WorldWideScience

Sample records for hydra multi-object spectrograph

  1. Cosmological surveys with multi-object spectrographs

    CERN Document Server

    Colless, Matthew

    2016-01-01

    Multi-object spectroscopy has been a key technique contributing to the current era of 'precision cosmology'. From the first exploratory surveys of the large-scale structure and evolution of the universe to the current generation of superbly detailed maps spanning a wide range of redshifts, multi-object spectroscopy has been a fundamentally important tool for mapping the rich structure of the cosmic web and extracting cosmological information of increasing variety and precision. This will continue to be true for the foreseeable future, as we seek to map the evolving geometry and structure of the universe over the full extent of cosmic history in order to obtain the most precise and comprehensive measurements of cosmological parameters. Here I briefly summarize the contributions that multi-object spectroscopy has made to cosmology so far, then review the major surveys and instruments currently in play and their prospects for pushing back the cosmological frontier. Finally, I examine some of the next generation ...

  2. IOT Overview: Optical Multi-Object Spectrographs

    Science.gov (United States)

    Schmidtobreick, L.; Bagnulo, S.; Jehin, E.; Marconi, G.; O'Brien, K.; Pompei, E.; Saviane, I.

    We give an introduction to the several instruments that ESO operates and which are able to perform optical multi-object spectroscopy. We point out the standard ways of reducing these spectra, the problems that occur, and the way we deal with them. A short introduction is given on how the quality control is performed.

  3. GNOMOS: The Gemini NIR-Optical Multi Object Spectrograph

    CERN Document Server

    Schiavon, Ricardo P; Chiboucas, Kristin; Diaz, Ruben; Geballe, Tom; Gimeno, German; Gomez, Percy; Hibon, Pascale; Hirst, Paul; Jorgensen, Inger; Labrie, Kathleen; Leggett, Sandy; Lemoine-Busserolle, Marie; Levenson, Nancy; Mason, Rachel; McDermid, Richard; Miller, Bryan; Nitta, Atsuko; Pessev, Peter; Rodgers, Bernadette; Schirmer, Mischa; Trujillo, Chad; Turner, James

    2012-01-01

    This paper is a response to a call for white papers solicited by Gemini Observatory and its Science and Technology Advisory Committee, to help define the science case and requirements for a new Gemini instrument, envisaged to consist of a single-object spectrograph at medium resolution simultaneously covering optical and near-infrared wavelengths. In this white paper we discuss the science case for an alternative new instrument, consisting instead of a multi-object, medium-resolution, high-throughput spectrograph, covering simultaneously the optical and near-infrared slices of the electromagnetic spectrum. We argue that combination of wide wavelength coverage at medium resolution with moderate multiplexing power is an innovative path that will enable the pursuit of fundamental science questions in a variety of astrophysical topics, without compromise of the science goals achievable by single-object spectroscopy on a wide baseline. We present a brief qualitative discussion of the main features of a notional ha...

  4. Mauna Kea Spectrographic Explorer (MSE): a conceptual design for multi-object high resolution spectrograph

    Science.gov (United States)

    Zhang, Kai; Zhu, Yongtian; Hu, Zhongwen

    2016-08-01

    The Maunakea Spectroscopic Explorer (MSE) project will transform the CFHT 3.6m optical telescope into a 10m class dedicated multi-object spectroscopic facility, with an ability to simultaneously measure thousands of objects with a spectral resolution range spanning 2,000 to 40,000. MSE will develop two spectrographic facilities to meet the science requirements. These are respectively, the Low/Medium Resolution spectrographs (LMRS) and High Resolution spectrographs (HRS). Multi-object high resolution spectrographs with total of 1,156 fibers is a big challenge, one that has never been attempted for a 10m class telescope. To date, most spectral survey facilities work in single order low/medium resolution mode, and only a few Wide Field Spectrographs (WFS) provide a cross-dispersion high resolution mode with a limited number of orders. Nanjing Institute of Astronomical Optics and Technology (NIAOT) propose a conceptual design with the use of novel image slicer arrays and single order immersed Volume Phase Holographic (VPH) grating for the MSE multi-object high resolution spectrographs. The conceptual scheme contains six identical fiber-link spectrographs, each of which simultaneously covers three restricted bands (λ/30, λ/30, λ/15) in the optical regime, with spectral resolution of 40,000 in Blue/Visible bands (400nm / 490nm) and 20,000 in Red band (650nm). The details of the design is presented in this paper.

  5. Fireball multi object spectrograph: as-built optic performances

    Science.gov (United States)

    Grange, R.; Milliard, B.; Lemaitre, G.; Quiret, S.; Pascal, S.; Origné, A.; Hamden, E.; Schiminovich, D.

    2016-07-01

    Fireball (Faint Intergalactic Redshifted Emission Balloon) is a NASA/CNES balloon-borne experiment to study the faint diffuse circumgalactic medium from the line emissions in the ultraviolet (200 nm) above 37 km flight altitude. Fireball relies on a Multi Object Spectrograph (MOS) that takes full advantage of the new high QE, low noise 13 μm pixels UV EMCCD. The MOS is fed by a 1 meter diameter parabola with an extended field (1000 arcmin2) using a highly aspherized two mirror corrector. All the optical train is working at F/2.5 to maintain a high signal to noise ratio. The spectrograph (R 2200 and 1.5 arcsec FWHM) is based on two identical Schmidt systems acting as collimator and camera sharing a 2400 g/mm aspherized reflective Schmidt grating. This grating is manufactured from active optics methods by double replication technique of a metal deformable matrix whose active clear aperture is built-in to a rigid elliptical contour. The payload and gondola are presently under integration at LAM. We will present the alignment procedure and the as-built optic performances of the Fireball instrument.

  6. EMIR, the GTC NIR multi-object imager-spectrograph

    Science.gov (United States)

    Garzón, F.; Abreu, D.; Barrera, S.; Becerril, S.; Cairós, L. M.; Díaz, J. J.; Fragoso, A. B.; Gago, F.; Grange, R.; González, C.; López, P.; Patrón, J.; Pérez, J.; Rasilla, J. L.; Redondo, P.; Restrepo, R.; Saavedra, P.; Sánchez, V.; Tenegi, F.; Vallbé, M.

    2007-06-01

    EMIR, currently entering into its fabrication and AIV phase, will be one of the first common user instruments for the GTC, the 10 meter telescope under construction by GRANTECAN at the Roque de los Muchachos Observatory (Canary Islands, Spain). EMIR is being built by a Consortium of Spanish and French institutes led by the Instituto de Astrofísica de Canarias (IAC). EMIR is designed to realize one of the central goals of 10m class telescopes, allowing observers to obtain spectra for large numbers of faint sources in a time-efficient manner. EMIR is primarily designed to be operated as a MOS in the K band, but offers a wide range of observing modes, including imaging and spectroscopy, both long slit and multi-object, in the wavelength range 0.9 to 2.5 μm. It is equipped with two innovative subsystems: a robotic reconfigurable multi-slit mask and dispersive elements formed by the combination of high quality diffraction grating and conventional prisms, both at the heart of the instrument. The present status of development, expected performances, schedule and plans for scientific exploitation are described and discussed. The development and fabrication of EMIR is funded by GRANTECAN and the Plan Nacional de Astronomía y Astrofísica (National Plan for Astronomy and Astrophysics, Spain).

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

    NARCIS (Netherlands)

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

    2012-01-01

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

  8. MOONS: the Multi-Object Optical and Near-infrared Spectrograph for the VLT

    NARCIS (Netherlands)

    M. Cirasuolo; . et al.; L. Kaper; B. Lemasle

    2014-01-01

    MOONS is a new Multi-Object Optical and Near-infrared Spectrograph selected by ESO as a third generation instrument for the Very Large Telescope (VLT). The grasp of the large collecting area offered by the VLT (8.2m diameter), combined with the large multiplex and wavelength coverage (optical to nea

  9. 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

  10. An adjustable slit mechanism for a fiber-fed multi-object spectrograph

    Science.gov (United States)

    Bailey, John I.; Mateo, Mario L.; Bagish, Alan P.; Crane, Jeffrey D.; Slater, Colin T.

    2012-09-01

    Fiber-fed multi-object spectrographs have greatly enhanced the spectroscopic capabilities of the world's premiere telescopes, but their flexibility has typically been limited by a fixed effective slit size that constrains the available resolving power. We present a novel mechanism that, for the first time, equips a fiber-fed spectrograph with multiple discreet slits of different widths. In this paper, we detail the mechanical design of our variable slit mechanism, which is capable of positioning any one of six slits in front of the fibers immediately prior to injection into the spectrograph's optical train. Further, we present the details of related systems necessary to achieve closed loop positioning of the slit mechanism given that no encoder is used. We also briefly discuss our use of open source and open hardware projects in the design. Finally, we describe the control system we have implemented for this subsystem.

  11. The Sydney-AAO Multi-object Integral field spectrograph (SAMI)

    CERN Document Server

    Croom, Scott M; Bland-Hawthorn, Joss; Bryant, Julia J; Fogarty, Lisa; Richards, Samuel; Goodwin, Michael; Farrell, Tony; Miziarski, Stan; Heald, Ron; Jones, D Heath; Lee, Steve; Colless, Matthew; Brough, Sarah; Hopkins, Andrew M; Bauer, Amanda E; Birchall, Michael N; Ellis, Simon; Horton, Anthony; Leon-Saval, Sergio; Lewis, Geraint; Lopez-Sanchez, A R; Min, Seong-Sik; Trinh, Christopher; Trowland, Holly

    2011-01-01

    We demonstrate a novel technology that combines the power of the multi-object spectrograph with the spatial multiplex advantage of an integral field spectrograph (IFS). The Sydney-AAO Multi-object IFS (SAMI) is a prototype wide-field system at the Anglo-Australian Telescope (AAT) that allows 13 imaging fibre bundles ("hexabundles") to be deployed over a 1-degree diameter field of view. Each hexabundle comprises 61 lightly-fused multimode fibres with reduced cladding and yields a 75 percent filling factor. Each fibre core diameter subtends 1.6 arcseconds on the sky and each hexabundle has a field of view of 15 arcseconds diameter. The fibres are fed to the flexible AAOmega double-beam spectrograph, which can be used at a range of spectral resolutions (R=lambda/delta(lambda) ~ 1700-13000) over the optical spectrum (3700-9500A). We present the first spectroscopic results obtained with SAMI for a sample of galaxies at z~0.05. We discuss the prospects of implementing hexabundles at a much higher multiplex over wid...

  12. The Multi-Object, Fiber-Fed Spectrographs for SDSS and the Baryon Oscillation Spectroscopic Survey

    CERN Document Server

    Smee, Stephen; Uomoto, Alan; Roe, Natalie; Schlegel, David; Rockosi, Constance M; Carr, Michael A; Leger, French; Dawson, Kyle S; Olmstead, Matthew D; Brinkmann, Jon; Owen, Russell; Barkhouser, Robert H; Honscheid, Klaus; Harding, Paul; Long, Dan; Lupton, Robert H; Loomis, Craig; Anderson, Lauren; Annis, James; Bernardi, Mariangela; Bhardwaj, Vaishali; Bizyaev, Dmitry; Bolton, Adam S; Brewington, Howard; Briggs, John W; Burles, Scott; Burns, James G; Castander, Francisco; Connolly, Andrew; Davenport, James R; Ebelke, Garrett; Epps, Harland; Feldman, Paul D; Friedman, Scott; Frieman, Joshua; Heckman, Timothy; Hull, Charles L; Knapp, Gillian R; Lawrence, David M; Loveday, Jon; Mannery, Edward J; Malanushenko, Elena; Malanushenko, Viktor; Merrelli, Aronne; Muna, Demitri; Newman, Peter; Nichol, Robert C; Oravetz, Daniel; Pan, Kaike; Pope, Adrian C; Ricketts, Paul G; Shelden, Alaina; Sandford, Dale; Siegmund, Walter; Simmons, Audrey; Smith, D; Snedden, Stephanie; Schneider, Donald P; Strauss, Michael; SubbaRao, Mark; Tremonti, Christy; Waddell, Patrick; York, Donald G

    2012-01-01

    We present the design and performance of the multi-object fiber spectrographs for the Sloan Digital Sky Survey (SDSS) and their upgrade for the Baryon Oscillation Spectroscopic Survey (BOSS). Originally commissioned in Fall 1999 on the 2.5-m aperture Sloan Telescope at Apache Point Observatory, the spectrographs produced more than 1.5 million spectra for the SDSS and SDSS-II surveys, enabling a wide variety of Galactic and extra-galactic science including the first observation of baryon acoustic oscillations in 2005. The spectrographs were upgraded in 2009 and are currently in use for BOSS, the flagship survey of the third-generation SDSS-III project. BOSS will measure redshifts of 1.35 million massive galaxies to redshift 0.7 and Lyman-$\\alpha$ absorption of 160,000 high redshift quasars over 10,000 square degrees of sky, making percent level measurements of the absolute cosmic distance scale of the Universe and placing tight constraints on the equation of state of dark energy. The twin multi-object fiber sp...

  13. MOSAIC: a Multi-Object Spectrograph for the E-ELT

    CERN Document Server

    Kelz, Andreas; Jagourel, Pascal

    2015-01-01

    The instrumentation plan for the European-Extremely Large Telescope foresees a Multi-Object Spectrograph (E-ELT MOS). The MOSAIC project is proposed by a European-Brazilian consortium, to provide a unique MOS facility for astrophysics, studies of the inter-galactic medium and for cosmology. The science cases range from spectroscopy of the most distant galaxies, mass assembly and evolution of galaxies, via resolved stellar populations and galactic archaeology, to planet formation studies. A further strong driver are spectroscopic follow-up observations of targets that will be discovered with the James Webb Space Telescope.

  14. MOSAIC: A Multi-Object Spectrograph for the E-ELT

    Science.gov (United States)

    Kelz, A.; Hammer, F.; Jagourel, P.; MOSAIC Consortium

    2016-10-01

    The instrumentation plan for the European Extremely Large Telescope foresees a Multi-Object Spectrograph (E-ELT MOS). The MOSAIC project is proposed by a European-Brazilian consortium, to provide a unique MOS facility for astrophysics, studies of the inter-galactic medium and for cosmology. The science cases range from spectroscopy of the most distant galaxies, mass assembly and evolution of galaxies, via resolved stellar populations and galactic archaeology, to planet formation studies. A further strong driver is spectroscopic follow-up observations of targets that will be discovered with the James Webb Space Telescope.

  15. Toward accurate radial velocities with the fiber-fed GIRAFFE multi-object VLT spectrograph

    Science.gov (United States)

    Royer, Frederic; Blecha, Andre; North, Pierre; Simond, Gilles; Baratchart, Sebastien; Cayatte, Veronique; Chemin, Laurent; Palsa, Ralf

    2002-12-01

    We describe briefly the Data-Reduction of the VLT fiber-fed multi-object GIRAFFE spectrograph - part of the VLT FLAMES facility. We focus on specific features of GIRAFFE - the simultaneous wavelength calibration - and their impact on the data-reduction strategy. We describe the implementation of the global physical model and we compare the results obtained with the simulated, laboratory and preliminary data. We discuss the influence of critical parameters, the overall accuracy of the wavelength solution, and the stability and the robustness of the global model approach. We address the accuracy of radial velocity measurements illustrated by solar spectra obtained during the Preliminary Acceptance in Europe.

  16. Data Reduction Pipeline for EMIR, the Near-IR Multi-Object Spectrograph for GTC

    Science.gov (United States)

    Pascual, S.; Gallego, J.; Cardiel, N.; Zamorano, J.; Gorgas, F. J.; García-Dabó, C. E.; Gil de Paz, A.

    2006-07-01

    EMIR is a near-infrared wide-field camera and multi-object spectrograph being built for the 10.4m Spanish telescope (Gran Telescopio Canarias, GTC) at La Palma Observatory. The Data Reduction Pipeline, which is being designed and built by the EMIR Universidad Complutense de Madrid group, will be optimized for handling and reducing near-infrared data acquired with EMIR. Both reduced data and associated error frames will be delivered to the end-users as a final product.

  17. A mask quality control tool for the OSIRIS multi-object spectrograph

    Science.gov (United States)

    López-Ruiz, J. C.; Vaz Cedillo, Jacinto Javier; Ederoclite, Alessandro; Bongiovanni, Ángel; González Escalera, Víctor

    2012-09-01

    OSIRIS multi object spectrograph uses a set of user-customised-masks, which are manufactured on-demand. The manufacturing process consists of drilling the specified slits on the mask with the required accuracy. Ensuring that slits are on the right place when observing is of vital importance. We present a tool for checking the quality of the process of manufacturing the masks which is based on analyzing the instrument images obtained with the manufactured masks on place. The tool extracts the slit information from these images, relates specifications with the extracted slit information, and finally communicates to the operator if the manufactured mask fulfills the expectations of the mask designer. The proposed tool has been built using scripting languages and using standard libraries such as opencv, pyraf and scipy. The software architecture, advantages and limits of this tool in the lifecycle of a multiobject acquisition are presented.

  18. Reduction of Integral Field Spectroscopic Data from the Gemini Multi-Object Spectrograph (a commented example)

    CERN Document Server

    Lena, Davide

    2014-01-01

    The use of integral field spectroscopy is becoming increasingly popular, hovewer data reduction is still a difficult process. Here I present a step-by-step guide to the reduction of integral field data acquired with the Gemini Multi-Object Spectrograph (GMOS) on GEMINI. The reduction process, separately applied to a standard star and to the science data, includes bias and sky subtraction, flat-fielding, trimming, wavelength and flux calibration, creation of the cubes for each exposure and final combination into a single cube. Typical problems encoutered during the reduction process are discussed. The command list has been adapted from IRAF scripts given as tutorials at the South American Gemini Data Workshop (S\\~{a}o Jos\\'e dos Campos, Brazil, October 27-30, 2011) and scripts kindly provided by collaborators.

  19. The E-ELT Multi-Object Spectrograph: latest news from MOSAIC

    CERN Document Server

    Hammer, F; Kaper, L; Barbuy, B; Cuby, J G; Roth, M; Jagourel, P; Evans, C J; Puech, M; Fitzsimons, E; Dalton, G; Rodrigues, M

    2016-01-01

    There are 8000 galaxies, including 1600 at z larger than 1.6, which could be simultaneously observed in an E-ELT field of view of 40 sq. arcmin. A considerable fraction of astrophysical discoveries require large statistical samples, which can only be obtained with multi-object spectrographs (MOS). MOSAIC will provide a vast discovery space, enabled by a multiplex of 200 and spectral resolving powers of R=5000 and 20000. MOSAIC will also offer the unique capability of more than 10 "high-definition" (multi-object adaptive optics, MOAO) integral-field units, optimised to investigate the physics of the sources of reionization. The combination of these modes will make MOSAIC the world-leading MOS facility, contributing to all fields of contemporary astronomy, from extra-solar planets, to the study of the halo of the Milky Way and its satellites, and from resolved stellar populations in nearby galaxies out to observations of the earliest "first-light" structures in the Universe. It will also study the distribution ...

  20. The Planning Process for Multi-Object Spectroscopy with the JWST Near-Infrared Spectrograph

    Science.gov (United States)

    Beck, Tracy L.; Karakla, D. M.; Shyrokov, A.; Pontoppidan, K.; Soderblom, D. R.; Valenti, J. A.; Kassin, S. A.; Gilbert, K.; Blair, W. P.; Muzerolle, J.; Tumlinson, J.; Keyes, C. D.; Pavlovsky, C. M.; LeBlanc, T.

    2014-01-01

    The Near-Infrared Spectrograph (NIRSpec) for the James Webb Space Telescope (JWST) will have a powerful multi-object spectroscopy mode using four configurable Micro-Shutter Arrays (MSAs). The contiguous MSA shutters can be opened to form slits on astronomical targets, for simultaneous spectroscopy of up to 100 sources per exposure. The NIRSpec MSA shutters are in a fixed grid pattern, and careful analysis in the observation planning process will be crucial for optimal definition of science exposures. Our goal is to maximize the number of astronomical science sources observed in the fewest number of MSA slit configurations. We are developing algorithms in the NIRSpec MSA Planning Tool (MPT) to improve the quality of planned observations using several common science observing strategies as test use cases. For example, the needs for planning extremely deep exposures on a small number of JWST discovered z > 10 galaxy candidates will differ significantly from the requirements for planning spectral observations on a representative sample of stars from a galactic star cluster catalog. In this poster, we present a high level overview of our plans to develop and optimize the MPT for the JWST NIRSpec multi-object spectroscopy mode.

  1. Design drivers for a wide-field multi-object spectrograph for the William Herschel Telescope

    CERN Document Server

    Balcells, Marc; Carter, David; Dalton, Gavin B; Trager, Scott C; Feltzing, Sofia; Verheijen, Marc A W; Jarvis, Matt; Percival, Will; Abrams, Don C; Agocs, Tibor; Brown, Anthony G A; Cano, Diego; Evans, Chris; Helmi, Amina; Lewis, Ian J; McLure, Ross; Peletier, Reynier F; Perez-Fournon, Ismael; Sharples, Ray M; Tosh, Ian A J; Trujillo, Ignacio; Walton, Nic; Westfall, Kyle B

    2010-01-01

    Wide-field multi-object spectroscopy is a high priority for European astronomy over the next decade. Most 8-10m telescopes have a small field of view, making 4-m class telescopes a particularly attractive option for wide-field instruments. We present a science case and design drivers for a wide-field multi-object spectrograph (MOS) with integral field units for the 4.2-m William Herschel Telescope (WHT) on La Palma. The instrument intends to take advantage of a future prime-focus corrector and atmospheric-dispersion corrector that will deliver a field of view 2 deg in diameter, with good throughput from 370 to 1,000 nm. The science programs cluster into three groups needing three different resolving powers R: (1) high-precision radial-velocities for Gaia-related Milky Way dynamics, cosmological redshift surveys, and galaxy evolution studies (R = 5,000), (2) galaxy disk velocity dispersions (R = 10,000) and (3) high-precision stellar element abundances for Milky Way archaeology (R = 20,000). The multiplex requ...

