequency shift. The third technology is all-fiber wavelength conversion employing induced modulational instability. We obtain wavelength conversion over 40nm with a peak conversion efficiency of 28dB using 600mW pump pulses in 720m of high-nonlinearity optical fiber. We show

THE GALACTIC O-STAR SPECTROSCOPIC SURVEY (GOSSS). II. BRIGHT SOUTHERN STARS

International Nuclear Information System (INIS)

Sota, A.; Apellániz, J. Maíz; Alfaro, E. J.; Morrell, N. I.; Barbá, R. H.; Arias, J. I.; Walborn, N. R.; Gamen, R. C.

2014-01-01

We present the second installment of GOSSS, a massive spectroscopic survey of Galactic O stars, based on new homogeneous, high signal-to-noise ratio, R ∼ 2500 digital observations from both hemispheres selected from the Galactic O-Star Catalog (GOSC). In this paper we include bright stars and other objects drawn mostly from the first version of GOSC, all of them south of δ = –20°, for a total number of 258 O stars. We also revise the northern sample of Paper I to provide the full list of spectroscopically classified Galactic O stars complete to B = 8, bringing the total number of published GOSSS stars to 448. Extensive sequences of exceptional objects are given, including the early Of/WN, O Iafpe, Ofc, ON/OC, Onfp, Of?p, and Oe types, as well as double/triple-lined spectroscopic binaries. The new spectral subtype O9.2 is also discussed. The magnitude and spatial distributions of the observed sample are analyzed. We also present new results from OWN, a multi-epoch high-resolution spectroscopic survey coordinated with GOSSS that is assembling the largest sample of Galactic spectroscopic massive binaries ever attained. The OWN data combined with additional information on spectroscopic and visual binaries from the literature indicate that only a very small fraction (if any) of the stars with masses above 15-20 M ☉ are born as single systems. In the future we will publish the rest of the GOSSS survey, which is expected to include over 1000 Galactic O stars

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)

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 %.

Multi-mode optical fibers for connecting space-based spectrometers

Science.gov (United States)

Roberts, W. T.; Lindenmisth, C. A.; Bender, S.; Miller, E. A.; Motts, E.; Ott, M.; LaRocca, F.; Thomes, J.

2017-11-01

significantly smaller, less massive and less robust. Large core multi-mode optical fibers are often used to accommodate the optical connection of the two separated portions of such instrumentation. In some cases, significant throughput efficiency improvement can be realized by judiciously orienting the strands of multi-fiber cable, close-bunching them to accommodate a tight focus of the optical system on the optical side of the connection, and splaying them out linearly along a spectrometer slit on the other end. For such instrumentation to work effectively in identifying elements and molecules, and especially to produce accurate quantitative results, the spectral throughput of the optical fiber connection must be consistent over varying temperatures, over the range of motion of the optical head (and it's implied optical cable stresses), and over angle-aperture invariant of the total system. While the first two of these conditions have been demonstrated[4], spectral observations of the latter present a cause for concern, and may have an impact on future design of fiber-connected LIBS and Raman spectroscopy instruments. In short, we have observed that the shape of the spectral efficiency curve of a large multi-mode core optical fiber changes as a function of input angle.

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.

Topological insulator: Bi{sub 2}Se{sub 3}/polyvinyl alcohol film-assisted multi-wavelength ultrafast erbium-doped fiber laser

Energy Technology Data Exchange (ETDEWEB)

Guo, Bo; Yao, Yong, E-mail: yaoyong@hit.edu.cn; Yang, Yan-Fu; Yuan, Yi-Jun; Wang, Rui-Lai [Department of Electronic and Information Engineering, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055 (China); Wang, Shu-Guang; Ren, Zhong-Hua [Department of Materials Science and Engineering, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055 (China); Yan, Bo [College of Materials Science and Engineering, Zhengzhou University, Zhengzhou 450052 (China)

2015-02-14

We experimentally demonstrate a multi-wavelength ultrafast erbium-doped fiber laser incorporating a μm-scale topological insulator: Bi{sub 2}Se{sub 3}/Polyvinyl Alcohol film as both an excellent saturable absorber for mode-locking and a high-nonlinear medium to induce a giant third order optical nonlinear effect for mitigating the mode competition of erbium-doped fiber laser and stabilizing the multi-wavelength oscillation. By properly adjusting the pump power and the polarization state, the single-, dual-, triple-, four-wavelength mode-locking pulse could be stably initiated. For the four-wavelength operation, we obtain its pulse width of ∼22 ps and a fundamental repetition rate of 8.83 MHz. The fiber laser exhibits the maximum output power of 9.7 mW with the pulse energy of 1.1 nJ and peak power of 50 W at the pump power of 155 mW. Our study shows that the simple, stable, low-cost multi-wavelength ultrafast fiber laser could be applied in various potential fields, such as optical communication, biomedical research, and radar system.

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

MPO-type single-mode multi-fiber connector: Low-loss and high-return-loss intermateability of APC-MPO connectors

Science.gov (United States)

Satake, Toshiaki; Nagasawa, Shinji; Hughes, Mike; Lutz, Sharon

2011-01-01

The electrical communication laboratory of NTT started the research of MT (Mechanically Transferable) connector in early 1980s. The initial goal was to realize a multi-fiber connector which can repeat low loss, stable, reliable and low-cost connections of subscriber optical fiber cable networks for more than 20 years period in the field. We review the multi-fiber alignment design with two guide pins, and following several technical improvements toward the final MT connector used in the commercial telecommunication networks. And then, we review development histories to reach to the low-loss, high-return-loss and reliable APC-MPO (Angled Physical Contact Multi-fiber Push On) connectors introduced in NTT COs and in Verizon's FTTH (Fiber To The Home) networks. In the latter half, we propose the low-loss intermateability design for connectors made by different suppliers in order to enable mass introductions into large scale systems. In addition we also describe an accurate connector loss presumption method for different lots' ferrules based on the MT ferrule dimension data before assembling the connectors. We believe with a wide intermateability of APC-MPO connector will increase its use in the fields. The APC-MPO connector manufactured based on the proposed design had low insertion losses of less than 0.25 dB at the same level of simplex connectors and the higher level of return losses higher than 65 dB.

Design of Multi-core Fiber Patch Panel for Space Division Multiplexing Implementations

DEFF Research Database (Denmark)

Gonzalez, Luz E.; Morales, Alvaro; Rommel, Simon

2018-01-01

A multi-core fiber (MCF) patch panel was designed, allowing easy coupling of individual signals to and from a 7-core MCF. The device was characterized, measuring insertion loss and cross talk, finding highest insertion loss and lowest crosstalk at 1300 nm with values of 9.7 dB and -36.5 d...

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.

Design of multi-core fiber patch panel for space division multiplexing implementations

NARCIS (Netherlands)

González, Luz E.; Morales, Alvaro; Rommel, Simon; Jørgensen, Bo F.; Porras-Montenegro, N.; Tafur Monroy, Idelfonso

2018-01-01

A multi-core fiber (MCF) patch panel was designed, allowing easy coupling of individual signals to and from a 7-core MCF. The device was characterized, measuring insertion loss and cross talk, finding highest insertion loss and lowest crosstalk at 1300 nm with values of 9.7 dB and -36.5 dB

Tunable and reconfigurable multi-tap microwave photonic filter based on dynamic Brillouin gratings in fibers.

Science.gov (United States)

Sancho, J; Primerov, N; Chin, S; Antman, Y; Zadok, A; Sales, S; Thévenaz, L

2012-03-12

We propose and experimentally demonstrate new architectures to realize multi-tap microwave photonic filters, based on the generation of a single or multiple dynamic Brillouin gratings in polarization maintaining fibers. The spectral range and selectivity of the proposed periodic filters is extensively tunable, simply by reconfiguring the positions and the number of dynamic gratings along the fiber respectively. In this paper, we present a complete analysis of three different configurations comprising a microwave photonic filter implementation: a simple notch-type Mach-Zehnder approach with a single movable dynamic grating, a multi-tap performance based on multiple dynamic gratings and finally a stationary grating configuration based on the phase modulation of two counter-propagating optical waves by a common pseudo-random bit sequence (PRBS).

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.

Development of multi-channel optical-fiber feed through for ITER

International Nuclear Information System (INIS)

Sugie, Tatsuo; Kasai, Satoshi; Toriya, Tomoaki

1998-08-01

A multi-channel fiber feed through has been developed for visible and IR transmission lines through secondary vacuum boundary (cryostat boundary) of ITER. In the first phase, a scale down test-module which has ten fiber feed through in the vacuum flange was manufactured and tested. The vacuum seal was realized by soldering gold plated fibers to a vacuum flange with high temperature solder. The capacity to resist inner pressure rise of 5 atm, the acceleration resistant of 15g and the temperature resistant from 20degC-200degC were achieved by the test module. The connecting loss and the uniformity of transmission losses among each channels of the feed through were not well. Concerning the connecting loss, the best value was 2.2 dB and the worst one was 13.5 dB. In the second phase, the full performance test-module which has 57 fiber feed through was manufactured and tested. The feed through was improved in order to achieve a good transmission and the uniformity among each channels by using a optical fiber implanted in a center of a quartz rod very accurately. The capacity to resist inner pressure rise of 5 atm, the acceleration resistant of 15g and the temperature resistant from 40degC-200degC (Temperature ramp rate: >20degC/hr) were achieved by the full performance test-module. The connecting losses of the feed through were less than 3 dB, and the uniformity of transmission losses among each channels of the feed through was larger than 60%. The requirements for an optical-fiber feed through were almost satisfied with the full performance test-module. Further developments will be necessary for the remote handling method. (author)

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...

Multi-mode optical fibers for simultaneous 13-position measurements Thomson scattering apparatus in the JFT-2M tokamak

International Nuclear Information System (INIS)

Yamauchi, Toshihiko; Nakazawa, Ichiro; Matoba, Tohru; Ogura, Yoshiaki.

1987-11-01

The characteristics of fiber bundles for Thomson scattering optics are studied, whose fibers are made of multi-mode optical fibers. The variety of output patterns were observed by weighting on the fiber as well as by bending it after passing a He-Ne laser through a fiber bundle. This variety influenced the matching loss considerably. Then, the effect of former is larger than the latter, which is caused by the micro bending. And also, the spread of pulse width by weighting is connected with the spread of output pattern. The spread of pulse width was about 3ns at the most in a 2.3 m length of fiber bundle. (author)

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...

Defect study in ZnO related structures-A multi-spectroscopic approach

International Nuclear Information System (INIS)

Ling, C.C.; Cheung, C.K.; Gu, Q.L.; Dai, X.M.; Xu, S.J.; Zhu, C.Y.; Luo, J.M.; Zhu, C.Y.; Tam, K.H.; Djurisic, A.B.; Beling, C.D.; Fung, S.; Lu, L.W.; Brauer, G.; Anwand, W.; Skorupa, W.; Ong, H.C.

2008-01-01

ZnO has attracted a great deal of attention in recent years because of its potential applications for fabricating optoelectronic devices. Using a multi-spectroscopic approach including positron annihilation spectroscopy (PAS), deep level transient spectroscopy (DLTS), photoluminescence (PL) and X-ray photoelectron spectroscopy (XPS), we have studied the two observed phenomena from ZnO related structures. They namely included the H 2 O 2 pre-treatment induced ohmic to rectifying contact conversion on Au/n-ZnO contact and the p-type doping by nitrogen ion implantation. The aim of the studies was to offering comprehensive views as to how the defects influenced the structures electrical and optical properties of the structures. It was also shown that PAS measurement using the monoenergetic positron beam could offer valuable information of vacancy type defects in the vertical ZnO nanorod array structure

Defect study in ZnO related structures-A multi-spectroscopic approach

Energy Technology Data Exchange (ETDEWEB)

Ling, C.C. [Department of Physics, The University of Hong Kong, Pokfulam Road, Hong Kong (China)], E-mail: ccling@hku.hk; Cheung, C.K.; Gu, Q.L.; Dai, X.M.; Xu, S.J.; Zhu, C.Y.; Luo, J.M.; Zhu, C.Y.; Tam, K.H.; Djurisic, A.B.; Beling, C.D.; Fung, S.; Lu, L.W. [Department of Physics, The University of Hong Kong, Pokfulam Road, Hong Kong (China); Brauer, G.; Anwand, W.; Skorupa, W. [Institut fuer Ionenstrahlphysik und Materialforschung, Forschungszentrum Dresden-Rossendorf, Postfach 510119, D-01314 Dresden (Germany); Ong, H.C. [Department of Physics, Chinese University of Hong Kong, Shatin, Hong Kong (China)

2008-10-31

ZnO has attracted a great deal of attention in recent years because of its potential applications for fabricating optoelectronic devices. Using a multi-spectroscopic approach including positron annihilation spectroscopy (PAS), deep level transient spectroscopy (DLTS), photoluminescence (PL) and X-ray photoelectron spectroscopy (XPS), we have studied the two observed phenomena from ZnO related structures. They namely included the H{sub 2}O{sub 2} pre-treatment induced ohmic to rectifying contact conversion on Au/n-ZnO contact and the p-type doping by nitrogen ion implantation. The aim of the studies was to offering comprehensive views as to how the defects influenced the structures electrical and optical properties of the structures. It was also shown that PAS measurement using the monoenergetic positron beam could offer valuable information of vacancy type defects in the vertical ZnO nanorod array structure.

Defect study in ZnO related structures—A multi-spectroscopic approach

Science.gov (United States)

Ling, C. C.; Cheung, C. K.; Gu, Q. L.; Dai, X. M.; Xu, S. J.; Zhu, C. Y.; Luo, J. M.; Zhu, C. Y.; Tam, K. H.; Djurišić, A. B.; Beling, C. D.; Fung, S.; Lu, L. W.; Brauer, G.; Anwand, W.; Skorupa, W.; Ong, H. C.

2008-10-01

ZnO has attracted a great deal of attention in recent years because of its potential applications for fabricating optoelectronic devices. Using a multi-spectroscopic approach including positron annihilation spectroscopy (PAS), deep level transient spectroscopy (DLTS), photoluminescence (PL) and X-ray photoelectron spectroscopy (XPS), we have studied the two observed phenomena from ZnO related structures. They namely included the H 2O 2 pre-treatment induced ohmic to rectifying contact conversion on Au/ n-ZnO contact and the p-type doping by nitrogen ion implantation. The aim of the studies was to offering comprehensive views as to how the defects influenced the structures electrical and optical properties of the structures. It was also shown that PAS measurement using the monoenergetic positron beam could offer valuable information of vacancy type defects in the vertical ZnO nanorod array structure.