  2. The Fiber Multi-object Spectrograph (FMOS) Project: the Anglo-Australian Observatory role

    Science.gov (United States)

    Gillingham, Peter R.; Moore, Anna M.; Akiyama, Masayuki; Brzeski, Jurek; Correll, David; Dawson, John; Farrell, Tony J.; Frost, Gabriella; Griesbach, Jason S.; Haynes, Roger; Jones, Damien; Miziarski, Stan; Muller, Rolf; Smedley, Scott; Smith, Greg; Waller, Lew G.; Noakes, Katie; Arridge, Chris

    2003-03-01

    The Fiber Multi-Object Spectrograph (FMOS) project is an Australia-Japan-UK collaboration to design and build a novel 400 fiber positioner feeding two near infrared spectrographs from the prime focus of the Subaru telescope. The project comprises several parts. Those under design and construction at the Anglo-Australian Observatory (AAO) are the piezoelectric actuator driven fiber positioner (Echidna), a wide field (30 arcmin) corrector and a focal plane imager (FPI) used for controlling the positioner and for field acquisition. This paper presents an overview of the AAO share of the FMOS project. It describes the technical infrastructure required to extend the single Echidna "spine" design to a fully functioning multi-fiber instrument, capable of complete field reconfiguration in less than ten minutes. The modular Echidna system is introduced, wherein the field of view is populated by 12 identical rectangular modules, each positioning 40 science fibers and 2 guide fiber bundles. This arrangement allows maintenance by exchanging modules and minimizes the difficulties of construction. The associated electronics hardware, in itself a significant challenge, includes a 23 layer PCB board, able to supply current to each piezoelectric element in the module. The FPI is a dual purpose imaging system translating in two coordinates and is located beneath the assembled modules. The FPI measures the spine positions as well as acquiring sky images for instrument calibration and for field acquisition. An overview of the software is included.

  3. The E-ELT multi-object spectrograph: latest news from MOSAIC

    Science.gov (United States)

    Hammer, F.; Morris, S.; Kaper, L.; Barbuy, B.; Cuby, J. G.; Roth, M.; Jagourel, P.; Evans, C. J.; Puech, M.; Fitzsimons, E.; Dalton, G.; Rodrigues, M.

    2016-08-01

    There are 8000 galaxies, including 1600 at z >= 1.6, which could be simultaneously observed in an E-ELT field of view of 40 arcmin2. A considerable fraction of astrophysical discoveries require large statistical samples, which can only be obtained with multi-object spectrographs (MOS). MOSAIC will provide a vast discovery space, enabled by a multiplex of 200 and spectral resolving powers of R=5000 and 20000. MOSAIC will also offer the unique capability of more than 10 `high-definition' (multi-object adaptive optics, MOAO) integral-field units, optimised to investigate the physics of the sources of reionization. The combination of these modes will make MOSAIC the world-leading MOS facility, contributing to all fields of contemporary astronomy, from extra-solar planets, to the study of the halo of the Milky Way and its satellites, and from resolved stellar populations in nearby galaxies out to observations of the earliest `first-light' structures in the Universe. It will also study the distribution of the dark and ordinary matter at all scales and epochs of the Universe. Recent studies of critical technical issues such as sky-background subtraction and MOAO have demonstrated that such a MOS is feasible with state-of-the-art technology and techniques. Current studies of the MOSAIC team include further trade-offs on the wavelength coverage, a solution for compensating for the non-telecentric new design of the telescope, and tests of the saturation of skylines especially in the near-IR bands. In the 2020s the E-ELT will become the world's largest optical/IR telescope, and we argue that it has to be equipped as soon as possible with a MOS to provide the most efficient, and likely the best way to follow-up on James Webb Space Telescope (JWST) observations.

  4. Science case and requirements for the MOSAIC concept for a multi-object spectrograph for the European Extremely Large Telescope

    NARCIS (Netherlands)

    Evans, C. J.; Puech, M.; Barbuy, B.; Bonifacio, P.; Cuby, J.-G.; Guenther, E.; Hammer, F.; Jagourel, P.; Kaper, L.; Morris, S. L.; Afonso, J.; Amram, P.; Aussel, H.; Basden, A.; Bastian, N.; Battaglia, G.; Biller, B.; Bouché, N.; Caffau, E.; Charlot, S.; Clénet, Y.; Combes, F.; Conselice, C.; Contini, T.; Dalton, G.; Davies, B.; Disseau, K.; Dunlop, J.; Fiore, F.; Flores, H.; Fusco, T.; Gadotti, D.; Gallazzi, A.; Giallongo, E.; Gonçalves, T.; Gratadour, D.; Hill, V.; Huertas-Company, M.; Ibata, R.; Larsen, S.; Le Fèvre, O.; Lemasle, B.; Maraston, C.; Mei, S.; Mellier, Y.; Östlin, G.; Paumard, T.; Pello, R.; Pentericci, L.; Petitjean, P.; Roth, M.; Rouan, D.; Schaerer, D.; Telles, E.; Trager, S.; Welikala, N.; Zibetti, S.; Ziegler, B.

    2014-01-01

    Over the past 18 months we have revisited the science requirements for a multi-object spectrograph (MOS) for the European Extremely Large Telescope (E-ELT). These efforts span the full range of E-ELT science and include input from a broad cross-section of astronomers across the ESO partner countries

  5. MEGARA optical design: the new integral field unit and multi-object spectrograph for the GTC 10m telescope

    Science.gov (United States)

    García-Vargas, María. Luisa; Sánchez-Blanco, Ernesto; Carrasco, Esperanza; Gil de Paz, Armando; Páez, Gonzalo; Pérez, Ana; Gallego, Jesús; Sánchez, Francisco; Vílchez, José M.

    2012-12-01

    We describe the optical design of MEGARA, the future optical Integral Field Unit (IFU) and Multi-Object Spectrograph (MOS) for the 10.4-m Gran Telescopio CANARIAS (GTC). MEGARA is being built by a Consortium of public research institutions led by the Universidad Complutense de Madrid (UCM, Spain) that also includes INAOE (Mexico), IAA-CSIC (Spain) and UPM (Spain).

  6. The Lick-Index Calibration of the GEMINI Multi-Object Spectrographs

    CERN Document Server

    Puzia, Thomas H; 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 arcsecond slit width and 1x1 CCD pixel binning (corresponding to ~2.5 Angstroem spectral resolution) and the other with 0.75 arcsecond slit width and 2x2 binning (~4 Angstroem). We find small and well-defined correction terms for the set of Balmer indices Hbeta, HgammaA, and HdeltaA along with the metallicity sensitive indices Fe5015, Fe5270, Fe5335, Fe5406, Mg2 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 TiO1 and TiO2, with very wide wavelength coverage or indices that sample very weak molecular and atomic absorption features, such as Mg1, as well as indices with...

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

    Energy Technology Data Exchange (ETDEWEB)

    Puzia, Thomas H. [Department of Astronomy and Astrophysics, Pontificia Universidad Católica de Chile, Avenida Vicuña Mackenna 4860, Macul, Santiago (Chile); Miller, Bryan W.; Trancho, Gelys [Gemini Observatory, Casilla 603, La Serena (Chile); Basarab, Brett [Middlebury College, Middlebury, VT 05753 (United States); Mirocha, Jordan T. [Center for Astrophysics and Space Astronomy, University of Colorado, 389 UCB, Boulder, CO 80309 (United States); Butler, Karen, E-mail: tpuzia@astro.puc.cl, E-mail: bmiller@gemini.edu [National Optical Astronomy Observatory, 950 North Cherry Avenue, Tucson, AZ 85719 (United States)

    2013-06-01

    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 {sub A}, and Hδ {sub A} along with the metallicity sensitive indices Fe5015, Fe5270, Fe5335, Fe5406, Mg{sub 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{sub 1} and TiO{sub 2}, with very wide wavelength coverage or indices that sample very weak molecular and atomic absorption features, such as Mg{sub 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.

  8. MOONS: a Multi-Object Optical and Near-infrared Spectrograph for the VLT

    CERN Document Server

    Cirasuolo, M; Bender, R; Bonifacio, P; Evans, C; Kaper, L; Oliva, E; Vanzi, L; Abreu, M; Atad-Ettedgui, E; Babusiaux, C; Bauer, F; Best, P; Bezawada, N; Bryson, I; Cabral, A; Caputi, K; Centrone, M; Chemla, F; Cimatti, A; Cioni, M-R; Clementini, G; Coelho, J; Daddi, E; Dunlop, J; Feltzing, S; Ferguson, A; Flores, H; Fontana, A; Fynbo, J; Garilli, B; Glauser, A; Guinouard, I; Hammer, F; Hastings, P; Hess, A; Ivison, R; Jagourel, P; Jarvis, M; Kauffman, G; Lawrence, A; Lee, D; Licausi, G; Lilly, S; Lorenzetti, D; Maiolino, R; Mannucci, F; McLure, R; Minniti, D; Montgomery, D; Muschielok, B; Nandra, K; Navarro, R; Norberg, P; Origlia, L; Padilla, N; Peacock, J; Pedicini, F; Pentericci, L; Pragt, J; Puech, M; Randich, S; Renzini, A; Ryde, N; Rodrigues, M; Royer, F; Saglia, R; Sanchez, A; Schnetler, H; Sobral, D; Speziali, R; Todd, S; Tolstoy, E; Torres, M; Venema, L; Vitali, F; Wegner, M; Wells, M; Wild, V; Wright, G

    2012-01-01

    MOONS is a new conceptual design for a Multi-Object Optical and Near-infrared Spectrograph for the Very Large Telescope (VLT), selected by ESO for a Phase A study. The baseline design consists of 1000 fibers deployable over a field of view of 500 square arcmin, the largest patrol field offered by the Nasmyth focus at the VLT. The total wavelength coverage is 0.8um-1.8um and two resolution modes: medium resolution and high resolution. In the medium resolution mode (R=4,000-6,000) the entire wavelength range 0.8um-1.8um is observed simultaneously, while the high resolution mode covers simultaneously three selected spectral regions: one around the CaII triplet (at R=8,000) to measure radial velocities, and two regions at R=20,000 one in the J-band and one in the H-band, for detailed measurements of chemical abundances. The grasp of the 8.2m Very Large Telescope (VLT) combined with the large multiplex and wavelength coverage of MOONS - extending into the near-IR - will provide the observational power necessary to...

  9. MOONS: A New Powerful Multi-Object Spectrograph for the VLT

    Science.gov (United States)

    Cirasuolo, M.; MOONS Consortium

    2016-10-01

    MOONS (the Multi-Object Optical and Near-infrared Spectrograph) is a third-generation instrument for the ESO Very Large Telescope (VLT). The large collecting area offered by the VLT (8.2 m diameter), combined with the large multiplex and wavelength coverage (optical to near-IR: 0.64 μm - 1.8 μm) of MOONS will provide the European astronomical community with a powerful, unique instrument able to pioneer a wide range of Galactic, Extragalactic and Cosmological studies, and the crucial follow-up for major facilities such as Gaia, VISTA, Euclid and LSST. MOONS has the observational power needed to unveil galaxy formation and evolution over the entire history of the Universe, from stars in our Milky Way, through the redshift desert, and up to the epoch of the very first galaxies and reionization of the Universe at redshifts of z > 8-9, just a few million years after the Big Bang. From five years of observations MOONS will provide high-quality spectra for >3 M stars in our Galaxy and the Local Group, and for 1-2 M galaxies at z >1 (for an SDSS-like survey), promising to revolutionize our understanding of the Universe. The baseline design consists of 1024 fibers, deployable over a field-of-view of ˜500 sq. arcmin, the largest patrol field offered by the Nasmyth focus at the VLT. The total wavelength coverage is 0.64 μm - 1.8 μm with two spectral resolving power settings: in the medium-resolution mode (R˜4,000-6,000) the entire wavelength range is observed simultaneously, while the high-resolution mode will cover simultaneously selected sub-regions: one region with R˜9,000 near the Ca II triplet to measure stellar radial velocities, and part of the H-band at R˜20,000 for precision measurements of chemical abundances.

  10. Developing an integrated concept for the E-ELT Multi-Object Spectrograph (MOSAIC): design issues and trade-offs

    CERN Document Server

    Rodrigues, Myriam; Fitzsimons, Ewan; Chemla, Fanny; Morris, Tim; Hammer, Francois; Puech, Mathieu; Evans, Christopher; Jagourel, Pascal

    2016-01-01

    We present a discussion of the design issues and trade-offs that have been considered in putting together a new concept for MOSAIC, the multi-object spectrograph for the E-ELT. MOSAIC aims to address the combined science cases for E-ELT MOS that arose from the earlier studies of the multi-object and multi-adaptive optics instruments. MOSAIC combines the advantages of a highly-multiplexed instrument targeting single-point objects with one which has a more modest multiplex but can spatially resolve a source with high resolution (IFU). These will span across two wavebands: visible and near-infrared.

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

    Science.gov (United States)

    Navarro, Ramón; Chemla, Fanny; Bonifacio, Piercarlo; Flores, Hector; Guinouard, Isabelle; Huet, Jean-Michel; Puech, Mathieu; Royer, Frédéric; Pragt, Johannes H.; Wulterkens, Gerben; Sawyer, Eric C.; Caldwell, Martin E.; Tosh, Ian A. J.; Whalley, Martin S.; Woodhouse, Guy F. W.; Spanò, Paolo; Di Marcantonio, Paolo; Andersen, Michael I.; Dalton, Gavin B.; Kaper, Lex; Hammer, François

    2010-07-01

    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 6000, 18000 or 30000, at wavelengths from 370 nm to 1.7 μm, combined with a high multiplex (>200) and a large spectral coverage. Additionally medium and large IFUs are available. The system consists of three main modules: a fibre positioning system, fibres and a spectrograph. The recently finished OPTIMOS-EVE Phase-A study, carried out within the framework of the ESO E-ELT instrumentation studies, has been performed by an international consortium consisting of institutes from France, Netherlands, United Kingdom and Italy. All three main science themes of the E-ELT are covered by this instrument: Planets and Stars; Stars and Galaxies; Galaxies and Cosmology. This paper gives an overview of the OPTIMOS-EVE project, describing the science cases, top level requirements, the overall technical concept and the project management approach. It includes a description of the consortium, highlights of the science drivers and resulting science requirements, an overview of the instrument design and telescope interfaces, the operational concept, expected performance, work breakdown and management structure for the construction of the instrument, cost and schedule.

  12. Lessons learnt and results from the first survey of transiting exoplanet atmospheres using a multi-object spectrograph

    Science.gov (United States)

    Desert, Jean-Michel

    2015-12-01

    We present results from the first comprehensive survey program dedicated to probing transiting exoplanet atmospheres using transmission spectroscopy with a multi-object spectrograph (MOS). Our three-year survey focused on nine close-in giant planets for which the wavelength dependent transit depths in the visible were measured with Gemini/GMOS. In total, about 40 transits (200 hours) have been secured, with each exoplanet observed on average during four transits. This approach allows for a high spectrophotometric precision (200-500 ppm / 10 nm) and for a unique and reliable estimate of systematic uncertainties. We present the main results from this survey, the challenges faced by such an experiment, and the lessons learnt for future MOS observations and instrument designs. We show that the precision achieved by this survey permits us to distinguish hazy atmospheres from cloud-free scenarios. We lay out the challenges that are in front of us whilst preparing future atmospheric reconnaissance of habitable worlds with multi-object spectrographs.

  13. Developing arrayed waveguide grating spectrographs for multi-object astronomical spectroscopy.

    Science.gov (United States)

    Cvetojevic, Nick; Jovanovic, Nemanja; Lawrence, Jon; Withford, Michael; Bland-Hawthorn, Joss

    2012-01-30

    With the aim of utilizing arrayed waveguide gratings for multi-object spectroscopy in the field of astronomy, we outline several ways in which standard telecommunications grade chips should be modified. In particular, by removing the parabolic-horn taper or multimode interference coupler, and injecting with an optical fiber directly, the resolving power was increased threefold from 2400 ± 200 (spectral resolution of 0.63 ± 0.2 nm) to 7000 ± 700 (0.22 ± 0.02 nm) while attaining a throughput of 77 ± 5%. More importantly, the removal of the taper enabled simultaneous off-axis injection from multiple fibers, significantly increasing the number of spectra that can be obtained at once (i.e. the observing efficiency). Here we report that ~12 fibers can be injected simultaneously within the free spectral range of our device, with a 20% reduction in resolving power for fibers placed at 0.8 mm off-centre.

  14. Optical design of MEMS-based infrared multi-object spectrograph concept for the Gemini South Telescope

    Science.gov (United States)

    Chen, Shaojie; Sivanandam, Suresh; Moon, Dae-Sik

    2016-08-01

    We discuss the optical design of an infrared multi-object spectrograph (MOS) concept that is designed to take advantage of the multi-conjugate adaptive optics (MCAO) corrected field at the Gemini South telescope. This design employs a unique, cryogenic MEMS-based focal plane mask to select target objects for spectroscopy by utilizing the Micro-Shutter Array (MSA) technology originally developed for the Near Infrared Spectrometer (NIRSpec) of the James Webb Space Telescope (JWST). The optical design is based on all spherical refractive optics, which serves both imaging and spectroscopic modes across the wavelength range of 0.9-2.5 μm. The optical system consists of a reimaging system, MSA, collimator, volume phase holographic (VPH) grisms, and spectrograph camera optics. The VPH grisms, which are VPH gratings sandwiched between two prisms, provide high dispersing efficiencies, and a set of several VPH grisms provide the broad spectral coverage at high throughputs. The imaging mode is implemented by removing the MSA and the dispersing unit out of the beam. We optimize both the imaging and spectrographic modes simultaneously, while paying special attention to the performance of the pupil imaging at the cold stop. Our current design provides a 1' ♢ 1' and a 0.5' ♢ 1' field of views for imaging and spectroscopic modes, respectively, on a 2048 × 2048 pixel HAWAII-2RG detector array. The spectrograph's slit width and spectral resolving power are 0.18'' and 3,000, respectively, and spectra of up to 100 objects can be obtained simultaneously. We present the overall results of simulated performance using optical model we designed.

  15. 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.

  16. Scientific and technical performance of GMOS: the Gemini Multi-Object Spectrograph

    Science.gov (United States)

    Crampton, David; Murowinski, Richard

    2004-09-01

    GMOS is the first telescope - spectrograph combination that acts as a complete system to deliver enhanced image quality and stability while simultaneously exploiting the large aperture of an 8m telescope. The entire system (optics, mechanics, software, detectors) was designed to take advantage of the best images that the Gemini telescopes produce while being extremely reliable and efficient. The built-in wavefront sensor allows the telescope to quickly point at an object, optimize its focus and then track it precisely for many hours (possibly over several nights) while maintaining perfect telescope and instrument focus and providing first order image compensation. As a result of the carefully-engineered design of its structure and mechanisms and its active flexure control system, GMOS offers unique scientific opportunities. A recent enhancement was the implementation of the "nod and shuffle" technique to give improved sky subtraction for very faint object spectroscopy. Some of the scientific highlights of GMOS' many modes (Imaging, MOS, IFU, precision velocities) are reviewed, and some of the "lessons-learned" during the first few years of operation are described.

  17. Science Case and Requirements for the MOSAIC Concept for a Multi-Object Spectrograph for the European Extremely Large Telescope

    CERN Document Server

    Evans, C J; Barbuy, B; Bonifacio, P; Cuby, J -G; Guenther, E; Hammer, F; Jagourel, P; Kaper, L; Morris, S L; Afonso, J; Amram, P; Aussel, H; Basden, A; Bastian, N; Battaglia, G; Biller, B; Bouché, N; Caffau, E; Charlot, S; Clenet, Y; Combes, F; Conselice, C; Contini, T; Dalton, G; Davies, B; Disseau, K; Dunlop, J; Fiore, F; Flores, H; Fusco, T; Gadotti, D; Gallazzi, A; Giallongo, E; Gonçalves, T; Gratadour, D; Hill, V; Huertas-Company, M; Ibata, R; Larsen, S; Fèvre, O Le; Lemasle, B; Maraston, C; Mei, S; Mellier, Y; Östlin, G; Paumard, T; Pello, R; Pentericci, L; Petitjean, P; Roth, M; Rouan, D; Schaerer, D; Telles, E; Trager, S; Welikala, N; Zibetti, S; Ziegler, B

    2014-01-01

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

  18. Hydra

    DEFF Research Database (Denmark)

    Peder Pedersen, Claus

    2009-01-01

    Præsentation af forskningsprojekt relateret til den græske ø Hydra med fokus på konception og arkitekturtegning.......Præsentation af forskningsprojekt relateret til den græske ø Hydra med fokus på konception og arkitekturtegning....

  19. Hydra

    DEFF Research Database (Denmark)

    Peder Pedersen, Claus; Dinesen, Cort Ross

    2009-01-01

    Beskrivelse af kontekst og baggrund for et forskningsprojekt gennemført på den græske ø Hydra i perioden 2004-2008......Beskrivelse af kontekst og baggrund for et forskningsprojekt gennemført på den græske ø Hydra i perioden 2004-2008...

  20. XMS and NG1dF: extreme multiplex spectrographs for wide-field multi-object spectroscopy

    Science.gov (United States)

    Content, Robert; Barden, Sam; Becerril, Santiago; Boehm, Armin; Clark, Paul; Costillo, Pedro; Dubbeldam, C. Mark; Farrell, Tony; Glazebrook, Karl; Haynes, Roger; Meisenheimer, Klaus; Miziarski, Stan; Nikoloudakis, Nikolaos; Prada, Luis Francisco; Rohloff, Ralf-Rainer; Shanks, Tom; Sharples, Ray M.; Wagner, Karl

    2010-07-01

    Two feasibility studies for spectrographs that can deliver at least 4000 MOS slits over a 1° field at the prime focuses of the Anglo-Australian and Calar Alto Observatories have been completed. We describe the design and science case of the Calar Alto eXtreme Multiplex Spectrograph (XMS) for which an extended study, half way between feasibility study and phase-A, was made. The optical design is quite similar than in the AAO study for the Next Generation 1 degree Field (NG1dF) but the mechanical design of XMS is quite different and much more developed. In a single night, 25000 galaxy redshifts can be measured to z~0.7 and beyond for measuring the Baryon Acoustic Oscillation (BAO) scale and many other science goals. This may provide a low-cost alternative to WFMOS for example and other large fibre spectrographs. The design features four cloned spectrographs which gives a smaller total weight and length than a unique spectrograph to makes it placable at prime focus. The clones use a transparent design including a grism in which all optics are about the size or smaller than the clone rectangular subfield so that they can be tightly packed with little gaps between subfields. Only low cost glasses are used; the variations in chromatic aberrations between bands are compensated by changing a box containing the grism and two adjacent lenses. Three bands cover the 420nm to 920nm wavelength range at 10A resolution while another cover the Calcium triplet at 3A. An optional box does imaging. We however also studied different innovative methods for acquisition without imaging. A special mask changing mechanism was also designed to compensate for the lack of space around the focal plane. Conceptual designs for larger projects (AAT 2º field, CFHT, VISTA) have also been done.