Massive Young Stellar Objects in the Galactic Center. 1; Spectroscopic Identification from Spitzer/IRS Observations

Science.gov (United States)

An, Deokkeun; Ramirez, Solange V.; Sellgren, Kris; Arendt, Richard G.; Boogert, A. C. Adwin; Robitaille, Thomas P.; Schultheis, Mathias; Cotera, Angela S.; Smith, Howard A.; Stolovy, Susan R.

2011-01-01

We present results from our spectroscopic study, using the Infrared Spectrograph (IRS) onboard the Spitzer Space Telescope, designed to identify massive young stellar objects (YSOs) in the Galactic Center (GC). Our sample of 107 YSO candidates was selected based on IRAC colors from the high spatial resolution, high sensitivity Spitzer/IRAC images in the Central Molecular Zone (CMZ), which spans the central approximately 300 pc region of the Milky Way Galaxy. We obtained IRS spectra over 5 micron to 35 micron using both high- and low-resolution IRS modules. We spectroscopically identify massive YSOs by the presence of a 15.4 micron shoulder on the absorption profile of 15 micron CO2 ice, suggestive of CO2 ice mixed with CH30H ice on grains. This 15.4 micron shoulder is clearly observed in 16 sources and possibly observed in an additional 19 sources. We show that 9 massive YSOs also reveal molecular gas-phase absorption from C02, C2H2, and/or HCN, which traces warm and dense gas in YSOs. Our results provide the first spectroscopic census of the massive YSO population in the GC. We fit YSO models to the observed spectral energy distributions and find YSO masses of 8 - 23 solar Mass, which generally agree with the masses derived from observed radio continuum emission. We find that about 50% of photometrically identified YSOs are confirmed with our spectroscopic study. This implies a preliminary star formation rate of approximately 0.07 solar mass/yr at the GC.

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.

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

The new MQ/AAO/Strasbourg multi-wavelength and spectroscopic PNe database: MASPN

Science.gov (United States)

Parker, Quentin Andrew; Bojicic, Ivan; Frew, David; Acker, Agnes; Ochsenbein, Francois; MASPN Database Team

2015-01-01

We are in a new golden age of PN discovery. This is thanks in particular to high sensitivity, wide-field, narrow-band surveys of the Galactic plane undertaken on the UKST in Australia and the Isaac Newton telescope on La Palma. Together these telescopes and their H-alpha surveys have provided very significant Planetary Nebulae (PNe) discoveries that have more than doubled the totals accrued by all telescopes over the previous 250 years. However, these PNe are not simply more of the same found in previous catalogues. Most new PNe are more obscured, evolved and of lower surface brightness than previous compilations while others are faint but compact and more distant. This has required an extensive and time-consuming programme of spectroscopic confirmation on a variety of 2m and 4m telescopes that is now largely complete. The scope of any future large-scale PNe studies, particularly those of a statistical nature or undertaken to understand true PNe diversity and evolution should now reflect this fresh PN population landscape of the combined sample of ~3500 Galactic PNe now available. Such studies should be coloured and nuanced by these recent major discoveries and the massive, high sensitivity, high resolution, multi-wavelength imaging surveys now available across much of the electromagnetic spectrum.Following this motivation we provide, for the first time, an accessible, reliable, on-line "one-stop" SQL database for essential, up-to date information for all known Galactic PN. We have attempted to: i) Reliably remove the many PN mimics/false ID's that have biased previous compilations and subsequent studies; ii) Provide accurate, updated positions, sizes, morphologies, radial velocities, fluxes, multi-wavelength imagery and spectroscopy; iii) Link to CDS/Vizier and hence provide archival history for each object; iv) Provide an interface to sift, select, browse, collate, investigate, download and visualise the complete currently known Galactic PNe diaspora and v

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.

Refractive index sensors based on the fused tapered special multi-mode fiber

Science.gov (United States)

Fu, Xing-hu; Xiu, Yan-li; Liu, Qin; Xie, Hai-yang; Yang, Chuan-qing; Zhang, Shun-yang; Fu, Guang-wei; Bi, Wei-hong

2016-01-01

In this paper, a novel refractive index (RI) sensor is proposed based on the fused tapered special multi-mode fiber (SMMF). Firstly, a section of SMMF is spliced between two single-mode fibers (SMFs). Then, the SMMF is processed by a fused tapering machine, and a tapered fiber structure is fabricated. Finally, a fused tapered SMMF sensor is obtained for measuring external RI. The RI sensing mechanism of tapered SMMF sensor is analyzed in detail. For different fused tapering lengths, the experimental results show that the RI sensitivity can be up to 444.517 81 nm/RIU in the RI range of 1.334 9—1.347 0. The RI sensitivity is increased with the increase of fused tapering length. Moreover, it has many advantages, including high sensitivity, compact structure, fast response and wide application range. So it can be used to measure the solution concentration in the fields of biochemistry, health care and food processing.

Advanced Modular, Multi-Channel, High Speed Fiber Optic Sensing System for Acoustic Emissions Monitoring, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Intelligent Fiber Optic Systems Corporation (IFOS) proposes to prove the feasibility of innovations based on ultra-light-weight, ultra-high-speed, multi-channel,...

Multi-wavelength Brillouin Raman erbium-doped fiber laser generation in a linear cavity

International Nuclear Information System (INIS)

Shirazi, M R; Harun, S W; Ahmad, H

2014-01-01

A multi-wavelength Brillouin Raman erbium-doped fiber laser is proposed and demonstrated. The setup uses a 7.7 km dispersion compensating fiber simultaneously as the Brillouin and Raman nonlinear gain media and operates in conjunction with a 3 m erbium-doped fiber as the linear gain medium. At a Brillouin pump (BP) wavelength of 1530 nm, where Raman and erbium gains overlap each other, 34 Brillouin Stokes lines having line spacing of 0.075 nm are created by using a Raman pump power of only 24.1 dBm, an erbium pump power of about 22.1 dBm, and a BP power of 6.5 dBm in the proposed linear cavity. The system is highly efficient and is able to generate many comparable peak-power lines at a low pump power. (paper)

GESE: A Small UV Space Telescope to Conduct a Large Spectroscopic Survey of Z-1 Galaxies

Science.gov (United States)

Heap, Sara R.; Gong, Qian; Hull, Tony; Kruk, Jeffrey; Purves, Lloyd

2013-01-01

One of the key goals of NASA's astrophysics program is to answer the question: How did galaxies evolve into the spirals and elliptical galaxies that we see today? We describe a space mission concept called Galaxy Evolution Spectroscopic Explorer (GESE) to address this question by making a large spectroscopic survey of galaxies at a redshift, z is approximately 1 (look-back time of approximately 8 billion years). GESE is a 1.5-meter space telescope with an ultraviolet (UV) multi-object slit spectrograph that can obtain spectra of hundreds of galaxies per exposure. The spectrograph covers the spectral range, 0.2-0.4 micrometers at a spectral resolving power, R approximately 500. This observed spectral range corresponds to 0.1-0.2 micrometers as emitted by a galaxy at a redshift, z=1. The mission concept takes advantage of two new technological advances: (1) light-weighted, wide-field telescope mirrors, and (2) the Next- Generation MicroShutter Array (NG-MSA) to be used as a slit generator in the multi-object slit spectrograph.

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.

Orbital angular momentum mode groups multiplexing transmission over 2.6-km conventional multi-mode fiber.

Science.gov (United States)

Zhu, Long; Wang, Andong; Chen, Shi; Liu, Jun; Mo, Qi; Du, Cheng; Wang, Jian

2017-10-16

Twisted light carrying orbital angular momentum (OAM) is a special kind of structured light that has a helical phase front, a phase singularity, and a doughnut intensity profile. Beyond widespread developments in manipulation, microscopy, metrology, astronomy, nonlinear and quantum optics, OAM-carrying twisted light has seen emerging application of optical communications in free space and specially designed fibers. Instead of specialty fibers, here we show the direct use of a conventional graded-index multi-mode fiber (MMF) for OAM communications. By exploiting fiber-compatible mode exciting and filtering elements, we excite the first four OAM mode groups in an MMF. We demonstrate 2.6-km MMF transmission using four data-carrying OAM mode groups (OAM 0,1 , OAM +1,1 /OAM -1,1 , OAM +2,1 , OAM +3,1 ). Moreover, we demonstrate two data-carrying OAM mode groups multiplexing transmission over the 2.6-km MMF with low-level crosstalk free of multiple-input multiple-output digital signal processing (MIMO-DSP). The demonstrations may open up new perspectives to fiber-based OAM communication/non-communication applications using already existing conventional fibers.

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.

Noncontact ballistic motion measurement using a fiber-optic confocal sensor

International Nuclear Information System (INIS)

Shafir, E.; Berkovic, G.; Horovitz, Y.; Appelbaum, G.; Moshe, E.; Horovitz, E.; Skutelski, A.; Werdiger, M.; Perelmutter, L.; Sudai, M.

2007-01-01

A fiber-optic confocal sensor for noncontact ballistic measurements is described. Determination of motion at velocities of 1.7 km/s with an uncertainty as small as ±0.3% is demonstrated for both a projectile and a free-surface target. The fibers detect the passage of the object at their conjugate image points created by low F/ optics. This results in an output signal comprising a train of sharp pulses each precisely identifying when the ballistic object traverses an image point. Since the ballistic object does not contact the sensor at the time of imaging, the measurements do not perturb the motion, enabling multi-fragment measurement, as well as repetitive measurements of the same object point

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.

Detection of cosmic ray tracks using scintillating fibers and position sensitive multi-anode photomultipliers

International Nuclear Information System (INIS)

Atac, M.; Streets, J.; Wilcer, N.

1998-02-01

This experiment demonstrates detection of cosmic ray tracks by using Scintillating fiber planes and multi-anode photomultipliers (MA-PMTs). In a laboratory like this, cosmic rays provide a natural source of high-energy charged particles which can be detected with high efficiency and with nanosecond time resolution

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

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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

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.

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 ...

GESE: a small UV space telescope to conduct a large spectroscopic survey of z˜1 Galaxies

Science.gov (United States)

Heap, Sara R.; Gong, Qian; Hull, Tony; Kruk, Jeffrey; Purves, Lloyd

2014-11-01

One of the key goals of NASA's astrophysics program is to answer the question: How did galaxies evolve into the spirals and elliptical galaxies that we see today? We describe a space mission concept called Galaxy Evolution Spectroscopic Explorer (GESE) to address this question by making a large spectroscopic survey of galaxies at a redshift, z˜1 (look-back time of ˜8 billion years). GESE is a 1.5-m space telescope with an ultraviolet (UV) multi-object slit spectrograph that can obtain spectra of hundreds of galaxies per exposure. The spectrograph covers the spectral range, 0.2-0.4 μm at a spectral resolving power, R˜500. This observed spectral range corresponds to 0.1-0.2 μm as emitted by a galaxy at a redshift, z=1. The mission concept takes advantage of two new technological advances: (1) light-weighted, wide-field telescope mirrors, and (2) the Next-Generation MicroShutter Array (NG-MSA) to be used as a slit generator in the multi-object slit spectrograph.

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.

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.

Multi-spectroscopic characterization of bovine serum albumin upon interaction with atomoxetine

Directory of Open Access Journals (Sweden)

Arunkumar T. Buddanavar

2017-06-01

Full Text Available The quenching interaction of atomoxetine (ATX with bovine serum albumin (BSA was studied in vitro under optimal physiological condition (pH=7.4 by multi-spectroscopic techniques. The mechanism of ATX-BSA system was a dynamic quenching process and was confirmed by the fluorescence spectra and lifetime measurements. The number of binding sites, binding constants and other binding characteristics were computed. Thermodynamic parameters ∆H° and ∆S° indicated that intermolecular hydrophobic forces predominantly stabilized the drug-protein system. The average binding distance between BSA and ATX was studied by Försters theory. UV-absorption, Fourier transform infrared spectroscopy (FT-IR, circular dichroism (CD, synchronous spectra and three-dimensional (3D fluorescence spectral results revealed the changes in micro-environment of secondary structure of protein upon the interaction with ATX. Displacement of site probes and the effects of some common metal ions on the binding of ATX with BSA interaction were also studied.

Development of quality control and instrumentation performance metrics for diffuse optical spectroscopic imaging instruments in the multi-center clinical environment

Science.gov (United States)

Keene, Samuel T.; Cerussi, Albert E.; Warren, Robert V.; Hill, Brian; Roblyer, Darren; Leproux, AnaÑ--s.; Durkin, Amanda F.; O'Sullivan, Thomas D.; Haghany, Hosain; Mantulin, William W.; Tromberg, Bruce J.

2013-03-01

Instrument equivalence and quality control are critical elements of multi-center clinical trials. We currently have five identical Diffuse Optical Spectroscopic Imaging (DOSI) instruments enrolled in the American College of Radiology Imaging Network (ACRIN, #6691) trial located at five academic clinical research sites in the US. The goal of the study is to predict the response of breast tumors to neoadjuvant chemotherapy in 60 patients. In order to reliably compare DOSI measurements across different instruments, operators and sites, we must be confident that the data quality is comparable. We require objective and reliable methods for identifying, correcting, and rejecting low quality data. To achieve this goal, we developed and tested an automated quality control algorithm that rejects data points below the instrument noise floor, improves tissue optical property recovery, and outputs a detailed data quality report. Using a new protocol for obtaining dark-noise data, we applied the algorithm to ACRIN patient data and successfully improved the quality of recovered physiological data in some cases.

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.

A tunable narrow-line-width multi-wavelength Er-doped fiber laser based on a high birefringence fiber ring mirror and an auto-tracking filter

Science.gov (United States)

Jia, Xiu-jie; Liu, Yan-ge; Si, Li-bin; Guo, Zhan-cheng; Fu, Sheng-gui; Kai, Gui-yun; Dong, Xiao-yi

2008-01-01

A novel multi-wavelength erbium-doped fiber laser operating in C-band is proposed and successfully demonstrated. The wavelength interval between the wavelengths is about 0.22 nm. The 3 dB bandwidth of the laser is about 0.012 nm, and the output power reaches 4.8 mW. By using a high birefringence fiber ring mirror (HiBi-FLM) and a tunable FBG, the laser realizes switchable and tunable characteristic. The mode hopping can be effectively prevented. Moreover, this laser can improve wavelength stability significantly by taking advantage of an un-pumped Er3+-doped fiber at the standing-wave section. The laser can operate in stable narrow-line-width with single-, dual-wavelength, and unstable triple-wavelength output at room temperature.

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

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.

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.

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.)

Optical Fiber Sensing Based on Reflection Laser Spectroscopy

Directory of Open Access Journals (Sweden)

Gianluca Gagliardi

2010-03-01

Full Text Available An overview on high-resolution and fast interrogation of optical-fiber sensors relying on laser reflection spectroscopy is given. Fiber Bragg-gratings (FBGs and FBG resonators built in fibers of different types are used for strain, temperature and acceleration measurements using heterodyne-detection and optical frequency-locking techniques. Silica fiber-ring cavities are used for chemical sensing based on evanescent-wave spectroscopy. Various arrangements for signal recovery and noise reduction, as an extension of most typical spectroscopic techniques, are illustrated and results on detection performances are presented.

High spatial resolution distributed fiber system for multi-parameter sensing based on modulated pulses.

Science.gov (United States)

Zhang, Jingdong; Zhu, Tao; Zhou, Huan; Huang, Shihong; Liu, Min; Huang, Wei

2016-11-28

We demonstrate a cost-effective distributed fiber sensing system for the multi-parameter detection of the vibration, the temperature, and the strain by integrating phase-sensitive optical time domain reflectometry (φ-OTDR) and Brillouin optical time domain reflectometry (B-OTDR). Taking advantage of the fast changing property of the vibration and the static properties of the temperature and the strain, both the width and intensity of the laser pulses are modulated and injected into the single-mode sensing fiber proportionally, so that three concerned parameters can be extracted simultaneously by only one photo-detector and one data acquisition channel. A data processing method based on Gaussian window short time Fourier transform (G-STFT) is capable of achieving high spatial resolution in B-OTDR. The experimental results show that up to 4.8kHz vibration sensing with 3m spatial resolution at 10km standard single-mode fiber can be realized, as well as the distributed temperature and stress profiles along the same fiber with 80cm spatial resolution.

Switchable multi-wavelength erbium-doped fiber ring laser based on a tapered in-line Mach–Zehnder interferometer

Science.gov (United States)

Zhou, Yuxin; Wang, Xin; Tang, Zijuan; Lou, Shuqin

2018-05-01

In this paper, a switchable multi-wavelength erbium-doped fiber ring laser based on a tapered in-line Mach–Zehnder interferometer is proposed. The in-line Mach–Zehnder interferometer is fabricated by splicing a large-core fiber between two segments of single mode fibers, in which the first splicing point is tapered and the second splicing point is connected directly. By carefully rotating the polarization controller, switchable single-, dual-, triple- and quad-wavelength lasing outputs can be obtained with a side mode suppression ratio higher than 50 dB. The maximal peak power difference of multi-wavelength lasing is 3.67 dB, demonstrating a good power equalization performance. Furthermore, the proposed laser is proven to be very stable at room temperature. The wavelength shifts and peak power fluctuations are less than 0.02 nm and 1.3 dB over half an hour. In addition, stable quintuple-wavelength lasing with a side mode suppression ratio higher than 50 dB can also be realized when the filter length is changed.

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.

Wet spinning of PVA composite fibers with a large fraction of multi-walled carbon nanotubes

Directory of Open Access Journals (Sweden)

Dengpan Lai

2015-10-01

Full Text Available PVA composites fibers with a large fraction of multi-walled carbon nanotubes modified by both covalent and non-covalent functionalization were produced by a wet-spinning process. Model XQ-1 tensile tester, thermogravimetric analysis, scanning electron microscopy, differential scanning calorimetry, and wide-angle X-ray diffraction were used to characterize the properties of PVA/MWNT composite fibers. The TGA results suggested that MWNTs content in composite fibers were ranged from 5.3 wt% to 27.6 wt%. The mechanical properties of PVA/MWNT composite fibers were obviously superior to pure PVA fiber. The Young׳s modulus of composite fibers enhanced with increasing the content of MWNTs, and it rised gradually from 6.7 GPa for the pure PVA fiber to 12.8 GPa for the composite fibers with 27.6 wt% MWNTs. Meanwhile, the tensile strength increased gradually from 0.39 GPa for the pure PVA fiber to 0.74 GPa for the composite fibers with 14.4 wt% MWNTs. Nevertheless, the tensile strength of the composite fibers decreased as the MWNTs content up to 27.6 wt%. SEM results indicated that the MWNTs homogeneously dispersed in the composite fibers, however some agglomerates also existed when the content of MWNTs reached 27.6 wt%. DSC results proved strong interfacial interaction between MWNTs and PVA chain, which benefited composite fibers in the efficient stress-transfer. WXAD characterization showed that the orientation of PVA molecules declined from 94.1% to 90.9% with the increasing of MWNTs content. The good dispersibility of MWNTs throughout PVA matrix and efficient stress-transfer between MWNTs and PVA matrix may contributed to significant enhancement in the mechanical properties.

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.

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

Portable optical fiber probe-based spectroscopic scanner for rapid cancer diagnosis: a new tool for intraoperative margin assessment.

Directory of Open Access Journals (Sweden)

Niyom Lue

Full Text Available There continues to be a significant clinical need for rapid and reliable intraoperative margin assessment during cancer surgery. Here we describe a portable, quantitative, optical fiber probe-based, spectroscopic tissue scanner designed for intraoperative diagnostic imaging of surgical margins, which we tested in a proof of concept study in human tissue for breast cancer diagnosis. The tissue scanner combines both diffuse reflectance spectroscopy (DRS and intrinsic fluorescence spectroscopy (IFS, and has hyperspectral imaging capability, acquiring full DRS and IFS spectra for each scanned image pixel. Modeling of the DRS and IFS spectra yields quantitative parameters that reflect the metabolic, biochemical and morphological state of tissue, which are translated into disease diagnosis. The tissue scanner has high spatial resolution (0.25 mm over a wide field of view (10 cm × 10 cm, and both high spectral resolution (2 nm and high spectral contrast, readily distinguishing tissues with widely varying optical properties (bone, skeletal muscle, fat and connective tissue. Tissue-simulating phantom experiments confirm that the tissue scanner can quantitatively measure spectral parameters, such as hemoglobin concentration, in a physiologically relevant range with a high degree of accuracy (<5% error. Finally, studies using human breast tissues showed that the tissue scanner can detect small foci of breast cancer in a background of normal breast tissue. This tissue scanner is simpler in design, images a larger field of view at higher resolution and provides a more physically meaningful tissue diagnosis than other spectroscopic imaging systems currently reported in literatures. We believe this spectroscopic tissue scanner can provide real-time, comprehensive diagnostic imaging of surgical margins in excised tissues, overcoming the sampling limitation in current histopathology margin assessment. As such it is a significant step in the development of a

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.

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.

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)

Advances in the Echidna fiber-positioning technology

Science.gov (United States)

Sheinis, Andrew; Saunders, Will; Gillingham, Peter; Farrell, Tony J.; Muller, Rolf; Smedley, Scott; Brzeski, Jurek; Waller, Lewis G.; Gilbert, James; Smith, Greg

2014-07-01

We present advances in the patented Echidna 'tilting spine' fiber positioner technology that has been in operation since 2007 on the SUBARU telescope in the FMOS system. The new Echidna technology is proposed to be implemented on two large fiber surveys: the Dark Energy Spectroscopic Instrument (DESI) (5000 fibers) as well the Australian ESO Positioner (AESOP) for 4MOST, a spectroscopic survey instrument for the VISTA telescope (~2500 fibers). The new 'superspine' actuators are stiffer, longer and more accurate than their predecessors. They have been prototyped at AAO, demonstrating reconfiguration times of ~15s for errors of <5 microns RMS. Laboratory testing of the prortotype shows accurate operation at temperatures of -10 to +30C, with an average heat output of 200 microwatts per actuator during reconfiguration. Throughput comparisons to other positioner types are presented, and we find that losses due to tilt will in general be outweighed by increased allocation yield and reduced fiber stress FRD. The losses from spine tilt are compensated by the gain in allocation yield coming from the greater patrol area, and quantified elsewhere in these proceedings. For typical tilts, f-ratios and collimator overspeeds, Echidna offers a clear efficiency gain versus current r-that or theta-phi positioners.

SPLASH-SXDF Multi-wavelength Photometric Catalog

Science.gov (United States)

Mehta, Vihang; Scarlata, Claudia; Capak, Peter; Davidzon, Iary; Faisst, Andreas; Hsieh, Bau Ching; Ilbert, Olivier; Jarvis, Matt; Laigle, Clotilde; Phillips, John; Silverman, John; Strauss, Michael A.; Tanaka, Masayuki; Bowler, Rebecca; Coupon, Jean; Foucaud, Sébastien; Hemmati, Shoubaneh; Masters, Daniel; McCracken, Henry Joy; Mobasher, Bahram; Ouchi, Masami; Shibuya, Takatoshi; Wang, Wei-Hao

2018-04-01

We present a multi-wavelength catalog in the Subaru/XMM-Newton Deep Field (SXDF) as part of the Spitzer Large Area Survey with Hyper-Suprime-Cam (SPLASH). We include the newly acquired optical data from the Hyper-Suprime-Cam Subaru Strategic Program, accompanied by IRAC coverage from the SPLASH survey. All available optical and near-infrared data is homogenized and resampled on a common astrometric reference frame. Source detection is done using a multi-wavelength detection image including the u-band to recover the bluest objects. We measure multi-wavelength photometry and compute photometric redshifts as well as physical properties for ∼1.17 million objects over ∼4.2 deg2, with ∼800,000 objects in the 2.4 deg2 HSC-Ultra-Deep coverage. Using the available spectroscopic redshifts from various surveys over the range of 0 fraction of 3.2%. The SPLASH-SXDF catalog is a valuable, publicly available resource, perfectly suited for studying galaxies in the early universe and tracing their evolution through cosmic time.

Radiative characterization of random fibrous media with long cylindrical fibers: Comparison of single- and multi-RTE approaches

Science.gov (United States)

Randrianalisoa, Jaona; Haussener, Sophia; Baillis, Dominique; Lipiński, Wojciech

2017-11-01

Radiative heat transfer is analyzed in participating media consisting of long cylindrical fibers with a diameter in the limit of geometrical optics. The absorption and scattering coefficients and the scattering phase function of the medium are determined based on the discrete-level medium geometry and optical properties of individual fibers. The fibers are assumed to be randomly oriented and positioned inside the medium. Two approaches are employed: a volume-averaged two-intensity approach referred to as multi-RTE approach and a homogenized single-intensity approach referred to as the single-RTE approach. Both approaches require effective properties, determined using direct Monte Carlo ray tracing techniques. The macroscopic radiative transfer equations (for single intensity or two volume-averaged intensities) with the corresponding effective properties are solved using Monte Carlo techniques and allow for the determination of the radiative flux distribution as well as overall transmittance and reflectance of the medium. The results are compared against predictions by the direct Monte Carlo simulation on the exact morphology. The effects of fiber volume fraction and optical properties on the effective radiative properties and the overall slab radiative characteristics are investigated. The single-RTE approach gives accurate predictions for high porosity fibrous media (porosity about 95%). The multi-RTE approach is recommended for isotropic fibrous media with porosity in the range of 79-95%.

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.

The heat capacity of polyethylene fibers measured by multi-frequency temperature-modulated calorimetry

International Nuclear Information System (INIS)

Pyda, M.; Nowak-Pyda, E.; Wunderlich, B.

2006-01-01

The apparent heat capacity of polyethylene fibers in the melting region was measured by quasi-isothermal, temperature-modulated differential scanning calorimetry (TMDSC) and compared with results from standard differential scanning calorimetry (DSC) and the solid and liquid thermodynamic heat capacity as references from the ATHAS Data Bank. Using a multi-frequency, complex sawtooth modulation in the quasi-isothermal mode disclosed for the first time that the uncorrected apparent heat capacity C p =A Φ /(A T s ω) of the liquid polyethylene fiber increases with increasing frequency (A Φ is the differential heat-flow rate and A T s is the sample temperature). The frequency-dependent heat capacity cannot be represented by the expression: C p =A Φ /(A T s νω)[1+(τνω) 2 ] 0.5 because of a negative τ 2 . The results were later confirmed by independent measurements on single sinusoidal quasi-isothermal TMDSC on the same material. The error is caused by shrinking of the fiber, which deforms the sample pan

Effects of fiber/matrix interactions on the interfacial deformation micromechanics of cellulose-fiber/polymer composites

Science.gov (United States)

Tze, William Tai-Yin

The overall objective of this dissertation was to gain an understanding of the relationship between interfacial chemistry and the micromechanics of the cellulose-fiber/polymer composites. Regenerated cellulose (lyocell) fibers were treated with amine-, phenylamine-, phenyl-, and octadecyl-silanes, and also styrene-maleic anhydride copolymer. Inverse gas chromatography was conducted to evaluate the modified surfaces and to examine the adsorption behavior of ethylbenzene, a model compound for polystyrene, onto the fibers. Micro-composites were formed by depositing micro-droplets of polystyrene onto single fibers. The fiber was subjected to a tensile strain, and Raman spectroscopy was employed to determine the point-to-point variation of the strain- and stress-sensitive 895 cm-1 band of cellulose along the embedded region. Inverse gas chromatography studies reveal that the Ia-b values, calculated by matching the Lewis acid parameter ( KA) and basic parameter (KB) between polystyrene and different fibers, were closely correlated to the acid-base adsorption enthalpies of ethylbenzene onto the corresponding fibers. Hence, Ia-b was subsequently used as a convenient indicator for fiber/matrix acid-base interaction. The Raman micro-spectroscopic studies demonstrate that the interfacial tensile strain and stress are highest at the edge of the droplet, and these values decline from the edge region to the middle region of the embedment. The maximum of these local strains corresponds to a strain-control fracture of the matrix polymer. The minimum of the local tensile stress corresponds to the extent of fiber-to-matrix load transfer. The slope of the tensile stress profile allows for an estimation of the maximum interfacial shear stress, which is indicative of fiber/polymer (practical) adhesion. As such, a novel micro-Raman tensile technique was established for evaluating the ductile-fiber/brittle-polymer system in this study. The micro-Raman tensile technique provided maximum

Spectroscopic Parameters of Lumbar Intervertebral Disc Material

Science.gov (United States)

Terbetas, G.; Kozlovskaja, A.; Varanius, D.; Graziene, V.; Vaitkus, J.; Vaitkuviene, A.