  1. Greedy Set Cover Field Selection for Multi-object Spectroscopy in C++ MPI

    Science.gov (United States)

    Stenborg, T. N.

    2015-09-01

    Multi-object spectrographs allow efficient observation of clustered targets. Observational programs of many targets not encompassed within a telescope's field of view, however, require multiple pointings. Here, a greedy set cover algorithmic approach to efficient field selection in such a scenario is examined. The goal of this approach is not to minimize the total number of pointings needed to cover a given target set, but rather maximize the observational return for a restricted number of pointings. Telescope field of view and maximum targets per field are input parameters, allowing algorithm application to observation planning for the current range of active multi-object spectrographs (e.g. the 2dF/AAOmega, Fiber Large Array Multi Element Spectrograph, Fiber Multi-Object Spectrograph, Hectochelle, Hectospec and Hydra systems), and for any future systems. A parallel version of the algorithm is implemented with the message passing interface, facilitating execution on both shared and distributed memory systems.

  2. An optical design of the wide-field imaging and multi-object spectrograph for an Antarctic infrared telescope

    Science.gov (United States)

    Ichikawa, Takashi; Obata, Tomokazu

    2016-08-01

    A design of the wide-field infrared camera (AIRC) for Antarctic 2.5m infrared telescope (AIRT) is presented. The off-axis design provides a 7'.5 ×7'. 5 field of view with 0".22 pixel-1 in the wavelength range of 1 to 5 μm for the simultaneous three-color bands using cooled optics and three 2048×2048 InSb focal plane arrays. Good image quality is obtained over the entire field of view with practically no chromatic aberration. The image size corresponds to the refraction limited for 2.5 m telescope at 2 μm and longer. To enjoy the stable atmosphere with extremely low perceptible water vapor (PWV), superb seeing quality, and the cadence of the polar winter at Dome Fuji on the Antarctic plateau, the camera will be dedicated to the transit observations of exoplanets. The function of a multi-object spectroscopic mode with low spectra resolution (R 50-100) will be added for the spectroscopic transit observation at 1-5 μm. The spectroscopic capability in the environment of extremely low PWV of Antarctica will be very effective for the study of the existence of water vapor in the atmosphere of super earths.

  3. The Apache Point Observatory Galactic Evolution Experiment (APOGEE) high-resolution near-infrared multi-object fiber spectrograph

    Science.gov (United States)

    Wilson, John C.; Hearty, Fred; Skrutskie, Michael F.; Majewski, Steven; Schiavon, Ricardo; Eisenstein, Daniel; Gunn, Jim; Blank, Basil; Henderson, Chuck; Smee, Stephen; Barkhouser, Robert; Harding, Al; Fitzgerald, Greg; Stolberg, Todd; Arns, Jim; Nelson, Matt; Brunner, Sophia; Burton, Adam; Walker, Eric; Lam, Charles; Maseman, Paul; Barr, Jim; Leger, French; Carey, Larry; MacDonald, Nick; Horne, Todd; Young, Erick; Rieke, George; Rieke, Marcia; O'Brien, Tom; Hope, Steve; Krakula, John; Crane, Jeff; Zhao, Bo; Carr, Mike; Harrison, Craig; Stoll, Robert; Vernieri, Mary A.; Holtzman, Jon; Shetrone, Matt; Allende-Prieto, Carlos; Johnson, Jennifer; Frinchaboy, Peter; Zasowski, Gail; Bizyaev, Dmitry; Gillespie, Bruce; Weinberg, David

    2010-07-01

    The Apache Point Observatory Galactic Evolution Experiment (APOGEE) will use a dedicated 300-fiber, narrow-band (1.5-1.7 micron), high resolution (R~30,000), near-infrared spectrograph to survey approximately 100,000 giant stars across the Milky Way. This survey, conducted as part of the Sloan Digital Sky Survey III (SDSS III), will revolutionize our understanding of kinematical and chemical enrichment histories of all Galactic stellar populations. The instrument, currently in fabrication, will be housed in a separate building adjacent to the 2.5 m SDSS telescope and fed light via approximately 45-meter fiber runs from the telescope. The instrument design includes numerous technological challenges and innovations including a gang connector that allows simultaneous connection of all fibers with a single plug to a telescope cartridge that positions the fibers on the sky, numerous places in the fiber train in which focal ratio degradation must be minimized, a large (290 mm x 475 mm elliptically-shaped recorded area) mosaic-VPH, an f/1.4 sixelement refractive camera featuring silicon and fused silica elements with diameters as large as 393 mm, three near-within a custom, LN2-cooled, stainless steel vacuum cryostat with dimensions 1.4 m x 2.3 m x 1.3 m.

  4. MEGARA: the future optical IFU and multi-object spectrograph for the 10.4m GTC telescope

    Science.gov (United States)

    Gil de Paz, A.; Carrasco, E.; Gallego, J.; Sánchez, F. M.; Vílchez Medina, J. M.; García-Vargas, M. L.; Arrillaga, X.; Carrera, M. A.; Castillo-Morales, A.; Castillo-Domínguez, E.; Cedazo, R.; Eliche-Moral, C.; Ferrusca, D.; González-Guardia, E.; Maldonado, M.; Marino, R. A.; Martínez-Delgado, I.; Morales Durán, I.; Mújica, E.; Pascual, S.; Pérez-Calpena, A.; Sánchez-Penim, A.; Sánchez-Blanco, E.; Serena, F.; Tulloch, S.; Villar, V.; Zamorano, J.; Barrado y Naváscues, D.; Bertone, E.; Cardiel, N.; Cava, A.; Cenarro, J.; Chávez, M.; García, M.; Guichard, J.; Gúzman, R.; Herrero, A.; Huélamo, N.; Hughes, D.; Iglesias, J.; Jiménez-Vicente, J.; Aguerri, A. L.; Mayya, D.; Méndez-Abreu, J. M.; Mollá, M.; Muñoz-Tuñón, C.; Peimbert, S.; Peimbert, M.; Pérez-González, P. G.; Pérez Montero, E.; Rodríguez, M.; Rodríguez-Espinosa, J. M.; Rodríguez-Merino, L.; Rosa, D.; Sánchez-Almeida, J.; Sánchez Contreras, C.; Sánchez-Blázquez, Patricia; Sánchez, S.; Sarajedini, A.; Silich, S.; Simón, S.; Tenorio-Tagle, G.; Terlevich, E.; Terlevich, R.; Trujillo, I.; Tsamis, Y.; Vega, O.

    2012-09-01

    In these proceedings we give a summary of the characteristics and current status of the MEGARA instrument, the future optical IFU and MOS for the 10.4-m Gran Telescopio Canarias (GTC). MEGARA is being built by a Consortium of public research institutions led by the Universidad Complutense de Madrid (UCM, Spain) that also includes INAOE (Mexico), IAA-CSIC (Spain) and UPM (Spain). The MEGARA IFU includes two different fiber bundles, one called LCB (Large Compact Bundle) with a field-of-view of 12.5×11.3 arcsec2 and a spaxel size of 0.62 arcsec yielding spectral resolutions between R=6,800-17,000 and another one called SCB (Small Compact Bundle) covering 8.5×6.7 arcsec2 with hexagonally-shaped and packed 0.42-arcsec spaxels and resolutions R=8,000-20,000. The MOS component allows observing up to 100 targets in 3.5×3.5 arcmin2. Both the IFU bundles and the set of 100 robotic positioners of the MOS will be placed at one of the GTC Folded-Cass foci while the spectrographs (one in the case of the MEGARA-Basic concept) will be placed at the Nasmyth platform. On March 2012 MEGARA passed the Preliminary Design Review and its first light is expected to take place at the end of 2015.

  5. Performance of the Apache Point Observatory Galactic Evolution Experiment (APOGEE) high-resolution near-infrared multi-object fiber spectrograph

    Science.gov (United States)

    Wilson, John C.; Hearty, F.; Skrutskie, M. F.; Majewski, S. R.; Schiavon, R.; Eisenstein, D.; Gunn, J.; Holtzman, J.; Nidever, D.; Gillespie, B.; Weinberg, D.; Blank, B.; Henderson, C.; Smee, S.; Barkhouser, R.; Harding, A.; Hope, S.; Fitzgerald, G.; Stolberg, T.; Arns, J.; Nelson, M.; Brunner, S.; Burton, A.; Walker, E.; Lam, C.; Maseman, P.; Barr, J.; Leger, F.; Carey, L.; MacDonald, N.; Ebelke, G.; Beland, S.; Horne, T.; Young, E.; Rieke, G.; Rieke, M.; O'Brien, T.; Crane, J.; Carr, M.; Harrison, C.; Stoll, R.; Vernieri, M.; Shetrone, M.; Allende-Prieto, C.; Johnson, J.; Frinchaboy, P.; Zasowski, G.; Garcia Perez, A.; Bizyaev, D.; Cunha, K.; Smith, V. V.; Meszaros, Sz.; Zhao, B.; Hayden, M.; Chojnowski, S. D.; Andrews, B.; Loomis, C.; Owen, R.; Klaene, M.; Brinkmann, J.; Stauffer, F.; Long, D.; Jordan, W.; Holder, D.; Cope, F.; Naugle, T.; Pfaffenberger, B.; Schlegel, D.; Blanton, M.; Muna, D.; Weaver, B.; Snedden, S.; Pan, K.; Brewington, H.; Malanushenko, E.; Malanushenko, V.; Simmons, A.; Oravetz, D.; Mahadevan, S.; Halverson, S.

    2012-09-01

    The Apache Point Observatory Galactic Evolution Experiment (APOGEE) uses a dedicated 300-fiber, narrow-band near-infrared (1.51-1.7 μm), high resolution (R~22,500) spectrograph to survey approximately 100,000 giant stars across the Milky Way. This three-year survey, in operation since late-summer 2011 as part of the Sloan Digital Sky Survey III (SDSS III), will revolutionize our understanding of the kinematical and chemical enrichment histories of all Galactic stellar populations. We present the performance of the instrument from its first year in operation. The instrument is housed in a separate building adjacent to the 2.5-m SDSS telescope and fed light via approximately 45-meter fiber runs from the telescope. The instrument design includes numerous innovations including a gang connector that allows simultaneous connection of all fibers with a single plug to a telescope cartridge that positions the fibers on the sky, numerous places in the fiber train in which focal ratio degradation had to be minimized, a large mosaic-VPH (290 mm x 475 mm elliptically-shaped recorded area), an f/1.4 six-element refractive camera featuring silicon and fused silica elements with diameters as large as 393 mm, three near-infrared detectors mounted in a 1 x 3 mosaic with sub-pixel translation capability, and all of these components housed within a custom, LN2-cooled, stainless steel vacuum cryostat with dimensions 1.4-m x 2.3-m x 1.3-m.

  6. Progress on multi-object exoplanet search spectral interferometer

    Science.gov (United States)

    Zhang, Kai; Zhu, Yongtian; Wang, Lei; Yue, Zhongyu; Chen, Yi; Tang, Jin; Hu, Zhongwen

    2012-09-01

    It's a very important point that fully open up power of Gou Shoujing telescope (LAMOST) in exoplanet detection field by developing a multi-exoplanet survey system. But it's an indisputable truth in the present astronomy that a traditional type of multi-object high resolution spectrograph is almost impossible to be developed. External Dispersed Interferometry is an effective way to improve the radial velocity measuring accuracy of medium resolution spectrograph. With the using of this technique, Multi-object Exoplanet Search Spectral Interferometer (MESSI) is an exploratory system with medium measuring accuracy based on LAMOST low resolution spectrograph works in medium-resolution mode (R=5,000 - 10,000). And it's believed that will bring some feasible way in the future development of multi-object medium/high resolution spectrograph. After prototype experiment in 2010, a complete configuration is under the development, including a multi-object fixed-delay Michelson interferometer, an iodine cell with multi-fiber optical coupling system and a multi-terminal switching system in an efficient fiber physical coupling way. By some effective improvement, the interferometer has smaller cross section and more stable interference component. Moreover, based on physical and optical fiber coupling technique, it's possible for the iodine cell and the switching system to simultaneously and identically coupling 25 pairs of fibers. In paper, all of the progress is given in detail.

  7. EMIR, the GTC nir multi-object imager-spectrograph

    Directory of Open Access Journals (Sweden)

    F. Garzón

    2007-01-01

    Full Text Available EMIR, que esta actualmente cubriendo sus fases de fabricación y AIV, será uno de los primeros instrumentos de uso común en GTC el telescopio de 10m en construcción por GRANTECAN en el Observatorio del Roque de los Muchachos (Canarias, España. EMIR se construye por un consorcio de instituciones españolas y francesas, dirigido por el Instituto de Astrofísica de Canarias (IAC y está concebido para cubrir uno de los objetivos centrales de los telescopios de la clase de 10-m, el cual es obtener un gran número de espectros de fuentes débiles simultáneamente. EMIR está diseñado para operar principalmente como MOS en la banda K, aunque ofrece un amplio rango de modos de observación que incluyen imagen y espectroscopia, tanto de rendija larga como multiobjeto, en el rango espectral de 0.9 a 2.5 um. Está equipado con dos sistema novedosos en astronomía, que constituyen el corazón del instrumento: un robot reconfigurable de multimáscaras, de un lado, y elementos dispersivos formados por combinación de redes de difracción de alta calidad y prismas convencionales. Presentamos el estado actual de desarrollo, las prestaciones previstas y los planes iniciales para su explotación científica. Los desarrollos y fabricación de EMIR están financiados por GRANTECAN y el Plan Nacional de Astronomía y Astrofísica.

  8. EMIR, the GTC nir multi-object imager-spectrograph

    OpenAIRE

    Garzón, F.; D. Abreu; Barrera, S.; Correa, S.; J. J. Díaz; A. B. Fragoso; J. F. Fuentes; Gago, F.; C. González; López, P.; A. Manescau; J. Patrón; Pérez, J.; Redondo, P. (Pedro); Restrepo, R.

    2007-01-01

    EMIR, que esta actualmente cubriendo sus fases de fabricación y AIV, será uno de los primeros instrumentos de uso común en GTC el telescopio de 10m en construcción por GRANTECAN en el Observatorio del Roque de los Muchachos (Canarias, España). EMIR se construye por un consorcio de instituciones españolas y francesas, dirigido por el Instituto de Astrofísica de Canarias (IAC) y está concebido para cubrir uno de los objetivos centrales de los telescopios de la clase de 10-m, el cual...

  9. Multi-objective energy analysis

    Energy Technology Data Exchange (ETDEWEB)

    Cherniavsky, E.A.

    1979-11-01

    Analytic models have been applied to energy-planning problems in an effort to assess the probable impacts of alternative courses of action on vital social concerns such as the quality of the environment, the state of the economy, or extent of dependence on insecure foreign energy sources. A proposed program may have a variety of effects on social objectives; beneficial results in one area may be purchased at the cost of undesirable consequences in another. A policy must be judged by its impacts on a number of social concerns. The purpose of multi-objective analysis is to identify and quantify the tradeoffs between different social objectives, and to aid policymakers in formulating decisions that achieve the best possible compromise between conflicting goals. This paper reviews approaches and techniques currently employed in multi-objective analysis. Associated problems are explored and discussed in the light of experience with applications to energy-planning models. Conclusions are drawn concerning the most-fruitful directions for future research in this area. 40 references.

  10. New results from the multi-object Keck Exoplanet Tracker

    Directory of Open Access Journals (Sweden)

    J. C. van Eyken

    2007-01-01

    Full Text Available The W. M. Keck Exoplanet Tracker is a pre- cision Doppler radial velocity instrument for extrasolar planet detection based on a new technique, dispersed fixed-delay interferome- try (DFDI, which allows for multi-object sur- veying for the first time. Installed at the 2.5- m Sloan telescope at Apache Point Observa- tory, the combination of Michelson interfer- ometer and medium resolution spectrograph (Erskine & Ge 2000; Ge 2002 allows design for simultaneous Doppler measurements of 60 targets (Ge et al. 2005.

  11. 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...

  12. The Science Case for Multi-Object Spectroscopy on the European ELT

    NARCIS (Netherlands)

    Evans, Chris; Puech, Mathieu; Afonso, Jose; Almaini, Omar; Amram, Philippe; Aussel, Hervé; Barbuy, Beatriz; Basden, Alistair; Bastian, Nate; Battaglia, Giuseppina; Biller, Beth; Bonifacio, Piercarlo; Bouché, Nicholas; Bunker, Andy; Caffau, Elisabetta; Charlot, Stephane; Cirasuolo, Michele; Clenet, Yann; Combes, Francoise; Conselice, Chris; Contini, Thierry; Cuby, Jean-Gabriel; Dalton, Gavin; Davies, Ben; de Koter, Alex; Disseau, Karen; Dunlop, Jim; Epinat, Benoît; Fiore, Fabrizio; Feltzing, Sofia; Ferguson, Annette; Flores, Hector; Fontana, Adriano; Fusco, Thierry; Gadotti, Dimitri; Gallazzi, Anna; Gallego, Jesus; Giallongo, Emanuele; Gonçalves, Thiago; Gratadour, Damien; Guenther, Eike; Hammer, Francois; Hill, Vanessa; Huertas-Company, Marc; Ibata, Roridgo; Kaper, Lex; Korn, Andreas; Larsen, Søren; Le Fèvre, Olivier; Lemasle, Bertrand; Maraston, Claudia; Mei, Simona; Mellier, Yannick; Morris, Simon; Östlin, Göran; Paumard, Thibaut; Pello, Roser; Pentericci, Laura; Peroux, Celine; Petitjean, Patrick; Rodrigues, Myriam; Rodríguez-Muñoz, Lucía; Rouan, Daniel; Sana, Hugues; Schaerer, Daniel; Telles, Eduardo; Trager, Scott; Tresse, Laurence; Welikala, Niraj; Zibetti, Stefano; Ziegler, Bodo

    2015-01-01

    This White Paper presents the scientific motivations for a multi-object spectrograph (MOS) on the European Extremely Large Telescope (E-ELT). The MOS case draws on all fields of contemporary astronomy, from extra-solar planets, to the study of the halo of the Milky Way and its satellites, and from r

  13. 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...

  14. Dynamic multi-objective optimisation using PSO

    CSIR Research Space (South Africa)

    Greeff, M

    2010-01-01

    Full Text Available Functions. In Proc. of 2nd Italian Workshop on Evolutionary Computation and 3rd Italian Workshop on Artificial Life, 2006. 13. I. Hatzakis and D. Wallace. Dynamic Multi-Objective Optimization with Evolu- tionary Algorithms: A Forward Looking Approach...

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

    Science.gov (United States)

    Trager, S. C.

    2016-10-01

    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 driving the field of large-scale multi-object spectroscopic surveys; (2) statistics is important to drive conclusions, but inference is as or even more important; (3) multi-wavelength surveys are necessary, particularly for understanding galaxies and cosmology; and (4) a large number of new multi-object spectrographs at a wide variety of wavelengths are either already here or will rapidly be available. This conference shows that we are just learning how to get the most (astrophysics) out of these instruments.

  16. Overview of multi-objective optimization methods

    Institute of Scientific and Technical Information of China (English)

    雷秀娟; 史忠科

    2004-01-01

    To assist readers to have a comprehensive understanding, the classical and intelligent methods roundly based on precursory research achievements are summarized in this paper. First, basic conception and description about multi-objective (MO) optimization are introduced. Then some definitions and related terminologies are given. Furthermore several MO optimization methods including classical and current intelligent methods are discussed one by one succinctly. Finally evaluations on advantages and disadvantages about these methods are made at the end of the paper.

  17. Sommerskole 2004 - Hydra

    DEFF Research Database (Denmark)

    2004-01-01

    Montagen af/som nye erfaringsrum: intensiteter gennem disjunktioner. Arbejdsprocessen var struktureret gennem en række fortløbende spørgsmål, der blev formuleret successivt i perioden. Hydra kan ses som en kompleks topologisk konfiguration: hvis man betragter dens morfologi som en plastisk membra...... - en latex hvorigennem de topologiske kræfter tegner konturer - vil særlige strukturer danne ar i væv. Hydra kan ses som 2 komplekse topologiske og morfologiske plastiske membraner, der overførte eller snarere relaterede sine "mulige ny ar, rifter, knuder og forvridninger" i en symbiose...

  18. 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.

  19. Novel multi-objective optimization algorithm

    Institute of Scientific and Technical Information of China (English)

    Jie Zeng; Wei Nie

    2014-01-01

    Many multi-objective evolutionary algorithms (MOEAs) can converge to the Pareto optimal front and work wel on two or three objectives, but they deteriorate when faced with many-objective problems. Indicator-based MOEAs, which adopt various indicators to evaluate the fitness values (instead of the Pareto-dominance relation to select candidate solutions), have been regarded as promising schemes that yield more satisfactory re-sults than wel-known algorithms, such as non-dominated sort-ing genetic algorithm (NSGA-II) and strength Pareto evolution-ary algorithm (SPEA2). However, they can suffer from having a slow convergence speed. This paper proposes a new indicator-based multi-objective optimization algorithm, namely, the multi-objective shuffled frog leaping algorithm based on the ε indicator (ε-MOSFLA). This algorithm adopts a memetic meta-heuristic, namely, the SFLA, which is characterized by the powerful capa-bility of global search and quick convergence as an evolutionary strategy and a simple and effective ε-indicator as a fitness as-signment scheme to conduct the search procedure. Experimental results, in comparison with other representative indicator-based MOEAs and traditional Pareto-based MOEAs on several standard test problems with up to 50 objectives, show thatε-MOSFLA is the best algorithm for solving many-objective optimization problems in terms of the solution quality as wel as the speed of convergence.