2009-06-01

There are numerous methods of investigating intervertebral disc. Visualization methods are widely used in clinical practice. Histological, imunohistochemical and biochemical methods are more used in scientific research. We propose that a new spectroscopic investigation would be useful in determining intervertebral disc material, especially when no histological specimens are available. Purpose: to determine spectroscopic parameters of intervertebral disc material; to determine emission spectra common for all intervertebral discs; to create a background for further spectroscopic investigation where no histological specimen will be available. Material and Methods: 20 patients, 68 frozen sections of 20 μm thickness from operatively removed intervertebral disc hernia were excited by Nd:YAG microlaser STA-01-TH third harmonic 355 nm light throw 0, 1 mm fiber. Spectrophotometer OceanOptics USB2000 was used for spectra collection. Mathematical analysis of spectra was performed by ORIGIN multiple Gaussian peaks analysis. Results: In each specimen of disc hernia were found distinct maximal spectral peaks of 4 types supporting the histological evaluation of mixture content of the hernia. Fluorescence in the spectral regions 370-700 nm was detected in the disc hernias. The main spectral component was at 494 nm and the contribution of the components with the peak wavelength values at 388 nm, 412 nm and 435±5 nm were varying in the different groups of samples. In comparison to average spectrum of all cases, there are 4 groups of different spectral signatures in the region 400-500 nm in the patient groups, supporting a clinical data on different clinical features of the patients. Discussion and Conclusion: besides the classical open discectomy, new minimally invasive techniques of treating intervertebral disc emerge (PLDD). Intervertebral disc in these techniques is assessed by needle, no histological specimen is taken. Spectroscopic investigation via fiber optics through the

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 ...

Effects of the Post Multi-Fiber Agreement on Bangladesh Readymade Garments Sector

OpenAIRE

Dey, Palash-Kishore; Sumon, Md-Tawfique-Hasan

2009-01-01

The thesis “Effects of the Post Multi-fiber Agreement on Bangladesh Ready Made Garments Sector” is a part of our M.Sc. in Business Administration Program. The thesis paper on this topic is done under the supervision of Mr. Göran Alsén, Professor of Blekinge Institute of Technology (BTH) Ronneby, Sweden. In our country garment industry has been playing most vital role in our national economy, foreign exchange earnings, employment, growth in other sector and most prominently women employment. I...

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.

Extracting Optical Fiber Background from Surface-Enhanced Raman Spectroscopy Spectra Based on Bi-Objective Optimization Modeling.

Science.gov (United States)

Huang, Jie; Shi, Tielin; Tang, Zirong; Zhu, Wei; Liao, Guanglan; Li, Xiaoping; Gong, Bo; Zhou, Tengyuan

2017-08-01

We propose a bi-objective optimization model for extracting optical fiber background from the measured surface-enhanced Raman spectroscopy (SERS) spectrum of the target sample in the application of fiber optic SERS. The model is built using curve fitting to resolve the SERS spectrum into several individual bands, and simultaneously matching some resolved bands with the measured background spectrum. The Pearson correlation coefficient is selected as the similarity index and its maximum value is pursued during the spectral matching process. An algorithm is proposed, programmed, and demonstrated successfully in extracting optical fiber background or fluorescence background from the measured SERS spectra of rhodamine 6G (R6G) and crystal violet (CV). The proposed model not only can be applied to remove optical fiber background or fluorescence background for SERS spectra, but also can be transferred to conventional Raman spectra recorded using fiber optic instrumentation.

Multi-wavelength and multi-colour temporal and spatial optical solitons

DEFF Research Database (Denmark)

Kivshar, Y. S.; Sukhorukov, A. A.; Ostrovskaya, E. A.

2000-01-01

We present an overview of several novel types of multi- component envelope solitary waves that appear in fiber and waveguide nonlinear optics. In particular, we describe multi-channel solitary waves in bit-parallel-wavelength fiber transmission systems for high performance computer networks, multi......-color parametric spatial solitary waves due to cascaded nonlinearities of quadratic materials, and quasiperiodic envelope solitons in Fibonacci optical superlattices....

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.

Efficient design of gain-flattened multi-pump Raman fiber amplifiers using least squares support vector regression

Science.gov (United States)

Chen, Jing; Qiu, Xiaojie; Yin, Cunyi; Jiang, Hao

2018-02-01

An efficient method to design the broadband gain-flattened Raman fiber amplifier with multiple pumps is proposed based on least squares support vector regression (LS-SVR). A multi-input multi-output LS-SVR model is introduced to replace the complicated solving process of the nonlinear coupled Raman amplification equation. The proposed approach contains two stages: offline training stage and online optimization stage. During the offline stage, the LS-SVR model is trained. Owing to the good generalization capability of LS-SVR, the net gain spectrum can be directly and accurately obtained when inputting any combination of the pump wavelength and power to the well-trained model. During the online stage, we incorporate the LS-SVR model into the particle swarm optimization algorithm to find the optimal pump configuration. The design results demonstrate that the proposed method greatly shortens the computation time and enhances the efficiency of the pump parameter optimization for Raman fiber amplifier design.

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...

Spectroscopically Enhanced Method and System for Multi-Factor Biometric Authentication

Science.gov (United States)

Pishva, Davar

This paper proposes a spectroscopic method and system for preventing spoofing of biometric authentication. One of its focus is to enhance biometrics authentication with a spectroscopic method in a multifactor manner such that a person's unique ‘spectral signatures’ or ‘spectral factors’ are recorded and compared in addition to a non-spectroscopic biometric signature to reduce the likelihood of imposter getting authenticated. By using the ‘spectral factors’ extracted from reflectance spectra of real fingers and employing cluster analysis, it shows how the authentic fingerprint image presented by a real finger can be distinguished from an authentic fingerprint image embossed on an artificial finger, or molded on a fingertip cover worn by an imposter. This paper also shows how to augment two widely used biometrics systems (fingerprint and iris recognition devices) with spectral biometrics capabilities in a practical manner and without creating much overhead or inconveniencing their users.

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.

Capacity Enhancement for Hybrid Fiber-Wireless Channels with 46.8Gbit/sWireless Multi-CAP Transmission over 50m at W-Band

DEFF Research Database (Denmark)

Rommel, Simon; Puerta Ramírez, Rafael; Vegas Olmos, Juan José

2017-01-01

Transmission of a 46.8 Gbit/s multi-band CAP signal is experimentally demonstrated over a 50 m W-band radio-over-fiber link. Bit error rates below 3.8×10-3 are achieved, employing nine CAP bands with bit and power loading.......Transmission of a 46.8 Gbit/s multi-band CAP signal is experimentally demonstrated over a 50 m W-band radio-over-fiber link. Bit error rates below 3.8×10-3 are achieved, employing nine CAP bands with bit and power loading....

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....

Measurement of spatial refractive index distributions of fusion spliced optical fibers by digital holographic microtomography

Science.gov (United States)

Pan, Feng; Deng, Yating; Ma, Xichao; Xiao, Wen

2017-11-01

Digital holographic microtomography is improved and applied to the measurements of three-dimensional refractive index distributions of fusion spliced optical fibers. Tomographic images are reconstructed from full-angle phase projection images obtained with a setup-rotation approach, in which the laser source, the optical system and the image sensor are arranged on an optical breadboard and synchronously rotated around the fixed object. For retrieving high-quality tomographic images, a numerical method is proposed to compensate the unwanted movements of the object in the lateral, axial and vertical directions during rotation. The compensation is implemented on the two-dimensional phase images instead of the sinogram. The experimental results exhibit distinctly the internal structures of fusion splices between a single-mode fiber and other fibers, including a multi-mode fiber, a panda polarization maintaining fiber, a bow-tie polarization maintaining fiber and a photonic crystal fiber. In particular, the internal structure distortion in the fusion areas can be intuitively observed, such as the expansion of the stress zones of polarization maintaining fibers, the collapse of the air holes of photonic crystal fibers, etc.

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.

Multi-sample immunoassay inside optical fiber capillary enabled by evanescent wave detection

Directory of Open Access Journals (Sweden)

Chun-Wei Wang

2016-03-01

Full Text Available A novel evanescent wave-based (EW microfluidic capillary fiber-optic biosensor (MCFOB has been developed using capillaries as a transducer embedded in a multichannel device to enhance the collection efficiency of the fluorescence signal. The capillary serves dual roles as a waveguide and a container, enabling more straightforward, consistent, and compact biosensor packaging compared to conventional optical fiber biosensors and microfluidic systems. In order to detect multiple samples in one device, the biosensor incorporates a polydimethysiloxane (PDMS multi-channel device, which also serves as cladding for the biosensor. In addition, this biosensor only consumes 10 μl of a sample and does not require hydrofluoric acid etching in the fabrication process. The orientation for signal collection is optimized by comparing the lateral and normal signal directions for detected glyceraldehyde 3-phosphate dehydrogenase (GAPDH. C-reactive protein (CRP is used to validate the MCFOB, and the limit of detection (LOD for CRP in the MCFOB is 1.94 ng/ml (74 pM. Moreover, the real-time measurement is demonstrated to verify that the evanescent wave is the only exciting light source in the MCFOB, which gives the potential for real-time measurement applications. Keywords: C-reactive protein, Capillary, Fiber-optic, Microfluidic, Evanescent wave, Immunoassay

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.

Shape Sensing Using a Multi-Core Optical Fiber Having an Arbitrary Initial Shape in the Presence of Extrinsic Forces

Science.gov (United States)

Rogge, Matthew D. (Inventor); Moore, Jason P. (Inventor)

2014-01-01

Shape of a multi-core optical fiber is determined by positioning the fiber in an arbitrary initial shape and measuring strain over the fiber's length using strain sensors. A three-coordinate p-vector is defined for each core as a function of the distance of the corresponding cores from a center point of the fiber and a bending angle of the cores. The method includes calculating, via a controller, an applied strain value of the fiber using the p-vector and the measured strain for each core, and calculating strain due to bending as a function of the measured and the applied strain values. Additionally, an apparent local curvature vector is defined for each core as a function of the calculated strain due to bending. Curvature and bend direction are calculated using the apparent local curvature vector, and fiber shape is determined via the controller using the calculated curvature and bend direction.

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

4.7 Gbit/s transmission over 50m long 1mm diameter multi-core plastic optical fiber

NARCIS (Netherlands)

Yang, H.; Tangdiongga, E.; Lee, S.C.J.; Okonkwo, C.M.; Boom, van den H.P.A.; Randel, S.; Koonen, A.M.J.

2010-01-01

We report, for the first time, 4.7 Gbit/s transmission over 50 m long 1 mm diameter multi-core step-index plastic optical fiber, employing discrete multitone techniques and low-cost optical transceiver. A spectral efficiency of 13 bit/s/Hz is demonstrated.

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.

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.

Development of a TiO{sub 2}-coated optical fiber reactor for water decontamination; Developpement d'un reacteur a base de fibres optiques photocatalytiquement actives pour la depollution de l'eau

Energy Technology Data Exchange (ETDEWEB)

Danion, A

2004-09-15

The objective of this study was to built and to study a photo-reactor composed by TiO{sub 2}-coated optical fibers for water decontamination. The physico-chemical characteristics and the optical properties of the TiO{sub 2} coating were first studied. Then, the influences of different parameters as the coating thickness, the coating length and the coating volume were investigated both on the light transmission in the TiO{sub 2}- coated fiber and on the photo-catalytic activity of the fiber for a model compound (malic acid). The photo-catalytic degradation of malic acid was optimized using the experimental design methodology allowing to build a multi-fiber reactor comprising 57 optical fibers. The photo-degradation of malic acid was conducted in the multi-fiber reactor and it was demonstrated that the multi-fiber reactor was more efficient than the single-fiber reactor at the same fibers density. Finally, the multi-fiber reactor was applied to the photo-degradation of a fungicide, called fenamidone, and a degradation pathway was proposed. (author)

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.

Intermolecular interaction of fosinopril with bovine serum albumin (BSA): The multi-spectroscopic and computational investigation.

Science.gov (United States)

Zhou, Kai-Li; Pan, Dong-Qi; Lou, Yan-Yue; Shi, Jie-Hua

2018-04-16

The intermolecular interaction of fosinopril, an angiotensin converting enzyme inhibitor with bovine serum albumin (BSA), has been investigated in physiological buffer (pH 7.4) by multi-spectroscopic methods and molecular docking technique. The results obtained from fluorescence and UV absorption spectroscopy revealed that the fluorescence quenching mechanism of BSA induced by fosinopril was mediated by the combined dynamic and static quenching, and the static quenching was dominant in this system. The binding constant, K b , value was found to lie between 2.69 × 10 3 and 9.55 × 10 3  M -1 at experimental temperatures (293, 298, 303, and 308 K), implying the low or intermediate binding affinity between fosinopril and BSA. Competitive binding experiments with site markers (phenylbutazone and diazepam) suggested that fosinopril preferentially bound to the site I in sub-domain IIA on BSA, as evidenced by molecular docking analysis. The negative sign for enthalpy change (ΔH 0 ) and entropy change (ΔS 0 ) indicated that van der Waals force and hydrogen bonds played important roles in the fosinopril-BSA interaction, and 8-anilino-1-naphthalenesulfonate binding assay experiments offered evidence of the involvements of hydrophobic interactions. Moreover, spectroscopic results (synchronous fluorescence, 3-dimensional fluorescence, and Fourier transform infrared spectroscopy) indicated a slight conformational change in BSA upon fosinopril interaction. Copyright © 2018 John Wiley & Sons, Ltd.

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.

Self-healing in single and multiple fiber(s reinforced polymer composites

Directory of Open Access Journals (Sweden)

Woldesenbet E.

2010-06-01

Full Text Available You Polymer composites have been attractive medium to introduce the autonomic healing concept into modern day engineering materials. To date, there has been significant research in self-healing polymeric materials including several studies specifically in fiber reinforced polymers. Even though several methods have been suggested in autonomic healing materials, the concept of repair by bleeding of enclosed functional agents has garnered wide attention by the scientific community. A self-healing fiber reinforced polymer composite has been developed. Tensile tests are carried out on specimens that are fabricated by using the following components: hollow and solid glass fibers, healing agent, catalysts, multi-walled carbon nanotubes, and a polymer resin matrix. The test results have demonstrated that single fiber polymer composites and multiple fiber reinforced polymer matrix composites with healing agents and catalysts have provided 90.7% and 76.55% restoration of the original tensile strength, respectively. Incorporation of functionalized multi-walled carbon nanotubes in the healing medium of the single fiber polymer composite has provided additional efficiency. Healing is found to be localized, allowing multiple healing in the presence of several cracks.

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...

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...

THE zCOSMOS 10k-BRIGHT SPECTROSCOPIC SAMPLE

International Nuclear Information System (INIS)

Lilly, Simon J.; Maier, Christian; Carollo, Marcella; Caputi, Karina; Le Brun, Vincent; Kneib, Jean-Paul; Le Fevre, Olivier; De la Torre, Sylvain; De Ravel, Loic; Mainieri, Vincenzo; Mignoli, Marco; Zamorani, Gianni; Bardelli, Sandro; Bolzonella, Micol; Coppa, Graziano; Scodeggio, Marco; Contini, Thierry; Renzini, Alvio; Bongiorno, Angela; Cucciati, Olga

2009-01-01

We present spectroscopic redshifts of a large sample of galaxies with I AB -1 , independent of redshift. The reliability of individual redshifts is described by a Confidence Class that has been empirically calibrated through repeat spectroscopic observations of over 600 galaxies. There is very good agreement between spectroscopic and photometric redshifts for the most secure Confidence Classes. For the less secure Confidence Classes, there is a good correspondence between the fraction of objects with a consistent photometric redshift and the spectroscopic repeatability, suggesting that the photometric redshifts can be used to indicate which of the less secure spectroscopic redshifts are likely right and which are probably wrong, and to give an indication of the nature of objects for which we failed to determine a redshift. Using this approach, we can construct a spectroscopic sample that is 99% reliable and which is 88% complete in the sample as a whole, and 95% complete in the redshift range 0.5 < z < 0.8. The luminosity and mass completeness levels of the zCOSMOS-bright sample of galaxies is also discussed.

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

Design of Multi-core Fiber Patch Panel for Space Division Multiplexing Implementations

Science.gov (United States)

González, Luz E.; Morales, Alvaro; Rommel, Simon; Jørgensen, Bo F.; Porras-Montenegro, N.; Tafur Monroy, Idelfonso

2018-03-01

A multi-core fiber (MCF) patch panel was designed, allowing easy coupling of individual signals to and from a 7-core MCF. The device was characterized, measuring insertion loss and cross talk, finding highest insertion loss and lowest crosstalk at 1300 nm with values of 9.7 dB and -36.5 dB respectively, while at 1600 nm insertion loss drops to 4.8 dB and crosstalk increases to -24.1 dB. Two MCF splices between the fan-in module, the MCF, and the fan-out module are included in the characterization, and splicing parameters are discussed.

Interfacial enhancement of carbon fiber/nylon 12 composites by grafting nylon 6 to the surface of carbon fiber

Science.gov (United States)

Hui, Chen; Qingyu, Cai; Jing, Wu; Xiaohong, Xia; Hongbo, Liu; Zhanjun, Luo

2018-05-01

Nylon 6 (PA6) grafted onto carbon fiber (CF) after chemical oxidation treatment was in an attempt to reinforce the mechanical properties of carbon fiber composites. Scanning electronic microscopy (SEM), Fourier transform infrared analysis (FT-IR), X-ray photoelectron spectroscope (XPS) and thermogravimetric analysis (TG) were selected to characterize carbon fibers with different surface treated. Experimental results showed that PA6 was grafted uniformly on the fiber surface through the anionic polymerization. A large number of functional groups were introduced to the fiber surface and the surface roughness was increased. After grafting PA6 on the oxidized carbon fibers, it played an important role on improving the interfacial adhesion between the fibers and the matrix by improving PA12 wettability, increasing chemical bonding and mechanical interlocking. Compared with the desized CF composites, the tensile strength of PA6-CF/PA12 composites was increased by 30.8% from 53.9 MPa to 70.2 MPa. All results indicated that grafting PA6 onto carbon fiber surface was an effective method to enhance the mechanical strength of carbon fiber/nylon 12 composites.

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.

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.

Zigbee networking technology and its application in Lamost optical fiber positioning and control system

Science.gov (United States)

Jin, Yi; Zhai, Chao; Gu, Yonggang; Zhou, Zengxiang; Gai, Xiaofeng

2010-07-01

4,000 fiber positioning units need to be positioned precisely in LAMOST(Large Sky Area Multi-object Optical Spectroscopic Telescope) optical fiber positioning & control system, and every fiber positioning unit needs two stepper motors for its driven, so 8,000 stepper motors need to be controlled in the entire system. Wireless communication mode is adopted to save the installing space on the back of the focal panel, and can save more than 95% external wires compared to the traditional cable control mode. This paper studies how to use the ZigBee technology to group these 8000 nodes, explores the pros and cons of star network and tree network in order to search the stars quickly and efficiently. ZigBee technology is a short distance, low-complexity, low power, low data rate, low-cost two-way wireless communication technology based on the IEEE 802.15.4 protocol. It based on standard Open Systems Interconnection (OSI): The 802.15.4 standard specifies the lower protocol layers-the physical layer (PHY), and the media access control (MAC). ZigBee Alliance defined on this basis, the rest layers such as the network layer and application layer, and is responsible for high-level applications, testing and marketing. The network layer used here, based on ad hoc network protocols, includes the following functions: construction and maintenance of the topological structure, nomenclature and associated businesses which involves addressing, routing and security and a self-organizing-self-maintenance functions which will minimize consumer spending and maintenance costs. In this paper, freescale's 802.15.4 protocol was used to configure the network layer. A star network and a tree network topology is realized, which can build network, maintenance network and create a routing function automatically. A concise tree network address allocate algorithm is present to assign the network ID automatically.

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.

Investigation of Mechanical Properties and Morphology of Multi-Walled Carbon Nanotubes Reinforced Cellulose Acetate Fibers

Directory of Open Access Journals (Sweden)

Quazi Nahida Sultana

2017-11-01

Full Text Available Cellulose acetate (CA fibers were reinforced with multi-walled carbon nanotubes (MWCNTs at 0.5%, 1.0%, 1.5% and 2.0%. Yield strength, ultimate tensile strength, fracture strain and toughness of the nanocomposite fiber increased up to 1.5 wt. % of the carbon nanotube (CNT loading, however, further inclusion (2.0% of MWCNTs in CA decreased the mechanical properties. Experimental properties were also compared with analytical predictions using a Shear lag model for strength and the rule of mixture for modulus. A solution spinning process, coupled with sonication, mixing, and extrusion, was used to process the CNT-reinforced composite fiber. Scanning electron microscopy (SEM images of the cross sections of neat CA and CA-MWCNT fibers showed the formation of voids and irregular features. The enhanced interconnected fibrillation in the CNT-reinforced CA samples resulted in improved mechanical properties, which were observed by tensile testing. Fourier transform infrared spectroscopy (FTIR spectra showed the area under the curve for C–H bonding after the inclusion of CNT. There was no significant shift of wavenumber for the inclusion of MWCNT in the CA matrix, which indicates that the sonication process of the CNT-loaded solution did not degrade the CA bonding structure.

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.

A compressed sensing approach for resolution improvement in fiber-bundle based endomicroscopy

Science.gov (United States)

Dumas, John P.; Lodhi, Muhammad A.; Bajwa, Waheed U.; Pierce, Mark C.

2018-02-01

Endomicroscopy techniques such as confocal, multi-photon, and wide-field imaging have all been demonstrated using coherent fiber-optic imaging bundles. While the narrow diameter and flexibility of fiber bundles is clinically advantageous, the number of resolvable points in an image is conventionally limited to the number of individual fibers within the bundle. We are introducing concepts from the compressed sensing (CS) field to fiber bundle based endomicroscopy, to allow images to be recovered with more resolvable points than fibers in the bundle. The distal face of the fiber bundle is treated as a low-resolution sensor with circular pixels (fibers) arranged in a hexagonal lattice. A spatial light modulator is located conjugate to the object and distal face, applying multiple high resolution masks to the intermediate image prior to propagation through the bundle. We acquire images of the proximal end of the bundle for each (known) mask pattern and then apply CS inversion algorithms to recover a single high-resolution image. We first developed a theoretical forward model describing image formation through the mask and fiber bundle. We then imaged objects through a rigid fiber bundle and demonstrate that our CS endomicroscopy architecture can recover intra-fiber details while filling inter-fiber regions with interpolation. Finally, we examine the relationship between reconstruction quality and the ratio of the number of mask elements to the number of fiber cores, finding that images could be generated with approximately 28,900 resolvable points for a 1,000 fiber region in our platform.

Ultra-Weak Fiber Bragg Grating Sensing Network Coated with Sensitive Material for Multi-Parameter Measurements

OpenAIRE

Bai, Wei; Yang, Minghong; Hu, Chenyuan; Dai, Jixiang; Zhong, Xuexiang; Huang, Shuai; Wang, Gaopeng

2017-01-01

A multi-parameter measurement system based on ultra-weak fiber Bragg grating (UFBG) array with sensitive material was proposed and experimentally demonstrated. The UFBG array interrogation principle is time division multiplex technology with two semiconductor optical amplifiers as timing units. Experimental results showed that the performance of the proposed UFBG system is almost equal to that of traditional FBG, while the UFBG array system has obvious superiority with potential multiplexing ...

Multi-Modal Inference in Animacy Perception for Artificial Object

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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.

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.

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.

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

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.

Hollow fiber: a biophotonic implant for live cells

Science.gov (United States)

Silvestre, Oscar F.; Holton, Mark D.; Summers, Huw D.; Smith, Paul J.; Errington, Rachel J.

2009-02-01

The technical objective of this study has been to design, build and validate biocompatible hollow fiber implants based on fluorescence with integrated biophotonics components to enable in fiber kinetic cell based assays. A human osteosarcoma in vitro cell model fiber system has been established with validation studies to determine in fiber cell growth, cell cycle analysis and organization in normal and drug treated conditions. The rationale for implant development have focused on developing benchmark concepts in standard monolayer tissue culture followed by the development of in vitro hollow fiber designs; encompassing imaging with and without integrated biophotonics. Furthermore the effect of introducing targetable biosensors into the encapsulated tumor implant such as quantum dots for informing new detection readouts and possible implant designs have been evaluated. A preliminary micro/macro imaging approach has been undertaken, that could provide a mean to track distinct morphological changes in cells growing in a 3D matrix within the fiber which affect the light scattering properties of the implant. Parallel engineering studies have showed the influence of the optical properties of the fiber polymer wall in all imaging modes. Taken all together, we show the basic foundation and the opportunities for multi-modal imaging within an in vitro implant format.

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

On-chip grating coupler array on the SOI platform for fan-in/fan-out of multi-core fibers with low insertion loss and crosstalk

DEFF Research Database (Denmark)

Ding, Yunhong; Ye, Feihong; Peucheret, Christophe

2014-01-01

We design and fabricate a compact multi-core fiber fan-in/fan-out using a fully-etched grating coupler array on the SOI platform. Lowest coupling loss of 6.8 dB with 3 dB bandwidth of 48 nm and crosstalk lower than ×32 dB are demonstrated.......We design and fabricate a compact multi-core fiber fan-in/fan-out using a fully-etched grating coupler array on the SOI platform. Lowest coupling loss of 6.8 dB with 3 dB bandwidth of 48 nm and crosstalk lower than ×32 dB are demonstrated....

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

Directory of Open Access Journals (Sweden)

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

Directory of Open Access Journals (Sweden)

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

Directory of Open Access Journals (Sweden)

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.

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.

AKARI INFRARED CAMERA SURVEY OF THE LARGE MAGELLANIC CLOUD. II. THE NEAR-INFRARED SPECTROSCOPIC CATALOG

International Nuclear Information System (INIS)

Shimonishi, Takashi; Onaka, Takashi; Kato, Daisuke; Sakon, Itsuki; Ita, Yoshifusa; Kawamura, Akiko; Kaneda, Hidehiro

2013-01-01

We performed a near-infrared spectroscopic survey toward an area of ∼10 deg 2 of the Large Magellanic Cloud (LMC) with the infrared satellite AKARI. Observations were carried out as part of the AKARI Large-area Survey of the Large Magellanic Cloud (LSLMC). The slitless multi-object spectroscopic capability of the AKARI/IRC enabled us to obtain low-resolution (R ∼ 20) spectra in 2-5 μm for a large number of point sources in the LMC. As a result of the survey, we extracted about 2000 infrared spectra of point sources. The data are organized as a near-infrared spectroscopic catalog. The catalog includes various infrared objects such as young stellar objects (YSOs), asymptotic giant branch (AGB) stars, supergiants, and so on. It is shown that 97% of the catalog sources have corresponding photometric data in the wavelength range from 1.2 to 11 μm, and 67% of the sources also have photometric data up to 24 μm. The catalog allows us to investigate near-infrared spectral features of sources by comparison with their infrared spectral energy distributions. In addition, it is estimated that about 10% of the catalog sources are observed at more than two different epochs. This enables us to study a spectroscopic variability of sources by using the present catalog. Initial results of source classifications for the LSLMC samples are presented. We classified 659 LSLMC spectra based on their near-infrared spectral features by visual inspection. As a result, it is shown that the present catalog includes 7 YSOs, 160 C-rich AGBs, 8 C-rich AGB candidates, 85 O-rich AGBs, 122 blue and yellow supergiants, 150 red super giants, and 128 unclassified sources. Distributions of the classified sources on the color-color and color-magnitude diagrams are discussed in the text. Continuous wavelength coverage and high spectroscopic sensitivity in 2-5 μm can only be achieved by space observations. This is an unprecedented large-scale spectroscopic survey toward the LMC in the near

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

Directory of Open Access Journals (Sweden)

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

A SEARCH FOR L/T TRANSITION DWARFS WITH Pan-STARRS1 AND WISE: DISCOVERY OF SEVEN NEARBY OBJECTS INCLUDING TWO CANDIDATE SPECTROSCOPIC VARIABLES

International Nuclear Information System (INIS)

Best, William M. J.; Liu, Michael C.; Magnier, Eugene A.; Aller, Kimberly M.; Burgett, W. S.; Chambers, K. C.; Hodapp, K. W.; Kaiser, N.; Kudritzki, R.-P.; Morgan, J. S.; Tonry, J. L.; Wainscoat, R. J.; Deacon, Niall R.; Dupuy, Trent J.; Redstone, Joshua; Price, P. A.