  20. Fibre positioning algorithms for the WEAVE spectrograph

    NARCIS (Netherlands)

    Terrett, David L.; Lewis, Ian J.; Dalton, Gavin; Abrams, Don Carlos; Aguerri, J. Alfonso L.; Bonifacio, Piercarlo; Middleton, Kevin; Trager, Scott C.

    2014-01-01

    WEAVE is the next-generation wide-field optical spectroscopy facility for the William Herschel Telescope (WHT) in La Palma, Canary Islands, Spain. It is a multi-object "pick and place" fibre fed spectrograph with more than one thousand fibres, similar in concept to the Australian Astronomical Observ

  1. HST/STIS results on circumstellar disks and jets, future coronography and technology for IR multi-object spectroscopy

    Science.gov (United States)

    Woodgate, Bruce E.

    2002-01-01

    Results of studies of circumstellar disks and jets obtained by HST/STIS visible coronagraphy and UV spectroscopy, and by ground-based Fabry-Perot coronagraphy will be presented. Future improvements in coronagraphy will be discussed. The development of microshutter arrays as programmable multi-object selectors for the NGST near IR spectrograph will be described.

  2. 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...... simultaneously, aiming at integrating the market operation and planning as one unified process in the market environment. Subsequently, reliability assessment is performed to evaluate and reinforce the resultant expansion plan from MOOP. The proposed method has been tested with the IEEE 14-bus system...

  3. Multi-Object Spectroscopy with MUSE

    Science.gov (United States)

    Kelz, A.; Kamann, S.; Urrutia, T.; Weilbacher, P.; Bacon, R.

    2016-10-01

    Since 2014, MUSE, the Multi-Unit Spectroscopic Explorer, is in operation at the ESO-VLT. It combines a superb spatial sampling with a large wavelength coverage. By design, MUSE is an integral-field instrument, but its field-of-view and large multiplex make it a powerful tool for multi-object spectroscopy too. Every data-cube consists of 90,000 image-sliced spectra and 3700 monochromatic images. In autumn 2014, the observing programs with MUSE have commenced, with targets ranging from distant galaxies in the Hubble Deep Field to local stellar populations, star formation regions and globular clusters. This paper provides a brief summary of the key features of the MUSE instrument and its complex data reduction software. Some selected examples are given, how multi-object spectroscopy for hundreds of continuum and emission-line objects can be obtained in wide, deep and crowded fields with MUSE, without the classical need for any target pre-selection.

  4. Multi-Object Spectroscopy with MUSE

    CERN Document Server

    Kelz, Andreas; Urrutia, Tanya; Weilbacher, Peter; Bacon, Roland

    2015-01-01

    Since 2014, MUSE, the Multi-Unit Spectroscopic Explorer, is in operation at the ESO-VLT. It combines a superb spatial sampling with a large wavelength coverage. By design, MUSE is an integral-field instrument, but its field-of-view and large multiplex make it a powerful tool for multi-object spectroscopy too. Every data-cube consists of 90,000 image-sliced spectra and 3700 monochromatic images. In autumn 2014, the observing programs with MUSE have commenced, with targets ranging from distant galaxies in the Hubble Deep Field to local stellar populations, star formation regions and globular clusters. This paper provides a brief summary of the key features of the MUSE instrument and its complex data reduction software. Some selected examples are given, how multi-object spectroscopy for hundreds of continuum and emission-line objects can be obtained in wide, deep and crowded fields with MUSE, without the classical need for any target pre-selection.

  5. WIYN Open Cluster Study. XXXIX. Abundances in NGC 6253 from HYDRA Spectroscopy of the Li 6708 A Region

    CERN Document Server

    Anthony-Twarog, B J; Twarog, B A; Cummings, J D; Maderak, R M

    2010-01-01

    High-dispersion spectra of 89 potential members of the old, super-metal-rich open cluster, NGC 6253, have been obtained with the HYDRA multi-object spectrograph. Based upon radial-velocity measurements alone, 47 stars at the turnoff of the cluster color-magnitude diagram (CMD) and 18 giants are identified as potential members. Five turnoff stars exhibit evidence of binarity while proper-motion data eliminates two of the dwarfs as members. The mean cluster radial velocity from probable single-star members is -29.4 +/- 1.3 km/sec (sd). A discussion of the current estimates for the cluster reddening, derived independently of potential issues with the BV cluster photometry, lead to an adopted reddening of E(B-V) = 0.22 +/- 0.04. From equivalent width analyses of 38 probable single-star members near the CMD turnoff, the weighted average abundances are found to be [Fe/H] = +0.43 +/- 0.01, [Ni/H] = +0.53 +/- 0.02 and [Si/H] = +0.43 (+0.03,-0.04), where the errors refer to the standard errors of the weighted mean. We...

  6. Multi-objective optimization of inverse planning for accurate radiotherapy

    Institute of Scientific and Technical Information of China (English)

    曹瑞芬; 吴宜灿; 裴曦; 景佳; 李国丽; 程梦云; 李贵; 胡丽琴

    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 pl

  7. Multi objective SNP selection using pareto optimality.

    Science.gov (United States)

    Gumus, Ergun; Gormez, Zeliha; Kursun, Olcay

    2013-04-01

    Biomarker discovery is a challenging task of bioinformatics especially when targeting high dimensional problems such as SNP (single nucleotide polymorphism) datasets. Various types of feature selection methods can be applied to accomplish this task. Typically, using features versus class labels of samples in the training dataset, these methods aim at selecting feature subsets with maximal classification accuracies. Although finding such class-discriminative features is crucial, selection of relevant SNPs for maximizing other properties that exist in the nature of population genetics such as the correlation between genetic diversity and geographical distance of ethnic groups can also be equally important. In this work, a methodology using a multi objective optimization technique called Pareto Optimal is utilized for selecting SNP subsets offering both high classification accuracy and correlation between genomic and geographical distances. In this method, discriminatory power of an SNP is determined using mutual information and its contribution to the genomic-geographical correlation is estimated using its loadings on principal components. Combining these objectives, the proposed method identifies SNP subsets that can better discriminate ethnic groups than those obtained with sole mutual information and yield higher correlation than those obtained with sole principal components on the Human Genome Diversity Project (HGDP) SNP dataset.

  8. Multi-objective optimization of steel nitriding

    Directory of Open Access Journals (Sweden)

    P. Cavaliere

    2016-03-01

    Full Text Available Steel nitriding is a thermo-chemical process largely employed in the machine components production to solve mainly wear and fatigue damage in materials. The process is strongly influenced by many different variables such as steel composition, nitrogen potential (range 0.8–35, temperature (range 350–1200 °C, time (range 2–180 hours. In the present study, the influence of such parameters affecting the nitriding layers' thickness, hardness, composition and residual stress was evaluated. The aim was to streamline the process by numerical–experimental analysis allowing to define the optimal conditions for the success of the process. The optimization software that was used is modeFRONTIER (Esteco, through which was defined a set of input parameters (steel composition, nitrogen potential, nitriding time, etc. evaluated on the basis of an optimization algorithm carefully chosen for the multi-objective analysis. The mechanical and microstructural results belonging to the nitriding process, performed with different processing conditions for various steels, are presented. The data were employed to obtain the analytical equations describing nitriding behavior as a function of nitriding parameters and steel composition. The obtained model was validated through control designs and optimized by taking into account physical and processing conditions.

  9. Long-term stability of fibre-optic transmission for multi-object spectroscopy

    CERN Document Server

    Sharp, R; Cannon, R D

    2012-01-01

    We present an analysis of the long-term stability of fibre-optic transmission properties for fibre optics in astronomy. Data from six years of operation of the AAOmega multi-object spectrograph at the Anglo-Australian Telescope is presented. We find no evidence for significant degradation in the bulk transmission properties of the 38 m optical fibre train. Significant losses (<20% relative, 4% absolute) are identified and associated with the end termination of the optical fibres in the focal plane. Improved monitoring and maintenance can rectify the majority of this performance degradation.

  10. The dynamic genome of Hydra

    Science.gov (United States)

    Chapman, Jarrod A.; Kirkness, Ewen F.; Simakov, Oleg; Hampson, Steven E.; Mitros, Therese; Weinmaier, Therese; Rattei, Thomas; Balasubramanian, Prakash G.; Borman, Jon; Busam, Dana; Disbennett, Kathryn; Pfannkoch, Cynthia; Sumin, Nadezhda; Sutton, Granger G.; Viswanathan, Lakshmi Devi; Walenz, Brian; Goodstein, David M.; Hellsten, Uffe; Kawashima, Takeshi; Prochnik, Simon E.; Putnam, Nicholas H.; Shu, Shengquiang; Blumberg, Bruce; Dana, Catherine E.; Gee, Lydia; Kibler, Dennis F.; Law, Lee; Lindgens, Dirk; Martinez, Daniel E.; Peng, Jisong; Wigge, Philip A.; Bertulat, Bianca; Guder, Corina; Nakamura, Yukio; Ozbek, Suat; Watanabe, Hiroshi; Khalturin, Konstantin; Hemmrich, Georg; Franke, André; Augustin, René; Fraune, Sebastian; Hayakawa, Eisuke; Hayakawa, Shiho; Hirose, Mamiko; Hwang, Jung Shan; Ikeo, Kazuho; Nishimiya-Fujisawa, Chiemi; Ogura, Atshushi; Takahashi, Toshio; Steinmetz, Patrick R. H.; Zhang, Xiaoming; Aufschnaiter, Roland; Eder, Marie-Kristin; Gorny, Anne-Kathrin; Salvenmoser, Willi; Heimberg, Alysha M.; Wheeler, Benjamin M.; Peterson, Kevin J.; Böttger, Angelika; Tischler, Patrick; Wolf, Alexander; Gojobori, Takashi; Remington, Karin A.; Strausberg, Robert L.; Venter, J. Craig; Technau, Ulrich; Hobmayer, Bert; Bosch, Thomas C. G.; Holstein, Thomas W.; Fujisawa, Toshitaka; Bode, Hans R.; David, Charles N.; Rokhsar, Daniel S.; Steele, Robert E.

    2015-01-01

    The freshwater cnidarian Hydra was first described in 17021 and has been the object of study for 300 years. Experimental studies of Hydra between 1736 and 1744 culminated in the discovery of asexual reproduction of an animal by budding, the first description of regeneration in an animal, and successful transplantation of tissue between animals2. Today, Hydra is an important model for studies of axial patterning3, stem cell biology4 and regeneration5. Here we report the genome of Hydra magnipapillata and compare it to the genomes of the anthozoan Nematostella vectensis6 and other animals. The Hydra genome has been shaped by bursts of transposable element expansion, horizontal gene transfer, trans-splicing, and simplification of gene structure and gene content that parallel simplification of the Hydra life cycle. We also report the sequence of the genome of a novel bacterium stably associated with H. magnipapillata. Comparisons of the Hydra genome to the genomes of other animals shed light on the evolution of epithelia, contractile tissues, developmentally regulated transcription factors, the Spemann–Mangold organizer, pluripotency genes and the neuromuscular junction. PMID:20228792

  11. SAMOS: a versatile multi-object-spectrograph for the GLAO system SAM at SOAR

    Science.gov (United States)

    Robberto, Massimo; Donahue, Megan; Ninkov, Zoran; Smee, Stephen A.; Barkhouser, Robert H.; Gennaro, Mario; Tokovinin, Andrei

    2016-08-01

    The 4.1-m SOAR telescope can play a unique role for LSST follow-up studies through an efficient use of its laser-guided Adaptive Optics Module (SAM) that routinely delivers images with FWHM extreme precision. SAMOS can capture R 2,000 - 2, 500 spectra with a nominal 0:33" slit width in the 3,500-9,500 Å spectral range reaching in 3600 s median SNR=5 at AB=22.9 with the red grating and 23.5 with the blue grating, comparable to 8-m class telescopes working in seeing limited conditions. In this contribution we present the SAMOS opto-mechanical design, concept of operation and provide a few examples of compelling science programs that can uniquely benefit from SAMOS sensitivity, angular resolution, versatility and simplicity of use.

  12. Collision-free coordination of fiber positioners in multi-object spectrographs

    Science.gov (United States)

    Makarem, Laleh; Kneib, Jean-Paul; Gillet, Denis

    2016-07-01

    Many fiber-fed spectroscopic survey projects, such as DESI, PFS and MOONS, will use thousands of fiber positioners packed at a focal plane. To maximize observation time, the positioners need to move simultaneously and reach their targets swiftly. We have previously presented a motion planning method based on a decentralized navigation function for the collision-free coordination of the fiber positioners in DESI. In MOONS, the end effector of each positioner handling the fiber can reach the centre of its neighbours. There is therefore a risk of collision with up to 18 surrounding positioners in the chosen dense hexagonal configuration. Moreover, the length of the second arm of the positioner is almost twice the length of the first one. As a result, the geometry of the potential collision zone between two positioners is not limited to the extremity of their end-effector, but surrounds the second arm. In this paper, we modify the navigation function to take into account the larger collision zone resulting from the extended geometrical shape of the positioners. The proposed navigation function takes into account the configuration of the positioners as well as the constraints on the actuators, such as their maximal velocity and their mechanical clearance. Considering the fact that all the positioners' bases are fixed to the focal plane, collisions can occur locally and the risk of collision is limited to the 18 surrounding positioners. The decentralizing motion planning and trajectory generation takes advantage of this limited number of positioners and the locality of collisions, hence significantly reduces the complexity of the algorithm to a linear order. The linear complexity ensures short computation time. In addition, the time needed to move all the positioners to their targets is independent of the number of positioners. These two key advantages of the chosen decentralization approach turn this method to a promising solution for the collision-free motion-planning problem in the next- generation spectroscopic survey projects. A motion planning simulator, exploited as a software prototype, has been developed in Python. The pre-computed collision-free trajectories of the actuators of all the positioners are fed directly from the simulator to the electronics controlling the motors. A successful demonstration of the effectiveness of these trajectories on the real positioners as well as their simulated counterparts are put side by side in the following online video sequence (https://goo.gl/YuwwsE).

  13. MOSAIC at the E-ELT: A multi-object spectrograph for astrophysics, IGM and cosmology

    NARCIS (Netherlands)

    F. Hammer; B. Barbuy; J.G. Cuby; L. Kaper; S. Morris; C.J. Evans; P. Jagourel; G. Dalton; P. Rees; M. Puech; M. Rodriques; D. Pearson; K. Disseau

    2014-01-01

    The Universe is comprised of hundreds of billions of galaxies, each populated by hundreds of billions of stars. Astrophysics aims to understand the complexity of this almost incommensurable number of stars, stellar clusters and galaxies, including their spatial distribution, formation, and current i

  14. Gemini GMOS and WHT SAURON integral-field spectrograph observations of the AGN-driven outflow in NGC 1266

    NARCIS (Netherlands)

    Davis, Timothy A.; Krajnović, Davor; McDermid, Richard M.; Bureau, Martin; Sarzi, Marc; Nyland, Kristina; Alatalo, Katherine; Bayet, Estelle; Blitz, Leo; Bois, Maxime; Bournaud, Frédéric; Cappellari, Michele; Crocker, Alison; Davies, Roger L.; de Zeeuw, P. T.; Duc, Pierre-Alain; Emsellem, Eric; Khochfar, Sadegh; Kuntschner, Harald; Lablanche, Pierre-Yves; Morganti, Raffaella; Naab, Thorsten; Oosterloo, Tom; Scott, Nicholas; Serra, Paolo; Weijmans, Anne-Marie; Young, Lisa M.

    2012-01-01

    We use the Spectrographic Areal Unit for Research on Optical Nebulae and Gemini Multi-Object Spectrograph integral-field spectrographs to observe the active galactic nucleus (AGN) powered outflow in NGC 1266. This unusualgalaxy is relatively nearby (D = 30 Mpc), allowing us to investigate the proces

  15. Gemini GMOS and WHT SAURON integral-field spectrograph observations of the AGN-driven outflow in NGC 1266

    NARCIS (Netherlands)

    Davis, Timothy A.; Krajnovic, Davor; McDermid, Richard M.; Bureau, Martin; Sarzi, Marc; Nyland, Kristina; Alatalo, Katherine; Bayet, Estelle; Blitz, Leo; Bois, Maxime; Bournaud, Frederic; Cappellari, Michele; Crocker, Alison; Davies, Roger L.; de Zeeuw, P. T.; Duc, Pierre-Alain; Emsellem, Eric; Khochfar, Sadegh; Kuntschner, Harald; Lablanche, Pierre-Yves; Morganti, Raffaella; Naab, Thorsten; Oosterloo, Tom; Scott, Nicholas; Serra, Paolo; Weijmans, Anne-Marie; Young, Lisa M.

    2012-01-01

    We use the Spectrographic Areal Unit for Research on Optical Nebulae and Gemini Multi-Object Spectrograph integral-field spectrographs to observe the active galactic nucleus (AGN) powered outflow in NGC?1266. This unusual galaxy is relatively nearby (D = 30?Mpc), allowing us to investigate the proce

  16. Waste Minimization Through Process Integration and Multi-objective Optimization

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    By avoiding or reducing the production of waste, waste minimization is an effective approach to solve the pollution problem in chemical industry. Process integration supported by multi-objective optimization provides a framework for process design or process retrofit by simultaneously optimizing on the aspects of environment and economics. Multi-objective genetic algorithm is applied in this area as the solution approach for the multi-objective optimization problem.

  17. Conference Discussion: The Challenges in Multi-Object Spectroscopy Instrument and Survey Design, and in Data Processing and Analysis

    Science.gov (United States)

    Balcells, M.; Skillen, I.

    2016-10-01

    The final session of the conference Multi-Object Spectroscopy in the Next Decade: Big Questions, Large Surveys, and Wide Fields, held in La Palma 2-6 March 2015, was devoted to a discussion of the challenges in designing and operating the next-generation survey spectrographs, and planning and carrying out their massive surveys. The wide-ranging 1.5-hour debate was recorded on video tape, and in this paper we report the edited transcription of the dialog.

  18. 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 depen

  19. APPLICATION OF FUZZY MATHEMATICS IN MULTI-OBJECTIVE OPTIMAL DESIGN

    Institute of Scientific and Technical Information of China (English)

    1999-01-01

    In order to overcome the problem that theoretical research lags behind practical application in the multi-objective optimal design,a practical method is suggested.In this method the fuzzy nearness is used to seek an overall solution of the multi-objective optimal design and analyse the features of the curved surface.The method is tested using three practical examples.

  20. IFSRED: Data Reduction for Integral Field Spectrographs

    Science.gov (United States)

    Rupke, David S. N.

    2014-09-01

    IFSRED is a general-purpose library for reducing data from integral field spectrographs (IFSs). For a general IFS data cube, it contains IDL routines to: (1) find and apply a zero-point shift in a wavelength solution on a spaxel-by-spaxel basis, using sky lines; (2) find the spatial coordinates of a flux peak; (3) empirically correct for differential atmospheric refraction; (4) mosaic dithered exposures; (5) (integer) rebin; and (6) apply a telluric correction. A sky-subtraction routine for data from the Gemini Multi-Object Spectrograph and Imager (GMOS) that can be easily modified for any instrument is also included. IFSRED also contains additional software specific to reducing data from GMOS and the Gemini Near-Infrared Integral Field Spectrograph (NIFS).

  1. Fibre positioning concept for the WEAVE spectrograph at the WHT

    NARCIS (Netherlands)

    Lewis, Ian J.; Dalton, Gavin B.; Brock, Matthew; Gilbert, James; Abrams, Don C.; Aguerri, J. Alfonso L.; Bonifacio, Piercarlo; Middleton, Kevin; Trager, Scott C.

    2014-01-01

    WEAVE is the next-generation wide-field optical spectroscopy facility for the William Herschel Telescope (WHT) in La Palma, Canary Islands, Spain. It is a multi-object "pick and place" fibre fed spectrograph with more than one thousand fibres behind a new dedicated 2° prime focus corrector, This is

  2. 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

  3. Structural Multi-objective Probabilistic Design for Six Sigma

    Institute of Scientific and Technical Information of China (English)

    LI Yu-qiang; CUI Zhen-shan; CHEN Jun; ZHANG Dong-juan; RUAN Xue-yu

    2007-01-01

    Uncertainties in engineering design may lead to low reliable solutions that also exhibit high sensitivity to uncontrollable variations. In addition, there often exist several conflicting objectives and constraints in various design environments. In order to obtain solutions that are not only "multi-objectively" optimal, but also reliable and robust, a probabilistic optimization method was presented by integrating six sigma philosophy and multi-objective genetic algorithm. With this method, multi-objective genetic algorithm was adopted to obtain the global Pareto solutions, and six sigma method was used to improve the reliability and robustness of those optimal solutions. Two engineering design problems were provided as examples to illustrate the proposed method.

  4. Balanced Combinations of Solutions in Multi-Objective Optimization

    CERN Document Server

    Glaßer, Christian; Witek, Maximilian

    2010-01-01

    For every list of integers x_1, ..., x_m there is some j such that x_1 + ... + x_j - x_{j+1} - ... - x_m \\approx 0. So the list can be nearly balanced and for this we only need one alternation between addition and subtraction. But what if the x_i are k-dimensional integer vectors? Using results from topological degree theory we show that balancing is still possible, now with k alternations. This result is useful in multi-objective optimization, as it allows a polynomial-time computable balance of two alternatives with conflicting costs. The application to two multi-objective optimization problems yields the following results: - A randomized 1/2-approximation for multi-objective maximum asymmetric traveling salesman, which improves and simplifies the best known approximation for this problem. - A deterministic 1/2-approximation for multi-objective maximum weighted satisfiability.

  5. MULTI-OBJECTIVE PREDICTIVE CONTROL: A SOLUTION USING METAHEURISTICS

    Directory of Open Access Journals (Sweden)

    Halim Merabti

    2014-12-01

    Full Text Available The application of multi objective model predictive control approaches is significantly limited with computation time associated with optimization algorithms. Metaheuristics are general purpose heuristics that have been successfully used in solving difficult optimization problems in a reasonable computation time. In this work , we use and compare two multi objective metaheuristics, Multi-Objective Particle swarm Optimization, MOPSO, and Multi-Objective Gravitational Search Algorithm, MOGSA, to generate a set of approximately Pareto-optimal solutions in a single run. Two examples are studied, a nonlinear system consisting of two mobile robots tracking trajectories and avoiding obstacles and a linear multi variable system. The computation times and the quality of the solution in terms of the smoothness of the control signals and precision of tracking show that MOPSO can be an alternative for real time applications.