2013-01-01

We present initial results from a wide-field (30,000 deg 2 ) search for L/T transition brown dwarfs within 25 pc using the Pan-STARRS1 and Wide-field Infrared Survey Explorer (WISE) surveys. Previous large-area searches have been incomplete for L/T transition dwarfs, because these objects are faint in optical bands and have near-infrared (near-IR) colors that are difficult to distinguish from background stars. To overcome these obstacles, we have cross-matched the Pan-STARRS1 (optical) and WISE (mid-IR) catalogs to produce a unique multi-wavelength database for finding ultracool dwarfs. As part of our initial discoveries, we have identified seven brown dwarfs in the L/T transition within 9-15 pc of the Sun. The L9.5 dwarf PSO J140.2308+45.6487 and the T1.5 dwarf PSO J307.6784+07.8263 (both independently discovered by Mace et al.) show possible spectroscopic variability at the Y and J bands. Two more objects in our sample show evidence of photometric J-band variability, and two others are candidate unresolved binaries based on their spectra. We expect our full search to yield a well-defined, volume-limited sample of L/T transition dwarfs that will include many new targets for study of this complex regime. PSO J307.6784+07.8263 in particular may be an excellent candidate for in-depth study of variability, given its brightness (J = 14.2 mag) and proximity (11 pc)

Fiber Optic Sensors for Health Monitoring of Morphing Airframes. Part 2; Chemical Sensing Using Optical Fibers with Bragg Gratings

Science.gov (United States)

Wood, Karen; Brown, Timothy; Rogowski, Robert; Jensen, Brian

2000-01-01

Part 1 of this two part series described the fabrication and calibration of Bragg gratings written into a single mode optical fiber for use in strain and temperature monitoring. Part 2 of the series describes the use of identical fibers and additional multimode fibers, both with and without Bragg gratings, to perform near infrared spectroscopy. The demodulation system being developed at NASA Langley Research Center currently requires the use of a single mode optical fiber. Attempts to use this single mode fiber for spectroscopic analysis are problematic given its small core diameter, resulting in low signal intensity. Nonetheless, we have conducted a preliminary investigation using a single mode fiber in conjunction with an infrared spectrometer to obtain spectra of a high-performance epoxy resin system. Spectra were obtained using single mode fibers that contained Bragg gratings; however, the peaks of interest were barely discernible above the noise. The goal of this research is to provide a multipurpose sensor in a single optical fiber capable of measuring a variety of chemical and physical properties.

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

High-resolution wavefront shaping with a photonic crystal fiber for multimode fiber imaging

NARCIS (Netherlands)

Amitonova, L. V.; Descloux, A.; Petschulat, J.; Frosz, M. H.; Ahmed, G.; Babic, F.; Jiang, X.; Mosk, A. P.; Russell, P. S. J.; Pinkse, P.W.H.

2016-01-01

We demonstrate that a high-numerical-aperture photonic crystal fiber allows lensless focusing at an unparalleled res- olution by complex wavefront shaping. This paves the way toward high-resolution imaging exceeding the capabilities of imaging with multi-core single-mode optical fibers. We analyze

Novel scaffold design with multi-grooved PLA fibers

International Nuclear Information System (INIS)

Chung, Sangwon; King, Martin W; Gamcsik, Mike P

2011-01-01

A novel prototype nonwoven textile structure containing polylactide (PLA) multigrooved fibers has been proposed as a possible scaffold material for superior cell attachment and proliferation. Grooved cross-sectional fibers with larger surface area were obtained by a bi-component spinning system and the complete removal of the sacrificial component was confirmed by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and x-ray photon spectroscopy (XPS) analysis. These PLA nonwoven scaffolds containing the grooved fibers exhibited enhanced wettability, greater flexibility and tensile properties, and a larger surface area compared to a traditional PLA nonwoven fabric containing round fibers. To evaluate cellular attachment on the two types of PLA nonwoven scaffolds, NIH 3T3 fibroblasts were cultured for up to 12 days. It was evident that the initial cellular attachment was superior on the scaffold with grooved fibers, which was confirmed by MTT viability assay (p < 0.01) and SEM analysis. In the future, by modulating the size of the grooves on the fibers, such a scaffold material with a large surface area could serve as an alternative matrix for culturing different types of cells.

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.

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.

A pure silica ytterbium-doped sol–gel-based fiber laser

International Nuclear Information System (INIS)

Baz, Assaad; El Hamzaoui, Hicham; Fsaifes, Ihsan; Bouwmans, Géraud; Bouazaoui, Mohamed; Bigot, Laurent

2013-01-01

In this letter it is demonstrated that the sol–gel route combined with fiber fabrication by the stack and draw method can be used to realize efficient fiber lasers. More precisely, a pure silica ytterbium-doped photonic crystal fiber with a core obtained by the sol–gel polymeric technique is studied, and a laser efficiency of more than 73% is achieved for a laser emission around 1034 nm. The optical and spectroscopic properties of the monolith and fiber are investigated, together with the sensitivity of the fiber to photodarkening. The dimensions of the ytterbium-doped monolith combined with the uniform doping and refractive index that are reported make this technique particularly interesting for the realization of large-mode area fibers. (letter)

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

Multi-chord fiber-coupled interferometry of supersonic plasma jets (invited)

International Nuclear Information System (INIS)

Merritt, Elizabeth C.; Lynn, Alan G.; Gilmore, Mark A.; Thoma, Carsten; Loverich, John; Hsu, Scott C.

2012-01-01

A multi-chord fiber-coupled interferometer is being used to make time-resolved density measurements of supersonic argon plasma jets on the Plasma Liner Experiment. The long coherence length of the laser (>10 m) allows signal and reference path lengths to be mismatched by many meters without signal degradation, making for a greatly simplified optical layout. Measured interferometry phase shifts are consistent with a partially ionized plasma in which both positive and negative phase shift values are observed depending on the ionization fraction. In this case, both free electrons and bound electrons in ions and neutral atoms contribute to the index of refraction. This paper illustrates how the interferometry data, aided by numerical modeling, are used to derive total jet density, jet propagation velocity (∼15–50 km/s), jet length (∼20–100 cm), and 3D expansion.

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

MSE spectrograph optical design: a novel pupil slicing technique

Science.gov (United States)

Spanò, P.

2014-07-01

The Maunakea Spectroscopic Explorer shall be mainly devoted to perform deep, wide-field, spectroscopic surveys at spectral resolutions from ~2000 to ~20000, at visible and near-infrared wavelengths. Simultaneous spectral coverage at low resolution is required, while at high resolution only selected windows can be covered. Moreover, very high multiplexing (3200 objects) must be obtained at low resolution. At higher resolutions a decreased number of objects (~800) can be observed. To meet such high demanding requirements, a fiber-fed multi-object spectrograph concept has been designed by pupil-slicing the collimated beam, followed by multiple dispersive and camera optics. Different resolution modes are obtained by introducing anamorphic lenslets in front of the fiber arrays. The spectrograph is able to switch between three resolution modes (2000, 6500, 20000) by removing the anamorphic lenses and exchanging gratings. Camera lenses are fixed in place to increase stability. To enhance throughput, VPH first-order gratings has been preferred over echelle gratings. Moreover, throughput is kept high over all wavelength ranges by splitting light into more arms by dichroic beamsplitters and optimizing efficiency for each channel by proper selection of glass materials, coatings, and grating parameters.

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

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.

Chronic in vivo stability assessment of carbon fiber microelectrode arrays

Science.gov (United States)

Patel, Paras R.; Zhang, Huanan; Robbins, Matthew T.; Nofar, Justin B.; Marshall, Shaun P.; Kobylarek, Michael J.; Kozai, Takashi D. Y.; Kotov, Nicholas A.; Chestek, Cynthia A.

2016-12-01

Objective. Individual carbon fiber microelectrodes can record unit activity in both acute and semi-chronic (∼1 month) implants. Additionally, new methods have been developed to insert a 16 channel array of carbon fiber microelectrodes. Before assessing the in vivo long-term viability of these arrays, accelerated soak tests were carried out to determine the most stable site coating material. Next, a multi-animal, multi-month, chronic implantation study was carried out with carbon fiber microelectrode arrays and silicon electrodes. Approach. Carbon fibers were first functionalized with one of two different formulations of PEDOT and subjected to accelerated aging in a heated water bath. After determining the best PEDOT formula to use, carbon fiber arrays were chronically implanted in rat motor cortex. Some rodents were also implanted with a single silicon electrode, while others received both. At the end of the study a subset of animals were perfused and the brain tissue sliced. Tissue sections were stained for astrocytes, microglia, and neurons. The local reactive responses were assessed using qualitative and quantitative methods. Main results. Electrophysiology recordings showed the carbon fibers detecting unit activity for at least 3 months with average amplitudes of ∼200 μV. Histology analysis showed the carbon fiber arrays with a minimal to non-existent glial scarring response with no adverse effects on neuronal density. Silicon electrodes showed large glial scarring that impacted neuronal counts. Significance. This study has validated the use of carbon fiber microelectrode arrays as a chronic neural recording technology. These electrodes have demonstrated the ability to detect single units with high amplitude over 3 months, and show the potential to record for even longer periods. In addition, the minimal reactive response should hold stable indefinitely, as any response by the immune system may reach a steady state after 12 weeks.

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.

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.

GALAXY CLUSTERS IN THE LINE OF SIGHT TO BACKGROUND QUASARS. III. MULTI-OBJECT SPECTROSCOPY

International Nuclear Information System (INIS)

Andrews, H.; Barrientos, L. F.; Padilla, N.; Lacerna, I.; López, S.; Lira, P.; Maureira, M. J.; Gilbank, D. G.; Ellingson, E.; Gladders, M. D.; Yee, H. K. C.

2013-01-01

We present Gemini/GMOS-S multi-object spectroscopy of 31 galaxy cluster candidates at redshifts between 0.2 and 1.0 and centered on QSO sight lines taken from López et al. The targets were selected based on the presence of an intervening Mg II absorption system at a similar redshift to that of a galaxy cluster candidate lying at a projected distance 71 -1 Mpc from the QSO sight line (a p hotometric hit ) . The absorption systems span rest-frame equivalent widths between 0.015 and 2.028 Å. Our aim was three-fold: (1) to identify the absorbing galaxies and determine their impact parameters, (2) to confirm the galaxy cluster candidates in the vicinity of each quasar sightline, and (3) to determine whether the absorbing galaxies reside in galaxy clusters. In this way, we are able to characterize the absorption systems associated with cluster members. Our main findings are as follows. (1) We identified 10 out of 24 absorbing galaxies with redshifts between 0.2509 ≤ z gal ≤ 1.0955, up to an impact parameter of 142 h 71 -1 kpc and a maximum velocity difference of 280 km s –1 . (2) We spectroscopically confirmed 20 out of 31 cluster/group candidates, with most of the confirmed clusters/groups at z –1 from galaxy clusters/groups, in addition to two new ones related to galaxy group environments. These numbers imply efficiencies of 71% in finding such systems with MOS spectroscopy. This is a remarkable result since we defined a photometric hit as those cluster-absorber pairs having a redshift difference Δz = 0.1. The general population of our confirmed absorbing galaxies have luminosities L B ∼L B * and mean rest-frame colors (R c – z') typical of S cd galaxies. From this sample, absorbing cluster galaxies hosting weak absorbers are consistent with lower star formation activity than the rest, which produce strong absorption and agree with typical Mg II absorbing galaxies found in the literature. Our spectroscopic confirmations lend support to the selection of

Gel spinning of PVA composite fibers with high content of multi-walled carbon nanotubes and graphene oxide hybrids

International Nuclear Information System (INIS)

Wei, Yizhe; Lai, Dengpan; Zou, Liming; Ling, Xinlong; Lu, Hongwei; Xu, Yongjing

2015-01-01

In this report, poly (vinyl alcohol) (PVA) composite fibers with high content of multi-walled carbon nanotubes and graphene oxide (MWCNTs-GO) hybrids were prepared by gel spinning, and were characterized by TGA, DSC, SEM, XL-2 yarn strength tester and electrical conductivity measurement. The total content of MWCNTs-GO hybrids in the PVA composite fibers, which is up to 25 wt%, was confirmed by TGA analysis. The DSC measurement shows that the melting and crystallization peaks decreased after the addition of nano-fillers. This is due to the reason that the motion of PVA chains is completely confined by strong hydrogen bonding interaction between PVA and nano-fillers. After the addtion of GO, the dispersibility of MWCNTs in composite fibers improved slightly. And the tensile strength and Young's modulus increased by 38% and 67%, respectively. This is caused by the increased hydrogen bonding interaction and synergistic effect through hybridization of MWCNTs and GO. More significantly, the electrical conductivity of PVA/MWCNTs/GO composite fibers enhanced by three orders of magnitude with the addition of GO. (paper)

Development of a Lower-SWaP, RAD-Tolerant, Thermally Stable High Speed Fiber Optics Network for Harsh Environment Applications, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The proposed Phase I objectives and work plan, carried through to completion, will result in the development of a RAD-tolerant, high-speed, multi-channel fiber...

Modeling fiber Bragg grating device networks in photomechanical polymer optical fibers

Science.gov (United States)

Lanska, Joseph T.; Kuzyk, Mark G.; Sullivan, Dennis M.

2015-09-01

We report on the modeling of fiber Bragg grating (FBG) networks in poly(methyl methacrylate) (PMMA) polymer fibers doped with azo dyes. Our target is the development of Photomechanical Optical Devices (PODs), comprised of two FBGs in series, separated by a Fabry-Perot cavity of photomechanical material. PODs exhibit photomechanical multi-stability, with the capacity to access multiple length states for a fixed input intensity when a mechanical shock is applied. Using finite-difference time-domain (FDTD) numerical methods, we modeled the photomechanical response of both Fabry-Perot and Bragg-type PODs in a single polymer optical fiber. The polymer fiber was modeled as an instantaneous Kerr-type nonlinear χ(3) material. Our model correctly predicts the essential optical features of FBGs as well as the photomechanical multi-stability of nonlinear Fabry-Perot cavity-based PODs. Networks of PODs may provide a framework for smart shape-shifting materials and fast optical computation where the decision process is distributed over the entire network. In addition, a POD can act as memory, and its response can depend on input history. Our models inform and will accelerate targeted development of novel Bragg grating-based polymer fiber device networks for a variety of applications in optical computing and smart materials.