  6. Duality Theorems on Multi-objective Programming of Generalized Functions

    Institute of Scientific and Technical Information of China (English)

    Li-ping Pang; Wei Wang; Zun-quan Xia

    2006-01-01

    The form of a dual problem of Mond-Weir type for multi-objective programming problems of generalized functions is defined and theorems of the weak duality, direct duality and inverse duality are proven.

  7. Scalable and Practical Multi-Objective Distribution Network Expansion Planning

    NARCIS (Netherlands)

    Luong, N.H.; Grond, M.O.W.; La Poutré, 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

  8. Adaptive Multi-Objective Optimization Based on Feedback Design

    Institute of Scientific and Technical Information of China (English)

    窦立谦; 宗群; 吉月辉; 曾凡琳

    2010-01-01

    The problem of adaptive multi-objective optimization(AMOO) has received extensive attention due to its practical significance.An important issue in optimizing a multi-objective system is adjusting the weighting coefficients of multiple objectives so as to keep track of various conditions.In this paper,a feedback structure for AMOO is designed.Moreover,the reinforcement learning combined with hidden biasing information is applied to online tuning weighting coefficients of objective functions.Finally,the prop...

  9. A simulated annealing technique for multi-objective simulation optimization

    OpenAIRE

    Mahmoud H. Alrefaei; Diabat, Ali H.

    2009-01-01

    In this paper, we present a simulated annealing algorithm for solving multi-objective simulation optimization problems. The algorithm is based on the idea of simulated annealing with constant temperature, and uses a rule for accepting a candidate solution that depends on the individual estimated objective function values. The algorithm is shown to converge almost surely to an optimal solution. It is applied to a multi-objective inventory problem; the numerical results show that the algorithm ...

  10. Cobweb heuristic for multi-objective vehicle routing problem

    OpenAIRE

    Joseph Okitonyumbe Y. F; Berthold Ulungu E.-L; Joel Kapiamba Nt.

    2015-01-01

    Solving a classical vehicle routing problem (VRP) by exact methods presents many difficulties for large dimension problem. Consequently, in multi-objective framework, heuristic or metaheuristic methods are required. Due to particular VRP structure, it seems that a dedicated heuristicis more suitable than a metaheuristic. The aim of this article is to collapse different heuristics solving classical VRP and adapt them for to solve the multi-objective vehicle routing problem (MOVRP). The so-call...

  11. Cobweb Heuristic for solving Multi-Objective Vehicle Routing Problem

    OpenAIRE

    Okitonyumbe Y.F., Joseph; Ulungu, Berthold E.-L.; Kapiamba Nt., Joel

    2015-01-01

    Abstract Solving a classical vehicle routing problem (VRP) by exact methods presents many difficulties for large dimension problem. Consequently, in multi-objective framework, heuristic or metaheuristic methods are required. Due to particular VRP structure, it seems that a dedicated heuristic is more suitable than a metaheuristic. The aim of this article is to collapse different heuristics solving classical VRP and adapt them for to solve the multi-objective vehicle routing problem (MOVRP)...

  12. 4MOST: the high-resolution spectrograph

    Science.gov (United States)

    Seifert, W.; Xu, W.; Buschkamp, P.; Feiz, C.; Saviauk, A.; Barden, S.; Quirrenbach, A.; Mandel, H.

    2016-08-01

    4MOST (4-meter Multi-Object Spectroscopic Telescope) is a wide-field, fiber-feed, high-multiplex spectroscopic survey facility to be installed on the 4-meter ESO telescope VISTA in Chile. It consists of two identical low resolution spectrographs and one high resolution spectrograph. The instrument is presently in the preliminary design phase and expected to get operational end of 2022. The high resolution spectrograph will afford simultaneous observations of up to 812 targets - over a hexagonal field of view of 4.1 sq.degrees on sky - with a spectral resolution R>18,000 covering a wavelength range from 393 to 679nm in three channels. In this paper we present the optical and mechanical design of the high resolution spectrograph (HRS) as prepared for the review at ESO, Garching. The expected performance including the highly multiplexed fiber slit concept is simulated and its impact on the optical performance given. We show the thermal and finite element analyses and the resulting stability of the spectrograph under operational conditions.

  13. Solving Molecular Docking Problems with Multi-Objective Metaheuristics

    Directory of Open Access Journals (Sweden)

    María Jesús García-Godoy

    2015-06-01

    Full Text Available Molecular docking is a hard optimization problem that has been tackled in the past with metaheuristics, demonstrating new and challenging results when looking for one objective: the minimum binding energy. However, only a few papers can be found in the literature that deal with this problem by means of a multi-objective approach, and no experimental comparisons have been made in order to clarify which of them has the best overall performance. In this paper, we use and compare, for the first time, a set of representative multi-objective optimization algorithms applied to solve complex molecular docking problems. The approach followed is focused on optimizing the intermolecular and intramolecular energies as two main objectives to minimize. Specifically, these algorithms are: two variants of the non-dominated sorting genetic algorithm II (NSGA-II, speed modulation multi-objective particle swarm optimization (SMPSO, third evolution step of generalized differential evolution (GDE3, multi-objective evolutionary algorithm based on decomposition (MOEA/D and S-metric evolutionary multi-objective optimization (SMS-EMOA. We assess the performance of the algorithms by applying quality indicators intended to measure convergence and the diversity of the generated Pareto front approximations. We carry out a comparison with another reference mono-objective algorithm in the problem domain (Lamarckian genetic algorithm (LGA provided by the AutoDock tool. Furthermore, the ligand binding site and molecular interactions of computed solutions are analyzed, showing promising results for the multi-objective approaches. In addition, a case study of application for aeroplysinin-1 is performed, showing the effectiveness of our multi-objective approach in drug discovery.

  14. Solving molecular docking problems with multi-objective metaheuristics.

    Science.gov (United States)

    García-Godoy, María Jesús; López-Camacho, Esteban; García-Nieto, José; Aldana-Montes, Antonio J Nebroand José F

    2015-06-02

    Molecular docking is a hard optimization problem that has been tackled in the past with metaheuristics, demonstrating new and challenging results when looking for one objective: the minimum binding energy. However, only a few papers can be found in the literature that deal with this problem by means of a multi-objective approach, and no experimental comparisons have been made in order to clarify which of them has the best overall performance. In this paper, we use and compare, for the first time, a set of representative multi-objective optimization algorithms applied to solve complex molecular docking problems. The approach followed is focused on optimizing the intermolecular and intramolecular energies as two main objectives to minimize. Specifically, these algorithms are: two variants of the non-dominated sorting genetic algorithm II (NSGA-II), speed modulation multi-objective particle swarm optimization (SMPSO), third evolution step of generalized differential evolution (GDE3), multi-objective evolutionary algorithm based on decomposition (MOEA/D) and S-metric evolutionary multi-objective optimization (SMS-EMOA). We assess the performance of the algorithms by applying quality indicators intended to measure convergence and the diversity of the generated Pareto front approximations. We carry out a comparison with another reference mono-objective algorithm in the problem domain (Lamarckian genetic algorithm (LGA) provided by the AutoDock tool). Furthermore, the ligand binding site and molecular interactions of computed solutions are analyzed, showing promising results for the multi-objective approaches. In addition, a case study of application for aeroplysinin-1 is performed, showing the effectiveness of our multi-objective approach in drug discovery.

  15. JWST/NIRSpec Multi-Object Spectroscopy: Calibration and Data Products

    Science.gov (United States)

    Muzerolle, J.

    2016-10-01

    The James Webb Space Telescope will have a multi-object spectroscopic (MOS) capability as part of its Near-Infrared Spectrograph (NIRSpec). This mode will enable observations of up to ˜ 100 or more objects in a single exposure using a microshutter array containing a quarter-million independently operable shutters. The complexity of this data requires a robust and carefully constructed processing pipeline that can deliver well-calibrated and intelligently-organized data to the user. Here I describe the basic processing steps that will be part of the pipeline, including how we will account for problematic aspects including wavelength calibration and background subtraction. I also outline the expected format of the pipeline data products that will be delivered, and how the data can be handled interactively using data analysis and visualization tools that will also be provided.

  16. The Hydra drawings: digital imperfection

    DEFF Research Database (Denmark)

    Peder Pedersen, Claus

    2008-01-01

    Teksten diskuterer den digitale tegnings potenitaler med udgangspunkt i et kunstnerisk udviklingsarbejde gennemført på den græske ø Hydra. Den fokuserer på tegningens historiske betydning som medie for arkitektonisk formgivning og diskuterer muligheden for at gentænke forholdet mellem det åbent...

  17. Developer Tools for Evaluating Multi-Objective Algorithms

    Science.gov (United States)

    Giuliano, Mark E.; Johnston, Mark D.

    2011-01-01

    Multi-objective algorithms for scheduling offer many advantages over the more conventional single objective approach. By keeping user objectives separate instead of combined, more information is available to the end user to make trade-offs between competing objectives. Unlike single objective algorithms, which produce a single solution, multi-objective algorithms produce a set of solutions, called a Pareto surface, where no solution is strictly dominated by another solution for all objectives. From the end-user perspective a Pareto-surface provides a tool for reasoning about trade-offs between competing objectives. From the perspective of a software developer multi-objective algorithms provide an additional challenge. How can you tell if one multi-objective algorithm is better than another? This paper presents formal and visual tools for evaluating multi-objective algorithms and shows how the developer process of selecting an algorithm parallels the end-user process of selecting a solution for execution out of the Pareto-Surface.

  18. Modeling and Multi-objective Optimization of Refinery Hydrogen Network

    Institute of Scientific and Technical Information of China (English)

    焦云强; 苏宏业; 廖祖维; 侯卫锋

    2011-01-01

    The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming (MINLP). A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is intro-duced to illustrate the applicability of the approach.

  19. 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...

  20. A Multi-objective Model for Transmission Planning Under Uncertainties

    DEFF Research Database (Denmark)

    Zhang, Chunyu; Wang, Qi; Ding, Yi;

    2014-01-01

    The significant growth of distributed energy resources (DERs) associated with smart grid technologies has prompted excessive uncertainties in the transmission system. The most representative is the novel notation of commercial aggregator who has lighted a bright way for DERs to participate power...... trading and regulating in transmission level. In this paper, the aggregator caused uncertainty is analyzed first considering DERs’ correlation. During the transmission planning, a scenario-based multi-objective transmission planning (MOTP) framework is proposed to simultaneously optimize two objectives, i.......e. the cost of power purchase and network expansion, and the revenue of power delivery. A two-phase multi-objective PSO (MOPSO) algorithm is employed to be the solver. The feasibility of the proposed multi-objective planning approach has been verified by the 77-bus system linked with 38-bus distribution...

  1. Multi-objective quantum genetic algorithm in WSNs distribution optimization

    Science.gov (United States)

    Wen, Hao; Ren, Hong-liang

    2013-03-01

    To achieve lower energy and higher detection coverage simultaneously in scattering distribution wireless sensor networks (WSNs), a multi-objective optimization function combined with area coverage and node-communication energy is constructed. Based on the multi-objective quantum genetic algorithm (Mo-QGA) proposed by Li Bin and Zhuang-zhen Quan et al, we have obtained optimum solutions close to Pareto front. Experimental results indicate that the Mo-QGA has advantages both on efficiency and coverage, as well as low energy.

  2. MULTI OBJECTIVE ECONOMIC DISPATCH USING PARETO FRONTIER DIFFERENTIAL EVOLUTION

    Directory of Open Access Journals (Sweden)

    JAGADEESH GUNDA

    2011-10-01

    Full Text Available Multi Objective Economic dispatch (MOED problem has gained recent attention due to the deregulation of power industry and environmental regulations. So generating utilities should optimize their emission inaddition to the operating cost. In this paper a Pareto frontier Differential Evolution (PDE technique is developed to solve MOED problem, which provides a set of feasible solutions to the problem. To evaluate the performance and applicability of the proposed method, it is implemented on the standard IEEE-30 bus system having six generating units including valve point effects. The results obtained demonstrate the effectiveness of the proposed method for solving the Multi Objective economic dispatch problem considering security constraints.

  3. Entropy Diversity in Multi-Objective Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Eduardo J. Solteiro Pires

    2013-12-01

    Full Text Available Multi-objective particle swarm optimization (MOPSO is a search algorithm based on social behavior. Most of the existing multi-objective particle swarm optimization schemes are based on Pareto optimality and aim to obtain a representative non-dominated Pareto front for a given problem. Several approaches have been proposed to study the convergence and performance of the algorithm, particularly by accessing the final results. In the present paper, a different approach is proposed, by using Shannon entropy to analyze the MOPSO dynamics along the algorithm execution. The results indicate that Shannon entropy can be used as an indicator of diversity and convergence for MOPSO problems.

  4. Global, Multi-Objective Trajectory Optimization With Parametric Spreading

    Science.gov (United States)

    Vavrina, Matthew A.; Englander, Jacob A.; Phillips, Sean M.; Hughes, Kyle M.

    2017-01-01

    Mission design problems are often characterized by multiple, competing trajectory optimization objectives. Recent multi-objective trajectory optimization formulations enable generation of globally-optimal, Pareto solutions via a multi-objective genetic algorithm. A byproduct of these formulations is that clustering in design space can occur in evolving the population towards the Pareto front. This clustering can be a drawback, however, if parametric evaluations of design variables are desired. This effort addresses clustering by incorporating operators that encourage a uniform spread over specified design variables while maintaining Pareto front representation. The algorithm is demonstrated on a Neptune orbiter mission, and enhanced multidimensional visualization strategies are presented.

  5. Multi-objective nested algorithms for optimal reservoir operation

    Science.gov (United States)

    Delipetrev, Blagoj; Solomatine, Dimitri

    2016-04-01

    The optimal reservoir operation is in general a multi-objective problem, meaning that multiple objectives are to be considered at the same time. For solving multi-objective optimization problems there exist a large number of optimization algorithms - which result in a generation of a Pareto set of optimal solutions (typically containing a large number of them), or more precisely, its approximation. At the same time, due to the complexity and computational costs of solving full-fledge multi-objective optimization problems some authors use a simplified approach which is generically called "scalarization". Scalarization transforms the multi-objective optimization problem to a single-objective optimization problem (or several of them), for example by (a) single objective aggregated weighted functions, or (b) formulating some objectives as constraints. We are using the approach (a). A user can decide how many multi-objective single search solutions will generate, depending on the practical problem at hand and by choosing a particular number of the weight vectors that are used to weigh the objectives. It is not guaranteed that these solutions are Pareto optimal, but they can be treated as a reasonably good and practically useful approximation of a Pareto set, albeit small. It has to be mentioned that the weighted-sum approach has its known shortcomings because the linear scalar weights will fail to find Pareto-optimal policies that lie in the concave region of the Pareto front. In this context the considered approach is implemented as follows: there are m sets of weights {w1i, …wni} (i starts from 1 to m), and n objectives applied to single objective aggregated weighted sum functions of nested dynamic programming (nDP), nested stochastic dynamic programming (nSDP) and nested reinforcement learning (nRL). By employing the multi-objective optimization by a sequence of single-objective optimization searches approach, these algorithms acquire the multi-objective properties

  6. MIRADAS: The Multi-Object R=22K Near-IR Spectropolarimeter for the 10.4-meter GTC

    Science.gov (United States)

    Eikenberry, Stephen S.; MIRADAS Consortium

    2016-01-01

    The Mid-resolution InfRAreD Astronomical Spectrograph (MIRADAS), a near-infrared multi-object echelle spectrograph operating at spectral resolution R=22,000 over the 1-2.5µm bandpass, is being developed by an international consosrtium for the 10.4-meter Gran Telescopio Canarias (GTC). The MIRADAS consortium includes the University of Florida, Universidad de Barcelona, Universidad Complutense de Madrid, Instituto de Astrofísica de Canarias, as well as industrial partners in the US and Europe. MIRADAS completed its Final Design Review in mid-2015, and is currently undergoing fabrication, with planned first light in 2018/2019. In this paper, we review the overall science drivers and system design for MIRADAS, including key technologies such as cryogenic robotic probe arms, macroslicer mini-IFUs, full Stokes polarimetry, and a highly flexible observing configuration.

  7. 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

  8. Fault Detection and Isolation using Multi Objective Controller Design Techniques

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Niemann, Hans Henrik

    1996-01-01

    Abstract: This paper describes a method for designing fault detectionand isolation filters. The method is multi objective in the sense thatit follows optimization with arbitrarily mixed criteria specified ine.g. the QTR H-infinity or the QTR H^2 norm. Moreover,the involved optimization yields less...

  9. Computing Convex Coverage Sets for Multi-Objective Coordination Graphs

    NARCIS (Netherlands)

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

    2013-01-01

    Many real-world decision problems require making trade-offs between multiple objectives. However, in some cases, the relative importance of the objectives is not known when the problem is solved, precluding the use of single-objective methods. Instead, multi-objective methods, which compute the set

  10. 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...

  11. Navigation Constellation Design Using a Multi-Objective Genetic Algorithm

    Science.gov (United States)

    2015-03-26

    the mutation and crossover functions specified that certain design parameters be integer values [17]. Equation 21 represents the variables that...been used to force certain design variables to be integer values. Understanding the MATLAB code for the mutation and crossover functions is not...NAVIGATION CONSTELLATION DESIGN USING A MULTI-OBJECTIVE GENETIC ALGORITHM THESIS MARCH 2015

  12. Multi-Objective Constraint Satisfaction for Mobile Robot Area Defense

    Science.gov (United States)

    2010-03-01

    Dorronsoro, and En- rique Alba. jMetal: A Java Framework for Developing Multi-Objective Optimiza- tion Metaheuristics . Technical Report ITI-2006-10...32 3.1 Framework Development...17 NSGA-II non-dominated sorting genetic algorithm II . . . . . . . . . . . . . . . . . . . 17 jMetal Metaheuristic Algorithms in

  13. Study of Multi-objective Fuzzy Optimization for Path Planning

    Institute of Scientific and Technical Information of China (English)

    WANG Yanyang; WEI Tietao; QU Xiangju

    2012-01-01

    During path planning,it is necessary to satisfy the requirements of multiple objectives.Multi-objective synthesis is based on the need of flight mission and subjectivity inclination of decision-maker.The decision-maker,however,has illegibility for understanding the requirements of multiple objectives and the subjectivity inclination.It is important to develop a reasonable cost performance index for describing the illegibility of the decision-maker in multi-objective path planning.Based on Voronoi diagram method for the path planning,this paper studies the synthesis method of the multi-objective cost performance index.According to the application of the cost performance index to the path planning based on Voronoi diagram method,this paper analyzes the cost performance index which has been referred to at present.The analysis shows the insufficiency of the cost performance index at present,i.e.,it is difficult to synthesize sub-objective functions because of the great disparity of the sub-objective functions.Thus,a new approach is developed to optimize the cost performance index with the multi-objective fuzzy optimization strategy,and an improved performance index is established,which could coordinate the weight conflict of the sub-objective functions.Finally,the experimental result shows the effectiveness of the proposed approach.

  14. Analysing the performance of dynamic multi-objective optimisation algorithms

    CSIR Research Space (South Africa)

    Helbig, M

    2013-06-01

    Full Text Available Congress on Evolutionary Computation, 20-23 June 2013, Cancún, México Analysing the Performance of Dynamic Multi-objective Optimisation Algorithms Marde Helbig CSIR: Meraka Institute, Brummeria, South Africa; and University of Pretoria Computer...

  15. Genetic Tabu Search for the Multi-Objective Knapsack Problem

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    We introduce a hybrid algorithm for the 0-1 multidimensional multi-objective knapsack problem. This algorithm, called GTSMOKP, combines a genetic procedure and a tabu search operator. The algorithm is evaluated on 9 well-known benchmark instances and shows highly competitive results compared with two state-of-the-art algorithms.

  16. Covariance matrix adaptation for multi-objective optimization.

    Science.gov (United States)

    Igel, Christian; Hansen, Nikolaus; Roth, Stefan

    2007-01-01

    The covariance matrix adaptation evolution strategy (CMA-ES) is one of the most powerful evolutionary algorithms for real-valued single-objective optimization. In this paper, we develop a variant of the CMA-ES for multi-objective optimization (MOO). We first introduce a single-objective, elitist CMA-ES using plus-selection and step size control based on a success rule. This algorithm is compared to the standard CMA-ES. The elitist CMA-ES turns out to be slightly faster on unimodal functions, but is more prone to getting stuck in sub-optimal local minima. In the new multi-objective CMAES (MO-CMA-ES) a population of individuals that adapt their search strategy as in the elitist CMA-ES is maintained. These are subject to multi-objective selection. The selection is based on non-dominated sorting using either the crowding-distance or the contributing hypervolume as second sorting criterion. Both the elitist single-objective CMA-ES and the MO-CMA-ES inherit important invariance properties, in particular invariance against rotation of the search space, from the original CMA-ES. The benefits of the new MO-CMA-ES in comparison to the well-known NSGA-II and to NSDE, a multi-objective differential evolution algorithm, are experimentally shown.

  17. 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.

  18. Masses of Nix and Hydra

    CERN Document Server

    Tholen, David J; Grundy, William M; Elliott, Garrett T

    2007-01-01

    A four-body orbit solution for the Pluto system yields GM values of 870.3 +/- 3.7, 101.4 +/- 2.8, 0.039 +/- 0.034, and 0.021 +/- 0.042 km3 sec-2 for Pluto, Charon, Nix, and Hydra, respectively. Assuming a Charon-like density of 1.63 gm cm-3, the implied diameters for Nix and Hydra are 88 and 72 km, leading to visual geometric albedos of 0.08 and 0.18, respectively, though with considerable uncertainty. The eccentricity of Charon's orbit has a significant nonzero value; however, the 0.030 +/- 0.009 deg yr-1 rate at which the line of apsides precesses is insufficient to explain the difference in the longitude of periapsis seen in the orbits fitted to the 1992-1993 and 2002-2003 data sets. The mean orbital periods for Hydra, Nix, and Charon are in the ratios of 6.064 +/- 0.006 : 3.991 +/- 0.007 : 1, but we have not identified any resonant arguments that would indicate the existence of a mean motion resonance between any pairs of satellites.