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.

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)

New planetary nebulae in the outskirts of the Andromeda Galaxy discovered with the Guoshoujing Telescope (LAMOST)

International Nuclear Information System (INIS)

Yuan Haibo; Liu Xiaowei; Huo Zhiying; Zhang Huihua; Zhang Huawei; Zhao Yongheng; Chen Jianjun; Bai Zhongrui; Zhang Haotong; Yan Hongliang; Ren Juanjuan; Sun Shiwei; GarcIa-Benito, Ruben; Xiang Maosheng; Zhang Yong; Li Yeping; Lu Qishuai; Wang You; Ni Jijun; Wang Hai

2010-01-01

Planetary nebulae (PNe) are good tracers of the stellar populations, chemical composition and dynamics of their host galaxies. This paper reports the discovery of new PNe in the outskirts of the Andromeda Galaxy (M 31) with the Guoshoujing Telescope (GSJT, formerly named the Large Sky Area Multi-Object Fiber Spectroscopic Telescope-LAMOST) during its early commissioning phase. In total, 36 candidates selected from SDSS photometry are confirmed in terms of their PN nature, including 17 new discoveries and another 19 previously known emission line objects. Their positions, spectra, radial velocities and m 5007 magnitudes are presented. We discuss the potential for detecting more PNe in M31 with GSJT's multi-object spectroscopy and the related applications in studies of the dynamics and chemistry of M 31 and its assemblage history. (editor's recommendation)

Proposal of AAA-battery-size one-shot ATR Fourier spectroscopic imager for on-site analysis: Simultaneous measurement of multi-components with high accuracy

Science.gov (United States)

Hosono, Satsuki; Qi, Wei; Sato, Shun; Suzuki, Yo; Fujiwara, Masaru; Hiramatsu, Hiroyuki; Suzuki, Satoru; Abeygunawardhana, P. K. W.; Wada, Kenji; Nishiyama, Akira; Ishimaru, Ichiro

2015-03-01

For simultaneous measurement of multi-components on-site like factories, the ultra-compact (diameter: 9[mm], length: 45[mm], weight: 200[g]) one-shot ATR (Attenuated Total Reflection) Fourier spectroscopic imager was proposed. Because the proposed one-shot Fourier spectroscopic imaging is based on spatial-phase-shift interferometer, interferograms could be obtained with simple optical configurations. We introduced the transmission-type relativeinclined phase-shifter, that was constructed with a cuboid prism and a wedge prism, onto the optical Fourier transform plane of infinity corrected optical systems. And also, small light-sources and cameras in the mid-infrared light region, whose size are several millimeter on a side, are essential components for the ultra-compact spectroscopic configuration. We selected the Graphite light source (light source area: 1.7×1.7[mm], maker: Hawkeye technologies) whose radiation factor was high. Fortunately, in these days we could apply the cost-effective 2-dimensional light receiving device for smartphone (e.g. product name: LEPTON, maker: FLIR, price: around 400USD). In the case of alcoholic drinks factory, conventionally workers measure glucose and ethanol concentrations by bringing liquid solution back to laboratories every day. The high portable spectroscopy will make it possible to measure multi-components simultaneously on manufacturing scene. But we found experimentally that absorption spectrum of glucose and water and ethanol were overlapped each other in near infrared light region. But for mid-infrared light region, we could distinguish specific absorption peaks of glucose (@10.5[μm]) and ethanol (@11.5[μm]) independently from water absorption. We obtained standard curve between absorption (@9.6[μm]) and ethanol concentration with high correlation coefficient 0.98 successfully by ATR imaging-type 2-dimensional Fourier spectroscopy (wavelength resolution: 0.057[μm]) with the graphite light source (maker: Hawkeye

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.

[Study on spectral gain characterization of FWM processes with multi-frequency pumps in photonic crystal fiber].

Science.gov (United States)

Hui, Zhan-Qiang

2011-10-01

Spectral gain induced by four-wave-mixing with multi-frequency pump was investigated by exploiting the data signal and continue lights co-propagation in dispersion flattened high nonlinear photonic crystal fiber (PCF). The effects of wavelength drift of pump lights, polarization state of orthogonal or parallel of pump lights, polarization mismatch of signal light versus orthogonal pump lights, total power of signal and probe light on the spectrum gain were analyzed. The results show that good FWM gain effects with multi-frequency pump can be obtained in 36.4 nm wavelength range when power ratio of pump to probe light is appropriate and with identical polarization. Furthermore, the gain of FWM with multi-frequency pump is very sensitive to polarization fluctuation and the different idle waves obtain different gain with the variation in signal polarization state. Moreover, the impact of pump numbers was investigated. The obtained results would be helpful for further research on ultrahigh-speed all optical signal processing devices exploiting the FWM with multi-frequency pump in PCF for future photonics network.

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.

The LAMOST spectroscopic survey of globular clusters in M31 and M33. I. catalog and new identifications

International Nuclear Information System (INIS)

Chen, Bing-Qiu; Liu, Xiao-Wei; Xiang, Mao-Sheng; Huang, Yang; Sun, Ning-Chen; Wang, Chun; Ren, Juan-Juan; Zhang, Hua-Wei; Yuan, Hai-Bo; Rebassa-Mansergas, Alberto; Huo, Zhi-Ying; Yang, Ming; Zhang, Yong; Hou, Yong-Hui; Wang, Yue-Fei

2015-01-01

We present a catalog of 908 objects observed with the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) in fields in the vicinity of M31 and M33, targeted as globular clusters (GCs) and candidates. The targets include known GCs and candidates selected from the literature, as well as new candidates selected from the Sloan Digital Sky Survey (SDSS). Analysis shows that 356 of them are likely GCs with various confidence levels, while the remaining ones turn out to be background galaxies and quasars, stars and H ii regions in M31 or foreground Galactic stars. The 356 likely GCs include 298 bona fide GCs and 26 candidates known in the literature. Three candidates, selected from the Revised Bologna Catalog of M31 GCs and candidates (RBC) and one possible cluster from Johnson et al., are confirmed to be bona fide clusters. We search for new GCs in the halo of the M31 among the new candidates selected from the SDSS photometry. Based on radial velocities yielded by LAMOST spectra and visual examination of the SDSS images, we find 28 objects, 5 bona fide and 23 likely GCs. Among the five bona fide GCs, three have been recently discovered independently by others, and the remaining 25 are our new identifications, including two bona fide ones. The newly identified objects fall at projected distances ranging from 13 to 265kpc from M31. Of the two newly discovered bona fide GCs, one is located near M33, probably a GC belonging to M33. The other bona fide GC falls on the Giant Stream with a projected distance of 78 kpc from M31. Of the 23 newly identified likely GCs, one has a projected distance of about 265 kpc from M31 and could be an intergalactic cluster. (paper)

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 ...

Enhanced optical fiber fluorometer using a periodic perturbation in the fiber core

Science.gov (United States)

Chiniforooshan, Yasser; Bock, Wojtek J.; Ma, Jianjun

2013-10-01

Tracing of the specific chemicals and biological agents in a solution is becoming a vital interest in health, security and safety industries. Although a number of standard laboratory-based testing systems exists for detecting such targets, but the fast, real-time and on-site methods could be more efficient and cost-effective. One of the most common ways to detect a target in the solution is to use the fluorophore molecules which will be selectively attached to the targets and will emit or quench the fluorescence in presence of the target. The fiber-optic fluorometers are developed for inexpensive and portable detection. In this paper, we explain a novel multi-segment fiber structure which uses the periodic perturbation on the side-wall of a highly multi-mode fiber to enhance collecting the fluorescent light. This periodic perturbation is fabricated and optimized on the core of the fiber using a CO2 laser. The theoretical explanation to show the physical principle of the structure is followed by the experimental evidence of its functioning.

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

3D-Mössbauer spectroscopic microscope for mc-Si solar cell evaluation

Energy Technology Data Exchange (ETDEWEB)

Ino, Y., E-mail: y-ino@ob.sist.ac.jp; Soejima, H.; Hayakawa, K.; Yukihira, K.; Tanaka, K.; Fujita, H.; Watanabe, T. [Shizuoka Institute of Science and Technology (Japan); Ogai, K.; Moriguchi, K.; Harada, Y. [APCO. Ltd. (Japan); Yoshida, Y. [Shizuoka Institute of Science and Technology (Japan)

2016-12-15

A 3D-Mössbauer Spectroscopic Microscope is developed to evaluate Fe impurities in multi-crystalline Si solar cells, which combines the Mössbauer spectroscopic microscope with a scanning electron microscope (SEM), an electron beam induced current (EBIC), an electron backscatter diffraction (EBSD), and an electron energy analyzer (HV-CSA). In addition, a new moving-coil-actuator with a liner encoder of 100 nm-resolution is incorporated for the operations with both a constant velocity and a constant acceleration mode successfully with the same precision as that obtained by the conventional transducers. Furthermore, a new multi-capillary X-ray lens is designed to achieve a γ-ray spot size less than 100 μm in diameter. The new microscope provides us to investigate the space correlation between Fe impurities and the lattice defects such as grain boundaries in multi-crystalline Si solar cells.

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

Embedded Active Fiber Optic Sensing Network for Structural Health Monitoring in Harsh Environments

Energy Technology Data Exchange (ETDEWEB)

Wang, Anbo [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

2016-09-30

This report summarizes technical progress on the program “Embedded Active Fiber Optic Sensing Network for Structural Health Monitoring in Harsh Environments” funded by the National Energy Technology Laboratory of the U.S. Department of Energy, and performed by the Center for Photonics Technology at Virginia Tech. The objective of this project is to develop a first-of-a-kind technology for remote fiber optic generation and detection of acoustic waves for structural health monitoring in harsh environments. During the project period, which is from April 1, 2013 to Septemeber 30, 2016, three different acoustic generation mechanisms were studied in detail for their applications in building a fiber optic acoustic generation unit (AGU), including laser induced plasma breakdown (LIP), Erbium-doped fiber laser absorption, and metal laser absorption. By comparing the performance of the AGUs designed based on these three mechanisms and analyzing the experimental results with simulations, the metal laser absorption method was selected to build a complete fiber optic structure health monitoring (FO-SHM) system for the proposed high temperature multi-parameter structure health monitoring application. Based on the simulation of elastic wave propagation and fiber Bragg grating acoustic pulse detection, an FO-SHM element together with a completed interrogation system were designed and built. This system was first tested on an aluminum piece in the low-temperature range and successfully demonstrated its capability of multi-parameter monitoring and multi-point sensing. In the later stages of the project, the research was focused on improving the surface attachment design and preparing the FO-SHM element for high temperature environment tests. After several upgrades to the surface attachment methods, the FO-SHM element was able to work reliably up to 600oC when attached to P91 pipes, which are the target material of this project. In the final stage of this project, this FO

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.

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.

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.

WINDING METHOD SELECTION FOR TECHNICAL IMPLEMENTATION OF FIBER OPTIC COMMUNICATION LINE FOR HIGH-SPEED OBJECT

Directory of Open Access Journals (Sweden)

Vyacheslav A. Loparev

2017-07-01

Full Text Available The paper deals with fiber-optical cable winding methods for realization of fiber-optic communication line with high-speed object. We consider possible options of coils for optical cable winding providing mobility of one of the cable ends on an object. It is shown that the choice of a winding process is caused by the need of ensuring the minimum deformation of fiber-optical micro cable in case of separation from a winding body. It is revealed that the minimum tension value and its unevenness are observed when reeling from coils with a rocket form. Design ratios for determination of winding parameters are given. It is shown that reduction of tension unevenness reduces the jumps of internal tension and probability of break and emergence of optical signal local attenuation. Decrease in internal stresses occurs due to the absence of overlapping of the coils of the underlying layers with the overlying ones. To confirm the operability and the possibility of constructive implementation of the selected winding scheme, experiments were carried out to perform rocket and other types of winding with the use of a specially designed machine model. It is shown that the application of line rocket winding enables to achieve stability when reeling a cable during the movement and excludes breaks. Attenuation of optical signal decreases due to the increase in the bend minimum radius. This phenomenon is explained by reduction of the internal stresses causing optical signal attenuation in the place of cable separation from the coil.

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.

Multi-spectral confocal microendoscope for in-vivo imaging

Science.gov (United States)

Rouse, Andrew Robert

The concept of in-vivo multi-spectral confocal microscopy is introduced. A slit-scanning multi-spectral confocal microendoscope (MCME) was built to demonstrate the technique. The MCME employs a flexible fiber-optic catheter coupled to a custom built slit-scan confocal microscope fitted with a custom built imaging spectrometer. The catheter consists of a fiber-optic imaging bundle linked to a miniature objective and focus assembly. The design and performance of the miniature objective and focus assembly are discussed. The 3mm diameter catheter may be used on its own or routed though the instrument channel of a commercial endoscope. The confocal nature of the system provides optical sectioning with 3mum lateral resolution and 30mum axial resolution. The prism based multi-spectral detection assembly is typically configured to collect 30 spectral samples over the visible chromatic range. The spectral sampling rate varies from 4nm/pixel at 490nm to 8nm/pixel at 660nm and the minimum resolvable wavelength difference varies from 7nm to 18nm over the same spectral range. Each of these characteristics are primarily dictated by the dispersive power of the prism. The MCME is designed to examine cellular structures during optical biopsy and to exploit the diagnostic information contained within the spectral domain. The primary applications for the system include diagnosis of disease in the gastro-intestinal tract and female reproductive system. Recent data from the grayscale imaging mode are presented. Preliminary multi-spectral results from phantoms, cell cultures, and excised human tissue are presented to demonstrate the potential of in-vivo multi-spectral imaging.

Multi-focus beam shaping of high power multimode lasers

Science.gov (United States)

Laskin, Alexander; Volpp, Joerg; Laskin, Vadim; Ostrun, Aleksei

2017-08-01

Beam shaping of powerful multimode fiber lasers, fiber-coupled solid-state and diode lasers is of great importance for improvements of industrial laser applications. Welding, cladding with millimetre scale working spots benefit from "inverseGauss" intensity profiles; performance of thick metal sheet cutting, deep penetration welding can be enhanced when distributing the laser energy along the optical axis as more efficient usage of laser energy, higher edge quality and reduction of the heat affected zone can be achieved. Building of beam shaping optics for multimode lasers encounters physical limitations due to the low beam spatial coherence of multimode fiber-coupled lasers resulting in big Beam Parameter Products (BPP) or M² values. The laser radiation emerging from a multimode fiber presents a mixture of wavefronts. The fiber end can be considered as a light source which optical properties are intermediate between a Lambertian source and a single mode laser beam. Imaging of the fiber end, using a collimator and a focusing objective, is a robust and widely used beam delivery approach. Beam shaping solutions are suggested in form of optics combining fiber end imaging and geometrical separation of focused spots either perpendicular to or along the optical axis. Thus, energy of high power lasers is distributed among multiple foci. In order to provide reliable operation with multi-kW lasers and avoid damages the optics are designed as refractive elements with smooth optical surfaces. The paper presents descriptions of multi-focus optics as well as examples of intensity profile measurements of beam caustics and application results.

Fiber-integrated Brillouin microspectroscopy: Towards Brillouin endoscopy

Directory of Open Access Journals (Sweden)

Irina V. Kabakova

2017-11-01

Full Text Available Brillouin imaging (BI for micromechanical characterization of tissues and biomaterials is a fast-developing field of research with a strong potential for medical diagnosis of disease-modified tissues and cells. Although the principles of BI imply its compatibility with in vivo and in situ measurements, the integration of BI with a flexible catheter, capable of reaching the region of interest within the body, is yet to be reported. Here, for the first time, we experimentally investigate integration of the Brillouin spectroscope with standard optical fiber components to achieve a Brillouin endoscope. The performance of single-fiber and dual-fiber endoscopes are demonstrated and analyzed. We show that a major challenge in construction of Brillouin endoscopes is the strong backward Brillouin scattering in the optical fiber and we present a dual-fiber geometry as a possible solution. Measurements of Brillouin spectra in test liquids (water, ethanol and glycerol are demonstrated using the dual-fiber endoscope and its performance is analyzed numerically with the help of a beam propagation model.

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.

A SEARCH FOR L/T TRANSITION DWARFS WITH Pan-STARRS1 AND WISE: DISCOVERY OF SEVEN NEARBY OBJECTS INCLUDING TWO CANDIDATE SPECTROSCOPIC VARIABLES

Energy Technology Data Exchange (ETDEWEB)

Best, William M. J.; Liu, Michael C.; Magnier, Eugene A.; Aller, Kimberly M.; Burgett, W. S.; Chambers, K. C.; Hodapp, K. W.; Kaiser, N.; Kudritzki, R.-P.; Morgan, J. S.; Tonry, J. L.; Wainscoat, R. J. [Institute for Astronomy, University of Hawaii at Manoa, Honolulu, HI 96822 (United States); Deacon, Niall R. [Max Planck Institute for Astronomy, Koenigstuhl 17, D-69117 Heidelberg (Germany); Dupuy, Trent J. [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Redstone, Joshua [Facebook, 335 Madison Ave, New York, NY 10017-4677 (United States); Price, P. A., E-mail: wbest@ifa.hawaii.edu [Department of Astrophysical Sciences, Princeton University, Princeton, NJ 08544 (United States)

2013-11-10

We present initial results from a wide-field (30,000 deg{sup 2}) search for L/T transition brown dwarfs within 25 pc using the Pan-STARRS1 and Wide-field Infrared Survey Explorer (WISE) surveys. Previous large-area searches have been incomplete for L/T transition dwarfs, because these objects are faint in optical bands and have near-infrared (near-IR) colors that are difficult to distinguish from background stars. To overcome these obstacles, we have cross-matched the Pan-STARRS1 (optical) and WISE (mid-IR) catalogs to produce a unique multi-wavelength database for finding ultracool dwarfs. As part of our initial discoveries, we have identified seven brown dwarfs in the L/T transition within 9-15 pc of the Sun. The L9.5 dwarf PSO J140.2308+45.6487 and the T1.5 dwarf PSO J307.6784+07.8263 (both independently discovered by Mace et al.) show possible spectroscopic variability at the Y and J bands. Two more objects in our sample show evidence of photometric J-band variability, and two others are candidate unresolved binaries based on their spectra. We expect our full search to yield a well-defined, volume-limited sample of L/T transition dwarfs that will include many new targets for study of this complex regime. PSO J307.6784+07.8263 in particular may be an excellent candidate for in-depth study of variability, given its brightness (J = 14.2 mag) and proximity (11 pc)

Fiber-Optic Chemical Sensors and Fiber-Optic Bio-Sensors

Science.gov (United States)

Pospíšilová, Marie; Kuncová, Gabriela; Trögl, Josef

2015-01-01

This review summarizes principles and current stage of development of fiber-optic chemical sensors (FOCS) and biosensors (FOBS). Fiber optic sensor (FOS) systems use the ability of optical fibers (OF) to guide the light in the spectral range from ultraviolet (UV) (180 nm) up to middle infrared (IR) (10 µm) and modulation of guided light by the parameters of the surrounding environment of the OF core. The introduction of OF in the sensor systems has brought advantages such as measurement in flammable and explosive environments, immunity to electrical noises, miniaturization, geometrical flexibility, measurement of small sample volumes, remote sensing in inaccessible sites or harsh environments and multi-sensing. The review comprises briefly the theory of OF elaborated for sensors, techniques of fabrications and analytical results reached with fiber-optic chemical and biological sensors. PMID:26437407

Fiber-Optic Chemical Sensors and Fiber-Optic Bio-Sensors.

Science.gov (United States)

Pospíšilová, Marie; Kuncová, Gabriela; Trögl, Josef

2015-09-30

This review summarizes principles and current stage of development of fiber-optic chemical sensors (FOCS) and biosensors (FOBS). Fiber optic sensor (FOS) systems use the ability of optical fibers (OF) to guide the light in the spectral range from ultraviolet (UV) (180 nm) up to middle infrared (IR) (10 μm) and modulation of guided light by the parameters of the surrounding environment of the OF core. The introduction of OF in the sensor systems has brought advantages such as measurement in flammable and explosive environments, immunity to electrical noises, miniaturization, geometrical flexibility, measurement of small sample volumes, remote sensing in inaccessible sites or harsh environments and multi-sensing. The review comprises briefly the theory of OF elaborated for sensors, techniques of fabrications and analytical results reached with fiber-optic chemical and biological sensors.

Mitigating the impact of the DESI fiber assignment on galaxy clustering

Energy Technology Data Exchange (ETDEWEB)

Burden, Angela; Padmanabhan, Nikhil [Department of Physics, Yale University, New Haven, CT 06511 (United States); Cahn, Robert N.; White, Martin J. [Physics Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720 (United States); Samushia, Lado, E-mail: angela.burden@yale.edu, E-mail: nikhil.padmanabhan@yale.edu, E-mail: rncahn@lbl.gov, E-mail: mwhite@berkeley.edu, E-mail: lado@phys.ksu.edu [Physics Department, Kansas State University, 116 Cardwell Hall, 1228 N. 17th St. Manhattan, KS 66506 (United States)

2017-03-01

We present a simple strategy to mitigate the impact of an incomplete spectroscopic redshift galaxy sample as a result of fiber assignment and survey tiling. The method has been designed for the Dark Energy Spectroscopic Instrument (DESI) galaxy survey but may have applications beyond this. We propose a modification to the usual correlation function that nulls the almost purely angular modes affected by survey incompleteness due to fiber assignment. Predictions of this modified statistic can be calculated given a model of the two point correlation function. The new statistic can be computed with a slight modification to the data catalogues input to the standard correlation function code and does not incur any additional computational time. Finally we show that the spherically averaged baryon acoustic oscillation signal is not biased by the new statistic.

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-component optical solitary waves

DEFF Research Database (Denmark)

Kivshar, Y. S.; Sukhorukov, A. A.; Ostrovskaya, E. A.

2000-01-01

We discuss several novel types of multi-component (temporal and spatial) envelope solitary waves that appear in fiber and waveguide nonlinear optics. In particular, we describe multi-channel solitary waves in bit-parallel-wavelength fiber transmission systems for highperformance computer networks......, multi-color parametric spatial solitary waves due to cascaded nonlinearities of quadratic materials, and quasiperiodic envelope solitons due to quasi-phase-matching in Fibonacci optical superlattices. (C) 2000 Elsevier Science B.V. All rights reserved....

Surface decoration of short-cut polyimide fibers with multi-walled carbon nanotubes and their application for reinforcement of lightweight PC/ABS composites

Science.gov (United States)

Zhang, Le; Han, Enlin; Wu, Yulun; Wang, Xiaodong; Wu, Dezhen

2018-06-01

The surface decoration of short-cut polyimide (PI) fibers with multi-walled carbon nanotubes (MWCNTs) was performed by fabricating a polydopamine (PDA) coating layer on the fiber surface and then immobilizing MWCNTs onto the coating layer via covalent bonding. This successful surface decoration was confirmed by scanning electron microscopy, X-ray photoelectron spectroscopy, Fourier-transform infrared microscopy and static water contact angle. The application of the surface-decorated PI fibers as reinforcing fibers for reinforcement of polycarbonate (PC)/acrylonitrile-butadiene-styrene copolymer (ABS) alloy was investigated, which indicated that the MWCNTs-decorated PI fibers not only could effectively reinforce the PC/ABS alloy but also generated a significant lightweighting effect on the resulting composites. The maximum mechanical properties were achieved for the composites at a fiber content of 20 wt.% and a fiber length of 3 mm. This significant reinforcement effect is attributed to the enhancement of interaction bonding strength between the fibers and matrix as a result of the surface decoration of PI fibers with MWCNTs. The morphological investigation suggested that fiber rupture was the major energy dissipation mechanism in the tensile and impact failures, whereas fiber debonding and pullout were partly involved in the fracture energy dissipation. In addition, the presence of surface-decorated PI fibers slightly enhanced the thermal stability and load bearing capability of composites. This work can provide a type of high-performance lightweight composite material for automobile and aviation industries.

Hollow optical-fiber based infrared spectroscopy for measurement of blood glucose level by using multi-reflection prism.

Science.gov (United States)

Kino, Saiko; Omori, Suguru; Katagiri, Takashi; Matsuura, Yuji

2016-02-01

A mid-infrared attenuated total reflection (ATR) spectroscopy system employing hollow optical fibers and a trapezoidal multi-reflection ATR prism has been developed to measure blood glucose levels. Using a multi-reflection prism brought about higher sensitivity, and the flat and wide contact surface of the prism resulted in higher measurement reproducibility. An analysis of in vivo measurements of human inner lip mucosa revealed clear signatures of glucose in the difference spectra between ones taken during the fasting state and ones taken after ingestion of glucose solutions. A calibration plot based on the absorption peak at 1155 cm(-1) that originates from the pyranose ring structure of glucose gave measurement errors less than 20%.

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.

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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.

Towards diode-pumped mid-infrared praseodymium-ytterbium-doped fluoride fiber lasers

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Woodward, R. I.; Hudson, D. D.; Jackson, S. D.

2018-02-01

We explore the potential of a new mid-infrared laser transition in praseodymium-doped fluoride fiber for emission around 3.4 μm, which can be conveniently pumped by 0.975 μm diodes via ytterbium sensitizer co-doping. Optimal cavity designs are determined through spectroscopic measurements and numerical modeling, suggesting that practical diode-pumped watt-level mid-infrared fiber sources beyond 3 μm could be achieved.

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.

A multi-objective approach to improve SWAT model calibration in alpine catchments

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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.

Hybrid fiber grating cavity for multi-parametric sensing.

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Paladino, Domenico; Quero, Giuseppe; Caucheteur, Christophe; Mégret, Patrice; Cusano, Andrea

2010-05-10

We propose an all-fiber hybrid cavity involving two unbalanced uniform fiber Bragg gratings (FBGs) written at both sides of a tilted FBG (TFBG) to form an all-fiber interferometer. This configuration provides a wavelength gated reflection signal with interference fringes depending on the cavity features modulated by spectral dips associated to the wavelength dependent optical losses due to cladding mode coupling occurring along the TFBG. Such a robust structure preserves the advantages of uniform FBGs in terms of interrogation methods and allows the possibility of simultaneous physical and chemical sensing. (c) 2010 Optical Society of America.

A multi-objective framework to predict flows of ungauged rivers within regions of sparse hydrometeorologic observation

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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

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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.

Environmental concentrations of fibers with fluoro-edenitic composition and population exposure in Biancavilla (Sicily, Italy

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Biagio Maria Bruni

2014-06-01

Full Text Available INTRODUCTION. The town of Biancavilla (Sicily was included in the National Priorities List of Contaminated Sites due to environmental dispersion of amphibole fibers owing to the extraction of materials from a local quarry. The present report summarizes results from several, hitherto unpublished, environmental surveys carried out in the area, as well as from published analyses of the chemistry and composition of fibers. METHODS. Data included here comprises environmental fiber concentrations by scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS analysis in soil, indoor and outdoor air, personal monitoring, as well as a chemical characterization of the fibers. The full chemical structure and spectroscopic characterization of fibers were obtained through a multi-analytical approach: SEM-EDS, X-ray powder diffraction (XRPD, as well as Mössbauer (MS and Fourier transform infrared (FT-IR spectroscopies. RESULTS. Data analyzed provided a spatial and temporal picture of fiber concentrations in Biancavilla, and a qualitative assessment of population exposure. Results suggest that until 2000, the population had been exposed to high levels of amphibole fibers. Mitigation measures adopted since 2001, gradually reduced exposure levels to about 0.10.4 ff/l. Previous studies on fibrous amphiboles from Biancavilla reported considerable chemical variability. Differences in composition, especially concerning the presence of Si, Ca, Fe, and Na, were found both within and between samples. Compared to the previously investigated prismatic fluoro-edenite, these fibrous fluorine amphiboles consistently showed higher average values of Si and Fe content, whereas Ca was significantly lower, which we consider a distinctive characteristic of the fluorine fibrous variety. CONCLUSIONS. The population of Biancavilla had been highly exposed to a suite of fibrous amphiboles for over 50 years. Dust mitigation measures have gradually reduced exposure, but

Multi-objective optimization of solid waste flows: environmentally sustainable strategies for municipalities.

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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

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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

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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

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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.

A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

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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