  19. High resolution spectrograph for the 4MOST facility

    Science.gov (United States)

    Mignot, Shan; Amans, Jean-Philippe; Cohen, Mathieu; Horville, David; Jagourel, Pascal

    2012-09-01

    4MOST (4-metre Multi-Object Spectrograph Telescope) is a wide field and high multiplex fibre-fed spectroscopic facility continuously running a public survey on one of ESO's 4-metre telescopes (NTT or VISTA). It is currently undergoing a concept study and comprises a multi-object (300) high resolution (20 000) spectrograph whose purpose is to provide detailed chemical information in two wavelength ranges (395-456.5 nm and 587-673 nm). It will complement the data produced by ESA's space mission Gaia to form an unprecedented galactic-archaeology picture of the Milky Way as the result of the public survey. Building on the developments carried out for the GYES1 instrument on the Canada- France-Hawaii Telescope in 2010, the spectrograph is intended as being athermal and not featuring any motorised parts for high reliability and minimum maintenance, thereby allowing it to operate every night for five years. In addition to the fixed configuration which allows fine-tuning the spectrograph to a precise need, it features a dual-arm architecture with volume-phase holographic gratings to achieve the required dispersion at a maximum efficiency in each channel. By combining high yield time-wise and photon-wise, the spectrograph is expected to deliver more than a million spectra and make the most out of the selected 4-metre telescope.

  20. 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 ...

  1. Evidence of coevolution in multi-objective evolutionary algorithms

    CERN Document Server

    Whitacre, James M

    2009-01-01

    This paper demonstrates that simple yet important characteristics of coevolution can occur in evolutionary algorithms when only a few conditions are met. We find that interaction-based fitness measurements such as fitness (linear) ranking allow for a form of coevolutionary dynamics that is observed when 1) changes are made in what solutions are able to interact during the ranking process and 2) evolution takes place in a multi-objective environment. This research contributes to the study of simulated evolution in a at least two ways. First, it establishes a broader relationship between coevolution and multi-objective optimization than has been previously considered in the literature. Second, it demonstrates that the preconditions for coevolutionary behavior are weaker than previously thought. In particular, our model indicates that direct cooperation or competition between species is not required for coevolution to take place. Moreover, our experiments provide evidence that environmental perturbations can dri...

  2. Multi-Objective Simulating Annealing for Permutation Flow Shop Problems

    Science.gov (United States)

    Mokotoff, E.; Pérez, J.

    2007-09-01

    Real life scheduling problems require more than one criterion. Nevertheless, the complex nature of the Permutation Flow Shop problem has prevented the development of models with multiple criteria. Considering only one regular criterion, this scheduling problem was shown to be NP-complete. The Multi-Objective Simulated Annealing (MOSA) methods are metaheuristics based on Simulated Annealing to solve Multi-Objective Combinatorial Optimization (MOCO) problems, like the problem at hand. Starting from the general MOSA method introduced by Loukil et al. [1], we developed MOSA models to provide the decision maker with efficient solutions for the Permutation Flow Shop problem (common in the production of ceramic tiles). In this paper we present three models: two bicriteria models and one based on satisfaction levels for the main criterion.

  3. Multi-objective optimization of an axial compressor blade

    Energy Technology Data Exchange (ETDEWEB)

    Samad, Abdus; Kim, Kwang Yong [Inha University, Incheon (Korea, Republic of)

    2008-05-15

    Numerical optimization with multiple objectives is carried out for design of an axial compressor blade. Two conflicting objectives, total pressure ratio and adiabatic efficiency, are optimized with three design variables concerning sweep, lean and skew of blade stacking line. Single objective optimizations have been also performed. At the data points generated by D-optimal design, the objectives are calculated by three-dimensional Reynolds-averaged Navier-Stokes analysis. A second-order polynomial based response surface model is generated, and the optimal point is searched by sequential quadratic programming method for single objective optimization. Elitist non-dominated sorting of genetic algorithm (NSGA-II) with {epsilon}-constraint local search strategy is used for multi-objective optimization. Both objective function values are found to be improved as compared to the reference one by multi-objective optimization. The flow analysis results show the mechanism for the improvement of blade performance

  4. A New RWA Algorithm Based on Multi-Objective

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    In this article, we studied the associated research problems and challenges on routing and wavelength assignment (RWA) in WDM (wavelength division multiplexing) networks. Various RWA approaches are examined and compared. We proposed a new RWA algorithm based on multi-objective. In this new algorithm, we consider multiple network optimizing objectives to setup a lightpath with maximize profit and shortest path under the limited resources. By comparing and analyzing, the proposed algorithm is much better ...

  5. OSIRIS Multi-Object Spectroscopy: Mask Design Process

    Science.gov (United States)

    Gómez-Velarde, G.; García-Alvarez, D.; Cabrerra-Lavers, A.

    2016-10-01

    The OSIRIS (Optical System for Imaging and Low-Intermediate Resolution Integrated Spectroscopy) instrument at the 10.4 m GTC has offered a multi-object spectroscopic mode since March 2014. In this paper we describe the detailed process of designing a MOS mask for OSIRIS by using the Mask Designer Tool, and give some numbers on the accuracy of the mask manufacture achievable at the telescope for its scientific use.

  6. Enhanced Multi-Objective Energy Optimization by a Signaling Method

    Directory of Open Access Journals (Sweden)

    João Soares

    2016-10-01

    Full Text Available 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-dimensional signaling is also compared with this technique, which has previously been shown to boost metaheuristics performance for single-objective problems. Hence, multi-dimensional signaling is adapted and implemented here for the proposed multi-objective problem. In addition, parallel computing is used to mitigate the methods’ computational execution time. To validate the proposed techniques, a realistic case study for a chosen area of the northern region of Portugal is considered, namely part of Vila Real distribution grid (233-bus. It is assumed that this grid is managed by an energy aggregator entity, with reasonable amount of electric vehicles (EVs, several distributed generation (DG, customers with demand response (DR contracts and energy storage systems (ESS. The considered case study characteristics took into account several reported research works with projections for 2020 and 2050. The findings strongly suggest that the signaling method clearly improves the results and the Pareto front region quality.

  7. Replication in Overlay Networks: A Multi-objective Optimization Approach

    Science.gov (United States)

    Al-Haj Hassan, Osama; Ramaswamy, Lakshmish; Miller, John; Rasheed, Khaled; Canfield, E. Rodney

    Recently, overlay network-based collaborative applications such as instant messaging, content sharing, and Internet telephony are becoming increasingly popular. Many of these applications rely upon data-replication to achieve better performance, scalability, and reliability. However, replication entails various costs such as storage for holding replicas and communication overheads for ensuring replica consistency. While simple rule-of-thumb strategies are popular for managing the cost-benefit tradeoffs of replication, they cannot ensure optimal resource utilization. This paper explores a multi-objective optimization approach for replica management, which is unique in the sense that we view the various factors influencing replication decisions such as access latency, storage costs, and data availability as objectives, and not as constraints. This enables us to search for solutions that yield close to optimal values for these parameters. We propose two novel algorithms, namely multi-objective Evolutionary (MOE) algorithm and multi-objective Randomized Greedy (MORG) algorithm for deciding the number of replicas as well as their placement within the overlay. While MOE yields higher quality solutions, MORG is better in terms of computational efficiency. The paper reports a series of experiments that demonstrate the effectiveness of the proposed algorithms.

  8. Multi-objective based spectral unmixing for hyperspectral images

    Science.gov (United States)

    Xu, Xia; Shi, Zhenwei

    2017-02-01

    Sparse hyperspectral unmixing assumes that each observed pixel can be expressed by a linear combination of several pure spectra in a priori library. Sparse unmixing is challenging, since it is usually transformed to a NP-hard l0 norm based optimization problem. Existing methods usually utilize a relaxation to the original l0 norm. However, the relaxation may bring in sensitive weighted parameters and additional calculation error. In this paper, we propose a novel multi-objective based algorithm to solve the sparse unmixing problem without any relaxation. We transform sparse unmixing to a multi-objective optimization problem, which contains two correlative objectives: minimizing the reconstruction error and controlling the endmember sparsity. To improve the efficiency of multi-objective optimization, a population-based randomly flipping strategy is designed. Moreover, we theoretically prove that the proposed method is able to recover a guaranteed approximate solution from the spectral library within limited iterations. The proposed method can directly deal with l0 norm via binary coding for the spectral signatures in the library. Experiments on both synthetic and real hyperspectral datasets demonstrate the effectiveness of the proposed method.

  9. A Bayesian Alternative for Multi-objective Ecohydrological Model Specification

    Science.gov (United States)

    Tang, Y.; Marshall, L. A.; Sharma, A.; Ajami, H.

    2015-12-01

    Process-based ecohydrological models combine the study of hydrological, physical, biogeochemical and ecological processes of the catchments, which are usually 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. Our study aims to develop appropriate prior distributions and likelihood functions that minimize the model uncertainties and bias within a Bayesian ecohydrological framework. In our study, a formal Bayesian approach is implemented in an ecohydrological model which combines a hydrological model (HyMOD) and a dynamic vegetation model (DVM). Simulations focused on one objective likelihood (Streamflow/LAI) and multi-objective likelihoods (Streamflow and LAI) with different weights are compared. Uniform, weakly informative and strongly informative prior distributions are used in different simulations. The Kullback-leibler divergence (KLD) is used to measure the dis(similarity) between different priors and corresponding posterior distributions to examine the parameter sensitivity. Results show that different prior distributions can strongly influence posterior distributions for parameters, especially when the available data is limited or parameters are insensitive to the available data. We demonstrate differences in optimized parameters and uncertainty limits in different cases based on multi-objective likelihoods vs. single objective likelihoods. We also demonstrate the importance of appropriately defining the weights of objectives in multi-objective calibration according to different data types.

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

    KAUST Repository

    Abdelfattah, Ahmad M.

    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.

  11. Coexistence of neuropeptides in hydra

    DEFF Research Database (Denmark)

    Grimmelikhuijzen, C J

    1983-01-01

    Using a technique for simultaneous visualisation of two antigens in one section, oxytocin-like immunoreactivity has been found to coexist with bombesin-like immunoreactivity in neurons of the basal disk, gastric region and tentacles of hydra. Neurons with oxytocin-like immunoreactivity in peduncle...... and hypostome, on the other hand, have little or no bombesin-like material. Oxytocin-like immunoreactivity never coexists with FMRFamide-immunoreactivity. The neurons with oxytocin- and FMRFamide-like immunoreactivity, however, are often found to be closely intermingled. The results show that coexistence...

  12. Multi-objective community detection based on memetic algorithm.

    Directory of Open Access Journals (Sweden)

    Peng Wu

    Full Text Available Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels.

  13. EFFICIENT MULTI-OBJECTIVE EVOLUTIONARY ALGORITHM FOR JOB SHOP SCHEDULING

    Institute of Scientific and Technical Information of China (English)

    Lei Deming; Wu Zhiming

    2005-01-01

    A new representation method is first presented based on priority rules. According to this method, each entry in the chromosome indicates that in the procedure of the Giffler and Thompson (GT) algorithm, the conflict occurring in the corresponding machine is resolved by the corresponding priority rule. Then crowding-measure multi-objective evolutionary algorithm (CMOEA) is designed,in which both archive maintenance and fitness assignment use crowding measure. Finally the comparisons between CMOEA and SPEA in solving 15 scheduling problems demonstrate that CMOEA is suitable to job shop scheduling.

  14. Multi-objective optimization of acoustic black hole vibration absorbers.

    Science.gov (United States)

    Shepherd, Micah R; Feurtado, Philip A; Conlon, Stephen C

    2016-09-01

    Structures with power law tapers exhibit the acoustic black hole (ABH) effect and can be used for vibration reduction. However, the design of ABHs for vibration reduction requires consideration of the underlying theory and its regions of validity. To address the competing nature of the best ABH design for vibration reduction and the underlying theoretical assumptions, a multi-objective approach is used to find the lowest frequency where both criteria are sufficiently met. The Pareto optimality curve is estimated for a range of ABH design parameters. The optimal set could then be used to implement an ABH vibration absorber.

  15. Uncertain multi-objective multi-product solid transportation problems

    Indian Academy of Sciences (India)

    DEEPIKA RANI; T R GULATI

    2016-05-01

    The solid transportation problem is an important generalization of the classical transportation problem as it also considers the conveyance constraints along with the source and destination constraints. The problem can be made more effective by incorporating some other factors, which make it useful in real lifesituations. In this paper, we consider a fully fuzzy multi-objective multi-item solid transportation problem and present a method to find its fuzzy optimal-compromise solution using the fuzzy programming technique. To take into account the imprecision in finding the exact values of parameters, all the parameters are taken as trapezoidal fuzzy numbers. A numerical example is solved to illustrate the methodology

  16. Towards Automatic Controller Design using Multi-Objective Evolutionary Algorithms

    DEFF Research Database (Denmark)

    Pedersen, Gerulf

    of evolutionary computation, a choice was made to use multi-objective algorithms for the purpose of aiding in automatic controller design. More specifically, the choice was made to use the Non-dominated Sorting Genetic Algorithm II (NSGAII), which is one of the most potent algorithms currently in use......, as the foundation for achieving the desired goal. While working with the algorithm, some issues arose which limited the use of the algorithm for unknown problems. These issues included the relative scale of the used fitness functions and the distribution of solutions on the optimal Pareto front. Some work has...

  17. Multi-objective Optimization on Helium Liquefier Using Genetic Algorithm

    Science.gov (United States)

    Wang, H. R.; Xiong, L. Y.; Peng, N.; Meng, Y. R.; Liu, L. Q.

    2017-02-01

    Research on optimization of helium liquefier is limited at home and abroad, and most of the optimization is single-objective based on Collins cycle. In this paper, a multi-objective optimization is conducted using genetic algorithm (GA) on the 40 L/h helium liquefier developed by Technical Institute of Physics and Chemistry of the Chinese Academy of Science (TIPC, CAS), steady solutions are obtained in the end. In addition, the exergy loss of the optimized system is studied in the case of with and without liquid nitrogen pre-cooling. The results have guiding significance for the future design of large helium liquefier.

  18. METHOD OF CENTERS ALGORITHM FOR MULTI-OBJECTIVE PROGRAMMING PROBLEMS

    Institute of Scientific and Technical Information of China (English)

    Tarek Emam

    2009-01-01

    In this paper, we consider a method of centers for solving multi-objective programming problems, where the objective functions involved are concave functions and the set of feasible points is convex. The algorithm is defined so that the sub-problems that must be solved during its execution may be solved by finite-step procedures. Conditions are given under which the algorithm generates sequences of feasible points and constraint multiplier vectors that have accumulation points satisfying the KKT conditions. Finally, we establish convergence of the proposed method of centers algorithm for solving multiobjective programming problems.

  19. Large Sky Area Multi-Object Fiber Spectroscopic Telescope

    Institute of Scientific and Technical Information of China (English)

    ZHAO Yongheng

    2011-01-01

    The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) is a meridian reflecting Schmidt telescope with a clear aperture of four meters, a focal length of 20 meters and a field of view of five degrees. By using active optics technique to control its reflecting corrector, the LAMOST is made a unique astronomical instrument in combining a large aperture with a wide field of view. The available large focal plane of 1.75 meter in diameter can accommodate up to 4,000 fibers,

  20. Dynamic Cell Formation based on Multi-objective Optimization Model

    Directory of Open Access Journals (Sweden)

    Guozhu Jia

    2013-08-01

    Full Text Available In this paper, a multi-objective model is proposed to address the dynamic cellular manufacturing (DCM formation problem. This model considers four conflicting objectives: relocation cost, machine utilization, material handling cost and maintenance cost. The model also considers the situation that some machines could be shared by more than one cell at the same period. A genetic algorithm is applied to get the solution of this mathematical model. Three numerical examples are simulated to evaluate the validity of this model.  

  1. 4MOST - 4-metre Multi-Object Spectroscopic Telescope

    CERN Document Server

    de Jong, Roelof S; Chiappini, Cristina; Depagne, Éric; Haynes, Roger; Johl, Diane; Schnurr, Olivier; Schwope, Axel; Walcher, Jakob; Dionies, Frank; Haynes, Dionne; Kelz, Andreas; Kitaura, Francisco S; Lamer, Georg; Minchev, Ivan; Müller, Volker; Nuza, Sebastián E; Olaya, Jean-Christophe; Piffl, Tilmann; Popow, Emil; Steinmetz, Matthias; Ural, Uğur; Williams, Mary; Winkler, Roland; Wisotzki, Lutz; Ansorgb, Wolfgang R; Banerji, Manda; Solares, Eduardo Gonzalez; Irwin, Mike; Kennicutt, Robert C; King, David; McMahon, Richard; Koposov, Sergey; Parry, Ian R; Walton, Nicholas A; Finger, Gert; Iwert, Olaf; Krumpe, Mirko; Lizon, Jean-Louis; Vincenzo, Mainieri; Amans, Jean-Philippe; Bonifacio, Piercarlo; Cohen, Mathieu; Francois, Patrick; Jagourel, Pascal; Mignot, Shan B; Royer, Frédéric; Sartoretti, Paola; Bender, Ralf; Grupp, Frank; Hess, Hans-Joachim; Lang-Bardl, Florian; Muschielok, Bernard; Böhringer, Hans; Boller, Thomas; Bongiorno, Angela; Brusa, Marcella; Dwelly, Tom; Merloni, Andrea; Nandra, Kirpal; Salvato, Mara; Pragt, Johannes H; Navarro, Ramón; Gerlofsma, Gerrit; Roelfsema, Ronald; Dalton, Gavin B; Middleton, Kevin F; Tosh, Ian A; Boeche, Corrado; Caffau, Elisabetta; Christlieb, Norbert; Grebel, Eva K; Hansen, Camilla; Koch, Andreas; Ludwig, Hans-G; Quirrenbach, Andreas; Sbordone, Luca; Seifert, Walter; Thimm, Guido; Trifonov, Trifon; Helmi, Amina; Trager, Scott C; Feltzing, Sofia; Korn, Andreas; Boland, Wilfried

    2012-01-01

    The 4MOST consortium is currently halfway through a Conceptual Design study for ESO with the aim to develop a wide-field (>3 square degree, goal >5 square degree), high-multiplex (>1500 fibres, goal 3000 fibres) spectroscopic survey facility for an ESO 4m-class telescope (VISTA). 4MOST will run permanently on the telescope to perform a 5 year public survey yielding more than 20 million spectra at resolution R~5000 ({\\lambda}=390-1000 nm) and more than 2 million spectra at R~20,000 (395-456.5 nm & 587-673 nm). The 4MOST design is especially intended to complement three key all-sky, space-based observatories of prime European interest: Gaia, eROSITA and Euclid. Initial design and performance estimates for the wide-field corrector concepts are presented. We consider two fibre positioner concepts, a well-known Phi-Theta system and a new R-Theta concept with a large patrol area. The spectrographs are fixed configuration two-arm spectrographs, with dedicated spectrographs for the high- and low-resolution. A ful...

  2. 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.

  3. Multi-Objective Model Checking of Markov Decision Processes

    CERN Document Server

    Etessami, Kousha; Vardi, Moshe Y; Yannakakis, Mihalis

    2008-01-01

    We study and provide efficient algorithms for multi-objective model checking problems for Markov Decision Processes (MDPs). Given an MDP, $M$, and given multiple linear-time ($\\omega$-regular or LTL) properties $\\varphi_i$, and probabilities $r_i \\in [0,1]$, $i=1,...,k$, we ask whether there exists a strategy $\\sigma$ for the controller such that, for all $i$, the probability that a trajectory of $M$ controlled by $\\sigma$ satisfies $\\varphi_i$ is at least $r_i$. We provide an algorithm that decides whether there exists such a strategy and if so produces it, and which runs in time polynomial in the size of the MDP. Such a strategy may require the use of both randomization and memory. We also consider more general multi-objective $\\omega$-regular queries, which we motivate with an application to assume-guarantee compositional reasoning for probabilistic systems. Note that there can be trade-offs between different properties: satisfying property $\\varphi_1$ with high probability may necessitate satisfying $\\var...

  4. 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.

  5. Estimation of subsurface geomodels by multi-objective stochastic optimization

    Science.gov (United States)

    Emami Niri, Mohammad; Lumley, David E.

    2016-06-01

    We present a new method to estimate subsurface geomodels using a multi-objective stochastic search technique that allows a variety of direct and indirect measurements to simultaneously constrain the earth model. Inherent uncertainties and noise in real data measurements may result in conflicting geological and geophysical datasets for a given area; a realistic earth model can then only be produced by combining the datasets in a defined optimal manner. One approach to solving this problem is by joint inversion of the various geological and/or geophysical datasets, and estimating an optimal model by optimizing a weighted linear combination of several separate objective functions which compare simulated and observed datasets. In the present work, we consider the joint inversion of multiple datasets for geomodel estimation, as a multi-objective optimization problem in which separate objective functions for each subset of the observed data are defined, followed by an unweighted simultaneous stochastic optimization to find the set of best compromise model solutions that fits the defined objectives, along the so-called "Pareto front". We demonstrate that geostatistically constrained initializations of the algorithm improves convergence speed and produces superior geomodel solutions. We apply our method to a 3D reservoir lithofacies model estimation problem which is constrained by a set of geological and geophysical data measurements and attributes, and assess the sensitivity of the resulting geomodels to changes in the parameters of the stochastic optimization algorithm and the presence of realistic seismic noise conditions.

  6. 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.

  7. Evolutionary Multi-objective Portfolio Optimization in Practical Context

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    This paper addresses evolutionary multi-objective portfolio optimization in the practical context by incorporating realistic constraints into the problem model and preference criterion into the optimization search process. The former is essential to enhance the realism of the classical mean-variance model proposed by Harry Markowitz, since portfolio managers often face a number of realistic constraints arising from business and industry regulations, while the latter reflects the fact that portfolio managers are ultimately interested in specific regions or points along the efficient frontier during the actual execution of their investment orders. For the former,this paper proposes an order-based representation that can be easily extended to handle various realistic constraints like floor and ceiling constraints and cardinality constraint. An experimental study, based on benchmark problems obtained from the OR-library,demonstrates its capability to attain a better approximation of the efficient frontier in terms of proximity and diversity with respect to other conventional representations. The experimental results also illustrated its viability and practicality in handling the various realistic constraints. A simple strategy to incorporate preferences into the multi-objective optimization process is highlighted and the experimental study demonstrates its capability in driving the evolutionary search towards specific regions of the efficient frontier.

  8. 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.

  9. CROMOS A cryogenic near-infrared, multi-object spectrometer for the VLT

    CERN Document Server

    Genzel, R; Tomono, D; Thatte, N; Eisenhauer, F; Lehnert, M; Tecza, M; Bender, R

    2001-01-01

    We discuss a cryogenic, multi-object near-infrared spectrometer as a second generation instrument for the VLT. The spectrometer combines 20 to 40 independent integral eld units (IFUs), which can be positioned by a cryogenic robot over the entire unvignetted eld of the VLT (~7'). Each IFU consists of a contiguous cluster of 20 to 30 pixels (0.15 to 0.25" per pixel). The individual IFUs have cold fore-optics and couple into the spectrograph with integrated bers-microlenses. The spectrometer has lambda/d-lambda~4000 and simultaneously covers the J-, H-, and K-bands with three HAWAII 2 detectors. The system is designed for operation both in seeing limited and MCAO modes. Its speed is approximately 3500 times greater than that of ISAAC and 60 times greater than NIRMOS (in H-band). The proposed instrument aims at a wide range of science, ranging from studies of galaxies/clusters in the high-z Universe (dynamics and star formation in z>1 galaxies, evolution of ellipticals, properties of distant, obscured far-IR and ...

  10. Cone of Darkness: Finding Blank-sky Positions for Multi-object Wide-field Observations

    CERN Document Server

    Lorente, Nuria P F

    2013-01-01

    We present the Cone of Darkness, an application to automatically configure blank-sky positions for a series of stacked, wide-field observations, such as those carried out by the SAMI instrument on the Anglo-Australian Telescope (AAT). The Sydney-AAO Multi-object Integral field spectrograph (SAMI) uses a plug-plate to mount its $13 \\times 61$ core imaging fibre bundles (hexabundles) in the optical plane at the telescope's prime focus. To make the most efficient use of each plug-plate, several observing fields are typically stacked to produce a single plate. When choosing blank-sky positions for the observations it is most effective to select these such that one set of 26 holes gives valid sky positions for all fields on the plate. However, when carried out manually this selection process is tedious and includes a significant risk of error. The Cone of Darkness software aims to provide uniform blank-sky position coverage over the field of observation, within the limits set by the distribution of target position...

  11. Integration, Testing and Performance of the Infrared Multi-Object Spectrometer

    Science.gov (United States)

    Ohl, Raymond G.; Connelly, Joseph A.; Boyle, Robert F.; Derro, Rebecca J.; Greenhouse, Matthew A.; Madison, Timothy J.; Mentzell, J. Eric; Sparr, Leroy M.; Hylan, Jason E.; Ray, Knute

    2003-01-01

    The Infrared Multi-Object Spectrometer (IRMOS) is a principle investigator-class instrument for the Kitt Peak National Observatory 2.1 m and Mayall 3.8 m telescopes. IRMOS is a near-IR (0.8 - 2.5 micron) spectrometer with low-to mid-resolving power (R = lambda/delta lambda = 300 - 3000). On the 3.8 m telescope, IRMOS produces simultaneous spectra of approximately 100 objects in its approximately 3 x 2 arcmin field of view using a commercial micro electro-mechanical systems (MEMS) digital micro-mirror device (DMD) from Texas Instruments. The multi-mirror array DMD operates as a real-time programmable slit mask. The all-reflective optical design consists of two imaging subsystems. The focal reducer images the focal plane of the telescope onto the DMD field stop, and the spectrograph images the DMD onto a large-format detector. The instrument operates at approximately 80 K, cooled by a single electro-mechanical cryocooler. The bench and all components are made from aluminum 6061-T651. There are three cryogenic mechanisms. We describe laboratory integration and test of IRMOS before shipment to Kitt Peak. We give an overview of the optical alignment technique and integration of optical, mechanical, electrical and cryogenic subsystems. We compare optical test results to model predictions of point spread function size and morphology, contrast, and stray light. We discuss some lessons learned and conclude with a prediction for performance on the telescope.

  12. The Science Case for Multi-Object Spectroscopy on the European ELT

    CERN Document Server

    Evans, Chris; Afonso, Jose; Almaini, Omar; Amram, Philippe; Aussel, Hervé; Barbuy, Beatriz; Basden, Alistair; Bastian, Nate; Battaglia, Giuseppina; Biller, Beth; Bonifacio, Piercarlo; Bouché, Nicholas; Bunker, Andy; Caffau, Elisabetta; Charlot, Stephane; Cirasuolo, Michele; Clenet, Yann; Combes, Francoise; Conselice, Chris; Contini, Thierry; Cuby, Jean-Gabriel; Dalton, Gavin; Davies, Ben; de Koter, Alex; Disseau, Karen; Dunlop, Jim; Epinat, Benoît; Fiore, Fabrizio; Feltzing, Sofia; Ferguson, Annette; Flores, Hector; Fontana, Adriano; Fusco, Thierry; Gadotti, Dimitri; Gallazzi, Anna; Gallego, Jesus; Giallongo, Emanuele; Gonçalves, Thiago; Gratadour, Damien; Guenther, Eike; Hammer, Francois; Hill, Vanessa; Huertas-Company, Marc; Ibata, Roridgo; Kaper, Lex; Korn, Andreas; Larsen, Søren; Fèvre, Olivier Le; Lemasle, Bertrand; Maraston, Claudia; Mei, Simona; Mellier, Yannick; Morris, Simon; Östlin, Göran; Paumard, Thibaut; Pello, Roser; Pentericci, Laura; Peroux, Celine; Petitjean, Patrick; Rodrigues, Myriam; Rodríguez-Muñoz, Lucía; Rouan, Daniel; Sana, Hugues; Schaerer, Daniel; Telles, Eduardo; Trager, Scott; Tresse, Laurence; Welikala, Niraj; Zibetti, Stefano; Ziegler, Bodo

    2015-01-01

    This White Paper presents the scientific motivations for a multi-object spectrograph (MOS) on the European Extremely Large Telescope (E-ELT). The MOS case draws on all fields of contemporary astronomy, from extra-solar planets, to the study of the halo of the Milky Way and its satellites, and from resolved stellar populations in nearby galaxies out to observations of the earliest 'first-light' structures in the partially-reionised Universe. The material presented here results from thorough discussions within the community over the past four years, building on the past competitive studies to agree a common strategy toward realising a MOS capability on the E-ELT. The cases have been distilled to a set of common requirements which will be used to define the MOSAIC instrument, entailing two observational modes ('high multiplex' and 'high definition'). When combined with the unprecedented sensitivity of the E-ELT, MOSAIC will be the world's leading MOS facility. In analysing the requirements we also identify a hig...

  13. Commissioning COSMOS: Detection of Lithium in Young Stars in Lupus 3 through Multi-Object Spectroscopy

    Science.gov (United States)

    Lackey, Kyle; Briceno, Cesar; Elias, Jonathan H.

    2015-01-01

    COSMOS, a multi-object spectrograph and imager, is a new instrument on the Blanco 4-meter telescope at the Cerro Tololo Inter-American Observatory. In order to demonstrate the instrument's operations during commissioning, we used COSMOS, its red grism and three custom slit masks to conduct a spectroscopic survey of the star-forming core of the Lupus 3 dark cloud in an effort to detect the presence of Lithium in the T Tauri stars that have been previously identified in that region. We detected the Li I 6708 Angstrom resonance transition in several (but not all) stars that were observed, consistent with prior studies that have observed Lithium in other young stars at the center of the Lupus 3 dark cloud and in other star-forming regions. These results also demonstrate the ability of COSMOS to significantly reduce the time required to complete spectroscopic surveys, relative to single-object instruments.Lackey was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation Research Experiences for Undergraduates Program (AST-1262829).

  14. + 6 TEKSTER. KARTOGRAFI HYDRA 2013 #3

    DEFF Research Database (Denmark)

    Dinesen, Cort Ross

    2013-01-01

    +6 TEKSTER #3 indeholder en række indlæg, der er relateret til 14 NYE LANDSKABER/HYDRA 9, 2012 #1. Arbejdet med topologien og kartografien omkring tre urbane udsnit i Berlin, Paris og Tokyo har ført til en række udgivelser i GRID og følges op her med en række betragtninger, der perspektiverer denne...... at frembringe de baner, vi må tænke videre i. Denne serie af publikationer rummer også 10 NYE LANDSKABER/HYDRA 10 #2, 2013 og planlægges at blive fulgt op med et HYDRA 11 #4 i 2014. HYDRA refererer til en ø i Grækenland, der siden 2004 har dannet rammen om en sommerskole, der er optaget af KARTOGRAFI, MORFOLOGI...

  15. Gemini South Multi-Object Spectrograph (GMOS-S) detector Video boards upgrade: improved performance for the Hamamatsu CCDs.

    Science.gov (United States)

    Gimeno, German; Boucher, Luc; Chiboucas, Kristin; Hibon, Pascale; Lazo, Manuel; Murowinski, Richard; Rippa, Matthew; Rogers, Rolando; Rojas, Roberto; Roth, Katherine; White, John

    2016-01-01

    GMOS-S was upgraded with new Hamamatsu CCDs on June 2014, featuring an improved red sensitivity with respect to the previous detectors and significantly less fringing. Early after the commissioning, an issue was identified when observing in any of the binned readout modes, namely that saturated pixels produced a decrease of counts with respect to the bias level in neighboring pixels. This effect, also known as 'banding', spanned the entire width of the amplifier, and while it did not destroy information, it rendered data reduction very cumbersome. Making matters worse, due to the saturation of a bad column on amplifier number 5 (on CCD2, near the middle of the focal plane), it ended up affecting the entire amplifier for almost all exposures longer than a minute. A team of Gemini instrument scientists and engineers investigated the issue and identified the root cause of the problem as originated in the ARC controller video boards. After significant lab testing, it was verified that a newly available revision of the video boards would solve the problem, though modification of the software was required in order to be compatible with them. This work was performed during the last semester of 2014 and the first semester of 2015. The new video boards were installed and commissioned during August 2015. As of September 1st, the new boards are fully installed and integrated, and the 'banding' effect has been completely eliminated. A short period of time was devoted to the recharacterization of the detector system and the new values for the gains, read noise and full well capacity have been derived. As an added benefit, the full well was increased by ~ 10 percent with respect to the previous value. The GMOS-S new detectors are now operating normally in the Gemini observing queue, and performing at full capacity.

  16. Isolation of four novel neuropeptides, the hydra-RFamides I-IV, from Hydra magnipapillata

    DEFF Research Database (Denmark)

    Moosler, A; Rinehart, K L; Grimmelikhuijzen, C J

    1996-01-01

    Using a radioimmunoassay for the sequence Arg-Phe-NH2 (RFamide), we have isolated four novel peptides from extracts of Hydra magnipapillata:......Using a radioimmunoassay for the sequence Arg-Phe-NH2 (RFamide), we have isolated four novel peptides from extracts of Hydra magnipapillata:...

  17. Interleaving Guidance in Evolutionary Multi-Objective Optimization

    Institute of Scientific and Technical Information of China (English)

    Lam Thu Bui; Kalyanmoy Deb; Hussein A. Abbass; Daryl Essam

    2008-01-01

    In this paper, we propose a framework that uses localization for multi-objective optimization to simultaneously guide an evolutionary algorithm in both the decision and objective spaces. The localization is built using a limited number of adaptive spheres (local models) in the decision space. These spheres are usually guided, using some direction information, in the decision space towards the areas with non-dominated solutions. We use a second mechanism to adjust the spheres to specialize on different parts of the Pareto front by using a guided dominance technique in the objective space. Through this interleaved guidance in both spaces, the spheres will be guided towards different parts of the Pareto front while also exploring the decision space efficiently. The experimental results showed good performance for the local models using this dual guidance, in comparison with their original version.

  18. Genetic Algorithms Applied to Multi-Objective Aerodynamic Shape Optimization

    Science.gov (United States)

    Holst, Terry L.

    2005-01-01

    A genetic algorithm approach suitable for solving multi-objective problems is described and evaluated using a series of aerodynamic shape optimization problems. Several new features including two variations of a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding Pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. A new masking array capability is included allowing any gene or gene subset to be eliminated as decision variables from the design space. This allows determination of the effect of a single gene or gene subset on the Pareto optimal solution. Results indicate that the genetic algorithm optimization approach is flexible in application and reliable. The binning selection algorithms generally provide Pareto front quality enhancements and moderate convergence efficiency improvements for most of the problems solved.

  19. Well Field Management Using Multi-Objective Optimization

    DEFF Research Database (Denmark)

    Hansen, Annette Kirstine; Hendricks Franssen, H. J.; Bauer-Gottwein, Peter

    2013-01-01

    Efficient management of groundwater resources is important because groundwater availability is limited and, locally, groundwater quality has been impaired because of contamination. Here we present a multi-objective optimization framework for improving the management of a water works that operates...... with infiltration basins, injection wells and abstraction wells. The two management objectives are to minimize the amount of water needed for infiltration and to minimize the risk of getting contaminated water into the drinking water wells. The management is subject to a daily demand fulfilment constraint. Two...... optimization results are presented for the Hardhof water works in Zurich, Switzerland. It is found that both methods perform better than the historical management. The constant scheduling performs best in fairly stable conditions, whereas the sequential optimization performs best in extreme situations...

  20. A Multi-Objective Genetic Algorithm for Optimal Portfolio Problems

    Institute of Scientific and Technical Information of China (English)

    林丹; 赵瑞

    2004-01-01

    This paper concerns with modeling and design of an algorithm for the portfolio selection problems with fixed transaction costs and minimum transaction lots. A mean-variance model for the portfolio selection problem is proposed, and the model is formulated as a non-smooth and nonlinear integer programming problem with multiple objective functions. As it has been proven that finding a feasible solution to the problem only is already NP-hard, based on NSGA-II and genetic algorithm for numerical optimization of constrained problems (Genocop), a multi-objective genetic algorithm (MOGA) is designed to solve the model. Its features comprise integer encoding and corresponding operators, and special treatment of constraints conditions. It is illustrated via a numerical example that the genetic algorithm can efficiently solve portfolio selection models proposed in this paper. This approach offers promise for the portfolio problems in practice.

  1. 2000 fps multi-object tracking based on color histogram

    Science.gov (United States)

    Gu, Qingyi; Takaki, Takeshi; Ishii, Idaku

    2012-06-01

    In this study, we develop a real-time, color histogram-based tracking system for multiple color-patterned objects in a 512×512 image at 2000 fps. Our system can simultaneously extract the positions, areas, orientation angles, and color histograms of multiple objects in an image using the hardware implementation of a multi-object, color histogram extraction circuit module on a high-speed vision platform. It can both label multiple objects in an image consisting of connected components and calculate their moment features and 16-bin hue-based color histograms using cell-based labeling. We demonstrate the performance of our system by showing several experimental results: (1) tracking of multiple color-patterned objects on a plate rotating at 16 rps, and (2) tracking of human hand movement with two color-patterned drinking bottles.

  2. MOOPPS: An Optimization System for Multi Objective Scheduling

    CERN Document Server

    Geiger, Martin Josef

    2008-01-01

    In the current paper, we present an optimization system solving multi objective production scheduling problems (MOOPPS). The identification of Pareto optimal alternatives or at least a close approximation of them is possible by a set of implemented metaheuristics. Necessary control parameters can easily be adjusted by the decision maker as the whole software is fully menu driven. This allows the comparison of different metaheuristic algorithms for the considered problem instances. Results are visualized by a graphical user interface showing the distribution of solutions in outcome space as well as their corresponding Gantt chart representation. The identification of a most preferred solution from the set of efficient solutions is supported by a module based on the aspiration interactive method (AIM). The decision maker successively defines aspiration levels until a single solution is chosen. After successfully competing in the finals in Ronneby, Sweden, the MOOPPS software has been awarded the European Academ...

  3. Multi-object fixed delay Michelson interferometer for astronomical observation

    Science.gov (United States)

    Zhang, Kai; Zhu, Yongtian; Wang, Lei; Chen, Yi; Wang, Liang

    2012-10-01

    Optical interferometry isn't only widely applied into optical workshop, but also makes great contribution in astronomical observation. A multi-object fixed delay Michelson interferometer commissioned to search extra-solar planet (exoplanet) is introduced here. Fixed delay of 1.9mm, which is good for stellar radial velocity measuring precision, is obtained by two interference arms with different materials. This configuration has different refractive indexes and physical characteristics so that supplies wider field of view and better thermal stability. In addition, compact interference component with three glued prisms and smart structure are the other important features. Because of vibration influence, the combination among the prisms is a direct and effective method. And the reason why make the structure as small as possible is of central obscuration under the workspace of interferometer.

  4. 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)

  5. SAPA: A Multi-objective Metric Temporal Planner

    CERN Document Server

    Do, M; 10.1613/jair.1156

    2011-01-01

    SAPA is a domain-independent heuristic forward chaining planner that can handle durative actions, metric resource constraints, and deadline goals. It is designed to be capable of handling the multi-objective nature of metric temporal planning. Our technical contributions include (i) planning-graph based methods for deriving heuristics that are sensitive to both cost and makespan (ii) techniques for adjusting the heuristic estimates to take action interactions and metric resource limitations into account and (iii) a linear time greedy post-processing technique to improve execution flexibility of the solution plans. An implementation of SAPA using many of the techniques presented in this paper was one of the best domain independent planners for domains with metric and temporal constraints in the third International Planning Competition, held at AIPS-02. We describe the technical details of extracting the heuristics and present an empirical evaluation of the current implementation of SAPA.

  6. 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

  7. 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

  8. Replicated Spectrographs in Astronomy

    CERN Document Server

    Hill, Gary J

    2014-01-01

    As telescope apertures increase, the challenge of scaling spectrographic astronomical instruments becomes acute. The next generation of extremely large telescopes (ELTs) strain the availability of glass blanks for optics and engineering to provide sufficient mechanical stability. While breaking the relationship between telescope diameter and instrument pupil size by adaptive optics is a clear path for small fields of view, survey instruments exploiting multiplex advantages will be pressed to find cost-effective solutions. In this review we argue that exploiting the full potential of ELTs will require the barrier of the cost and engineering difficulty of monolithic instruments to be broken by the use of large-scale replication of spectrographs. The first steps in this direction have already been taken with the soon to be commissioned MUSE and VIRUS instruments for the Very Large Telescope and the Hobby-Eberly Telescope, respectively. MUSE employs 24 spectrograph channels, while VIRUS has 150 channels. We compa...

  9. Immersion echelle spectrograph

    Science.gov (United States)

    Stevens, Charles G.; Thomas, Norman L.

    2000-01-01

    A small spectrograph containing no moving components and capable of providing high resolution spectra of the mid-infrared region from 2 microns to 4 microns in wavelength. The resolving power of the spectrograph exceeds 20,000 throughout this region and at an optical throughput of about 10.sup.-5 cm.sup.2 sr. The spectrograph incorporates a silicon immersion echelle grating operating in high spectral order combined with a first order transmission grating in a cross-dispersing configuration to provide a two-dimensional (2-D) spectral format that is focused onto a two-dimensional infrared detector array. The spectrometer incorporates a common collimating and condensing lens assembly in a near aberration-free axially symmetric design. The spectrometer has wide use potential in addition to general research, such as monitoring atmospheric constituents for air quality, climate change, global warming, as well as monitoring exhaust fumes for smog sources or exhaust plumes for evidence of illicit drug manufacture.

  10. Hydra constitutively expresses transcripts involved in vertebrate neural differentiation

    Indian Academy of Sciences (India)

    Sandipan Chatterjee; Shweta Lahudkar; N N Godbole; Surendra Ghaskadbi

    2001-06-01

    The diploblastic Hydra is among the most primitive multicellular organisms. Using cross-hybridization with Xenopus probes, noggin-like transcripts were detected in the hypostome and basal disc of adult Hydra (Pelmatohydra oligactis), regions with properties similar to that of the amphibian organizer. This points to the possibility of a close molecular similarity between the Xenopus and Hydra organizers. The constitutive expression of a noggin-like gene in Hydra may be responsible for its regenerative capacity.

  11. 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

  12. The real-time control system for the CANARY multi-object adaptive optics on-sky demonstrator

    Science.gov (United States)

    Dipper, N. A.; Basden, A.; Looker, N. E.; Gendron, E.; Geng, D.; Gratadour, D.; Hubert, Z.; Vidal, F.; Myers, R. M.; Rousset, G.; Sevin, A.; Younger, E. J.

    2010-07-01

    CANARY is a Multi-Object Adaptive Optics (MOAO) system designed to demonstrate the AO aspects of proposed EELT instruments such as the multi-object spectrograph EAGLE. The first phase of Canary will be executed on the 4.2m William Herschel Telescope in 2010. We describe here the AO Real-time Control System (RTCS) for Canary. This is based on a distributed architecture of components interconnected by a fast serial fabric (sFPDP). The hardware used is a hybrid of FPGA and CPU technology. The middleware used for system data telemetry and control is based on CORBA and the publish/subscribe pattern. The system is designed to be easily modified and extended for the later, higher order, phases of CANARY. In order to provide the increase in computational power required in higher order systems, the current CPU technology can be readily replaced by acceleration hardware based on FPGA or GPU technologies. The Canary RTCS thus provides a test-bed for these new technologies that will be required for E-ELT instruments. These design concepts can be developed to provide an RTCS for E-ELT instruments and are in line with those under consideration by ESO for the E-ELT AO systems to which instruments such as EAGLE will be required to interface.

  13. Generation of Transgenic Hydra by Embryo Microinjection

    Science.gov (United States)

    Juliano, Celina E.; Lin, Haifan; Steele, Robert E.

    2014-01-01

    As a member of the phylum Cnidaria, the sister group to all bilaterians, Hydra can shed light on fundamental biological processes shared among multicellular animals. Hydra is used as a model for the study of regeneration, pattern formation, and stem cells. However, research efforts have been hampered by lack of a reliable method for gene perturbations to study molecular function. The development of transgenic methods has revitalized the study of Hydra biology1. Transgenic Hydra allow for the tracking of live cells, sorting to yield pure cell populations for biochemical analysis, manipulation of gene function by knockdown and over-expression, and analysis of promoter function. Plasmid DNA injected into early stage embryos randomly integrates into the genome early in development. This results in hatchlings that express transgenes in patches of tissue in one or more of the three lineages (ectodermal epithelial, endodermal epithelial, or interstitial). The success rate of obtaining a hatchling with transgenic tissue is between 10% and 20%. Asexual propagation of the transgenic hatchling is used to establish a uniformly transgenic line in a particular lineage. Generating transgenic Hydra is surprisingly simple and robust, and here we describe a protocol that can be easily implemented at low cost. PMID:25285460

  14. A Multi-Objective Genetic Algorithm for Outlier Removal.

    Science.gov (United States)

    Nahum, Oren E; Yosipof, Abraham; Senderowitz, Hanoch

    2015-12-28

    Quantitative structure activity relationship (QSAR) or quantitative structure property relationship (QSPR) models are developed to correlate activities for sets of compounds with their structure-derived descriptors by means of mathematical models. The presence of outliers, namely, compounds that differ in some respect from the rest of the data set, compromise the ability of statistical methods to derive QSAR models with good prediction statistics. Hence, outliers should be removed from data sets prior to model derivation. Here we present a new multi-objective genetic algorithm for the identification and removal of outliers based on the k nearest neighbors (kNN) method. The algorithm was used to remove outliers from three different data sets of pharmaceutical interest (logBBB, factor 7 inhibitors, and dihydrofolate reductase inhibitors), and its performances were compared with those of five other methods for outlier removal. The results suggest that the new algorithm provides filtered data sets that (1) better maintain the internal diversity of the parent data sets and (2) give rise to QSAR models with much better prediction statistics. Equally good filtered data sets in terms of these metrics were obtained when another objective function was added to the algorithm (termed "preservation"), forcing it to remove certain compounds with low probability only. This option is highly useful when specific compounds should be preferably kept in the final data set either because they have favorable activities or because they represent interesting molecular scaffolds. We expect this new algorithm to be useful in future QSAR applications.

  15. Determination of Pareto frontier in multi-objective maintenance optimization

    Energy Technology Data Exchange (ETDEWEB)

    Certa, Antonella [Dipartimento di Tecnologia Meccanica, Produzione e Ingegneria Gestionale, Universita di Palermo 90128 Palermo (Italy); Galante, Giacomo, E-mail: galante@dtpm.unipa.i [Dipartimento di Tecnologia Meccanica, Produzione e Ingegneria Gestionale, Universita di Palermo 90128 Palermo (Italy); Lupo, Toni; Passannanti, Gianfranco [Dipartimento di Tecnologia Meccanica, Produzione e Ingegneria Gestionale, Universita di Palermo 90128 Palermo (Italy)

    2011-07-15

    The objective of a maintenance policy generally is the global maintenance cost minimization that involves not only the direct costs for both the maintenance actions and the spare parts, but also those ones due to the system stop for preventive maintenance and the downtime for failure. For some operating systems, the failure event can be dangerous so that they are asked to operate assuring a very high reliability level between two consecutive fixed stops. The present paper attempts to individuate the set of elements on which performing maintenance actions so that the system can assure the required reliability level until the next fixed stop for maintenance, minimizing both the global maintenance cost and the total maintenance time. In order to solve the previous constrained multi-objective optimization problem, an effective approach is proposed to obtain the best solutions (that is the Pareto optimal frontier) among which the decision maker will choose the more suitable one. As well known, describing the whole Pareto optimal frontier generally is a troublesome task. The paper proposes an algorithm able to rapidly overcome this problem and its effectiveness is shown by an application to a case study regarding a complex series-parallel system.

  16. Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning

    Science.gov (United States)

    Englander, Jacob

    2015-01-01

    Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. Because low-thrust trajectory design is tightly coupled with systems design, power and propulsion characteristics must be chosen as well. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The methods is demonstrated on hypothetical mission to the main asteroid belt and to Deimos.

  17. 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.

  18. A Multi-objective Procedure for Efficient Regression Modeling

    CERN Document Server

    Sinha, Ankur; Kuosmanen, Timo

    2012-01-01

    Variable selection is recognized as one of the most critical steps in statistical modeling. The problems encountered in engineering and social sciences are commonly characterized by over-abundance of explanatory variables, non-linearities and unknown interdependencies between the regressors. An added difficulty is that the analysts may have little or no prior knowledge on the relative importance of the variables. To provide a robust method for model selection, this paper introduces a technique called the Multi-objective Genetic Algorithm for Variable Selection (MOGA-VS) which provides the user with an efficient set of regression models for a given data-set. The algorithm considers the regression problem as a two objective task, where the purpose is to choose those models over the other which have less number of regression coefficients and better goodness of fit. In MOGA-VS, the model selection procedure is implemented in two steps. First, we generate the frontier of all efficient or non-dominated regression m...

  19. Multi-objective optimization of aerostructures inspired by nature

    Science.gov (United States)

    Kearney, Adam C.

    The focus of this doctoral work is on the optimization of aircraft wing structures. The optimization was performed against the shape, size and topology of simple aircraft wing designs. A simple morphing wing actuator optimization is performed as well as a wing panel buckling topology optimization. This is done with biologically-inspired mathematical systems including a map L-system, a multi-objective genetic algorithm, and cellular structures represented by Voronoi diagrams. As with most aircraft optimizations, both studies aim to minimize the total weight of a wing while simultaneously meeting stiffness and strength requirements. Optimization is performed with the scripts developed in MATLAB as well as through the use of finite element codes, NASTRAN and LS-Dyna. The intent of this methodology is to develop unique designs inspired by nature and optimized through natural selection. The optimal designs are those with minimal weight as well as additional requirements specific to the problems. The designs and methodology have the potential to be of use in determining minimum weight designs in aircraft structures. A literature review of optimization techniques, methodology and method validation, and optimization comparisons is presented. The buckling panel optimization considered here also includes composite buckling failure and manufacturing assumptions for composite panels. The panels are optimized for mass and strength by controlling the laminate stacking sequence, stiffener size, and topology. The morphing wing is optimized for actuator loading and redundancy.

  20. Monocular visual scene understanding: understanding multi-object traffic scenes.

    Science.gov (United States)

    Wojek, Christian; Walk, Stefan; Roth, Stefan; Schindler, Konrad; Schiele, Bernt

    2013-04-01

    Following recent advances in detection, context modeling, and tracking, scene understanding has been the focus of renewed interest in computer vision research. This paper presents a novel probabilistic 3D scene model that integrates state-of-the-art multiclass object detection, object tracking and scene labeling together with geometric 3D reasoning. Our model is able to represent complex object interactions such as inter-object occlusion, physical exclusion between objects, and geometric context. Inference in this model allows us to jointly recover the 3D scene context and perform 3D multi-object tracking from a mobile observer, for objects of multiple categories, using only monocular video as input. Contrary to many other approaches, our system performs explicit occlusion reasoning and is therefore capable of tracking objects that are partially occluded for extended periods of time, or objects that have never been observed to their full extent. In addition, we show that a joint scene tracklet model for the evidence collected over multiple frames substantially improves performance. The approach is evaluated for different types of challenging onboard sequences. We first show a substantial improvement to the state of the art in 3D multipeople tracking. Moreover, a similar performance gain is achieved for multiclass 3D tracking of cars and trucks on a challenging dataset.

  1. Multi-Objective Optimization of A PCHE Channels

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Sang Moon; Kim, Kwang Yong [Inha University, Incheon (Korea, Republic of)

    2011-10-15

    High-temperature, gas-cooled nuclear reactors with a closed gas turbine cycle are recently being considered as a nuclear power generation concept for the future. In theory, the gas turbine cycle has an advantage in terms of simplicity and efficiency compared to the steam turbine cycle. However, since gas is used as the working fluid, inefficiency due to large volumes is inevitable, and a heat exchanger is used as a recuperator and pre-cooler. To solve this problem, different types of heat exchanger are needed. One of the alternative heat exchangers is the printed circuit heat exchanger (PCHE) developed by HEATRIC. Each flow channel of the PCHE is made through chemical etching on the surface of metal plates, and the typical PCHE channels on each plate have a zigzag shape to promote the heat transfer between the cold and hot channels. In this work, the zigzag flow channels of the PCHE have been optimized by using three-dimensional RANS analysis and a hybrid multi-objective evolutionary algorithm coupled with the RSA model. The cold channel angle and the ellipse aspect ratio of the cold channel are employed as the design variables. A group of optimal shapes are presented through Paretooptimal front (POF) by an {epsilon}-constraint strategy through an NSGA-II algorithm

  2. Multi-objective evolutionary algorithm for operating parallel reservoir system

    Science.gov (United States)

    Chang, Li-Chiu; Chang, Fi-John

    2009-10-01

    SummaryThis paper applies a multi-objective evolutionary algorithm, the non-dominated sorting genetic algorithm (NSGA-II), to examine the operations of a multi-reservoir system in Taiwan. The Feitsui and Shihmen reservoirs are the most important water supply reservoirs in Northern Taiwan supplying the domestic and industrial water supply needs for over 7 million residents. A daily operational simulation model is developed to guide the releases of the reservoir system and then to calculate the shortage indices (SI) of both reservoirs over a long-term simulation period. The NSGA-II is used to minimize the SI values through identification of optimal joint operating strategies. Based on a 49 year data set, we demonstrate that better operational strategies would reduce shortage indices for both reservoirs. The results indicate that the NSGA-II provides a promising approach. The pareto-front optimal solutions identified operational compromises for the two reservoirs that would be expected to improve joint operations.

  3. Adaptive surrogate model based multi-objective transfer trajectory optimization between different libration points

    Science.gov (United States)

    Peng, Haijun; Wang, Wei

    2016-10-01

    An adaptive surrogate model-based multi-objective optimization strategy that combines the benefits of invariant manifolds and low-thrust control toward developing a low-computational-cost transfer trajectory between libration orbits around the L1 and L2 libration points in the Sun-Earth system has been proposed in this paper. A new structure for a multi-objective transfer trajectory optimization model that divides the transfer trajectory into several segments and gives the dominations for invariant manifolds and low-thrust control in different segments has been established. To reduce the computational cost of multi-objective transfer trajectory optimization, a mixed sampling strategy-based adaptive surrogate model has been proposed. Numerical simulations show that the results obtained from the adaptive surrogate-based multi-objective optimization are in agreement with the results obtained using direct multi-objective optimization methods, and the computational workload of the adaptive surrogate-based multi-objective optimization is only approximately 10% of that of direct multi-objective optimization. Furthermore, the generating efficiency of the Pareto points of the adaptive surrogate-based multi-objective optimization is approximately 8 times that of the direct multi-objective optimization. Therefore, the proposed adaptive surrogate-based multi-objective optimization provides obvious advantages over direct multi-objective optimization methods.

  4. Target irradiation experiments. [Hydra accelerator

    Energy Technology Data Exchange (ETDEWEB)

    1976-01-01

    Target irradiation experiments have been carried out on the Hydra accelerator, operating at powers between 0.15 and 0.3 TW. As listed in Table I, four types of spherical shell targets have been studied: 3 mm diameter, 200 ..mu..m and 50 ..mu..m wall thickness Au targets; 3 mm diameter, 300 ..mu..m wall thickness plastic targets; and 0.85 mm diameter, 10 ..mu..m wall thickness Ni targets. When compared to a practical range for 700 keV electrons, the ratio of shell thickness to electron range varied between 0.03 for the Ni targets to 1.5 for the thick walled Au targets. Multiple exposure optical holography was utilized to determine ablator velocity, and a one-dimensional hydrodynamical materials code CHARTD was utilized to model target response and infer beam deposition. Energy deposition varied from 1 TW/gm for thick Au targets up to 8 TW/gm for thin Ni targets, and pusher velocities ranged between 0.5 and 3.5 cm/..mu..sec. Neutron production from D/sub 2/ and DT filled Ni exploding pusher targets was measured using Ag and Li activation counters and gated scintillator photomultiplier time of flight detectors.

  5. The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST)

    Institute of Scientific and Technical Information of China (English)

    Xiang-Qun Cui; Xiao-Zheng Xing; Xin-Nan Li; Yong-Tian Zhu; Gang Wang; Bo-Zhong Gu; A-Li Luo; Xin-Qi Xu; Zhen-Chao Zhang; Gen-Rong Liu; Hao-Tong Zhang; Yong-Heng Zhao; De-Hua Yang; Shu-Yun Cao; Hai-Yuan Chen; Jian-Jun Chen; Kun-Xin Chen; Ying Chen; Jia-Ru Chu; Lei Feng; Xue-Fei Gong; Yong-Hui Hou; Yao-Quan Chu; Hong-Zhuan Hu; Ning-Sheng Hu; Zhong-Wen Hu; Lei Jia; Fang-Hua Jiang; Xiang Jiang; Zi-Bo Jiang; Ge Jin; Ai-Hua Li; Yan Li; Guo-Ping Li; Ye-Ping Li; Guan-Qun Liu; Zhi-Gang Liu; Wen-Zhi Lu; Yin-Dun Mao; Li Men; Yong-Jun Qi; Zhao-Xiang Qi; Huo-Ming Shi; Zheng-Hong Tang; Qi Li; Qing-Sheng Tao; Da-Qi Wang; Dan Wang; Guo-Min Wang; Hai Wang; Jia-Ning Wang; Jian Wang; Jian-Ling Wang; Jian-Ping Wang; Lei Wang; Li-Ping Zhang; Shu-Qing Wang; You Wang; Yue-Fei Wang; Ling-Zhe Xu; Yan Xu; Shi-Hai Yang; Yong Yu; Hui Yuan; Xiang-Yan Yuan; Chao Zhai; Hong-Jun Su; Jing Zhang; Yan-Xia Zhang; Yong Zhang; Ming Zhao; Fang Zhou; Guo-Hua Zhou; Jie Zhu; Si-Cheng Zou; Zheng-Qiu Yao; Ya-Nan Wang

    2012-01-01

    The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST,also called the Guo Shou Jing Telescope) is a special reflecting Schmidt telescope.LAMOST's special design allows both a large aperture (effective aperture of 3.6m-4.9m) and a wide field of view (FOV) (5°).It has an innovative active reflecting Schmidt configuration which continuously changes the mirror's surface that adjusts during the observation process and combines thin deformable mirror active optics with segmented active optics.Its primary mirror (6.67 m ×6.05 m) and active Schmidt mirror (5.74m×4.40m) are both segmented,and composed of 37 and 24 hexagonal sub-mirrors respectively.By using a parallel controllable fiber positioning technique,the focal surface of 1.75 m in diameter can accommodate 4000 optical fibers.Also,LAMOST has 16 spectrographs with 32 CCD cameras.LAMOST will be the telescope with the highest rate of spectral acquisition.As a national large scientific project,the LAMOST project was formally proposed in 1996,and approved by the Chinese government in 1997.The construction started in 2001,was completed in 2008 and passed the official acceptance in June 2009.The LAMOST pilot survey was started in October 2011 and the spectroscopic survey will launch in September 2012.Up to now,LAMOST has released more than 480 000 spectra of objects.LAMOST will make an important contribution to the study of the large-scale structure of the Universe,structure and evolution of the Galaxy,and cross-identification of multiwaveband properties in celestial objects.

  6. 4MOST low-resolution spectrograph: design and performances

    Science.gov (United States)

    Laurent, F.; Kosmalski, Johan; Boudon, Didier; Caillier, Patrick; Daguisé, Eric; Migniau, Jean-Emmanuel; Pécontal, Arlette; Richard, Johan; Barden, Samuel C.; Bellido-Tirado, Olga; Frey, Steffen; Saviauk, Allar

    2016-08-01

    4MOST, the 4m Multi Object Spectroscopic Telescope, is an upcoming optical, fibre-fed, MOS facility for the VISTA telescope at ESO's Paranal Observatory in Chile. Its main science drivers are in the fields of galactic archeology, highenergy physics, galaxy evolution and cosmology. The preliminary design of 4MOST features 2436 fibres split into lowresolution (1624 fibres, 370-950 nm, R > 4000) and high-resolution spectrographs (812 fibres, three arms, 44-69 nm coverage each, R >18000) with a fibre positioner and covering an hexagonal field of view of 4.1 deg2. The 4MOST consortium consists of several institutes in Europe and Australia under leadership of the Leibniz-Institut für Astrophysik, Potsdam (AIP). 4MOST is currently in its Preliminary Design Phase with an expected start of science operations in 2021. Two third of fibres go to two Low Resolution Spectrographs with three channels per spectrograph. Each low resolution spectrograph is composed of 812 scientific and 10 calibration fibres using 85μm core fibres at f/3, a 200mm beam for an off-axis collimator associated to its Schmidt corrector, 3 arms with f/1.73 cameras and standard 6k x 6k 15μm pixel detectors. CRAL has the responsibility of the Low Resolution Spectrographs. In this paper, the optical design and performances of 4MOST Low Resolution Spectrograph designed for 4MOST PDR in June, 2016 will be presented. Special emphasis will be put on the Low Resolution Spectrograph system budget and performance analysis.

  7. Joint Geophysical Inversion With Multi-Objective Global Optimization Methods

    Science.gov (United States)

    Lelievre, P. G.; Bijani, R.; Farquharson, C. G.

    2015-12-01

    Pareto multi-objective global optimization (PMOGO) methods generate a suite of solutions that minimize multiple objectives (e.g. data misfits and regularization terms) in a Pareto-optimal sense. Providing a suite of models, as opposed to a single model that minimizes a weighted sum of objectives, allows a more complete assessment of the possibilities and avoids the often difficult choice of how to weight each objective. We are applying PMOGO methods to three classes of inverse problems. The first class are standard mesh-based problems where the physical property values in each cell are treated as continuous variables. The second class of problems are also mesh-based but cells can only take discrete physical property values corresponding to known or assumed rock units. In the third class we consider a fundamentally different type of inversion in which a model comprises wireframe surfaces representing contacts between rock units; the physical properties of each rock unit remain fixed while the inversion controls the position of the contact surfaces via control nodes. This third class of problem is essentially a geometry inversion, which can be used to recover the unknown geometry of a target body or to investigate the viability of a proposed Earth model. Joint inversion is greatly simplified for the latter two problem classes because no additional mathematical coupling measure is required in the objective function. PMOGO methods can solve numerically complicated problems that could not be solved with standard descent-based local minimization methods. This includes the latter two classes of problems mentioned above. There are significant increases in the computational requirements when PMOGO methods are used but these can be ameliorated using parallelization and problem dimension reduction strategies.

  8. Multi-objective vs. single-objective calibration of a hydrologic model using single- and multi-objective screening

    Science.gov (United States)

    Mai, Juliane; Cuntz, Matthias; Shafii, Mahyar; Zink, Matthias; Schäfer, David; Thober, Stephan; Samaniego, Luis; Tolson, Bryan

    2016-04-01

    Hydrologic models are traditionally calibrated against observed streamflow. Recent studies have shown however, that only a few global model parameters are constrained using this kind of integral signal. They can be identified using prior screening techniques. Since different objectives might constrain different parameters, it is advisable to use multiple information to calibrate those models. One common approach is to combine these multiple objectives (MO) into one single objective (SO) function and allow the use of a SO optimization algorithm. Another strategy is to consider the different objectives separately and apply a MO Pareto optimization algorithm. In this study, two major research questions will be addressed: 1) How do multi-objective calibrations compare with corresponding single-objective calibrations? 2) How much do calibration results deteriorate when the number of calibrated parameters is reduced by a prior screening technique? The hydrologic model employed in this study is a distributed hydrologic model (mHM) with 52 model parameters, i.e. transfer coefficients. The model uses grid cells as a primary hydrologic unit, and accounts for processes like snow accumulation and melting, soil moisture dynamics, infiltration, surface runoff, evapotranspiration, subsurface storage and discharge generation. The model is applied in three distinct catchments over Europe. The SO calibrations are performed using the Dynamically Dimensioned Search (DDS) algorithm with a fixed budget while the MO calibrations are achieved using the Pareto Dynamically Dimensioned Search (PA-DDS) algorithm allowing for the same budget. The two objectives used here are the Nash Sutcliffe Efficiency (NSE) of the simulated streamflow and the NSE of the logarithmic transformation. It is shown that the SO DDS results are located close to the edges of the Pareto fronts of the PA-DDS. The MO calibrations are hence preferable due to their supply of multiple equivalent solutions from which the

  9. Optical design of a multi-resolution, single shot spectrograph

    CERN Document Server

    Henault, Francois

    2016-01-01

    Multi-object or integral field spectrographs are recognized techniques for achieving simultaneous spectroscopic observations of different or extended sky objects with a high multiplex factor. In this communication is described a complementary approach for realizing similar measurements under different spectral resolutions at the same time. We describe the basic principle of this new type of spectrometer, that is based on the utilization of an optical pupil slicer. An optical design inspired from an already studied instrument is then presented and commented for the sake of illustration. Technical issues about the pupil slicer and diffractive components are also discussed. We finally conclude on the potential advantages and drawbacks of the proposed system.

  10. Fiber Assignment in Next-generation Wide-field Spectrographs

    OpenAIRE

    Morales, Isaac; Montero-Dorta, Antonio D.; Azzaro, Marco; Prada, Francisco; Sanchez, Justo; Becerril, Santiago

    2011-01-01

    We present an optimized algorithm for assigning fibers to targets in next-generation fiber-fed multi-object spectrographs. The method, that we named draining algorithm, ensures that the maximum number of targets in a given target field is observed in the first few tiles. Using randomly distributed targets and mock galaxy catalogs we have estimated that the gain provided by the draining algorithm as compared to a random assignment can be as much as 2% for the first tiles. This would imply for ...

  11. Data reduction pipeline for the MMT Magellan Infrared Spectrograph

    CERN Document Server

    Chilingarian, Igor; Fabricant, Daniel; McLeod, Brian; Roll, John; Szentgyorgyi, Andrew

    2012-01-01

    We describe principal components of the new spectroscopic data pipeline for the multi-object MMT/Magellan Infrared Spectrograph (MMIRS). The pipeline is implemented in IDL and C++. The performance of the data processing algorithms is sufficient to reduce a single dataset in 2--3 min on a modern PC workstation so that one can use the pipeline as a quick-look tool during observations. We provide an example of the spectral data processed by our pipeline and demonstrate that the sky subtraction quality gets close to the limits set by the Poisson photon statistics.

  12. Geophysical Inversion With Multi-Objective Global Optimization Methods

    Science.gov (United States)

    Lelièvre, Peter; Bijani, Rodrigo; Farquharson, Colin

    2016-04-01

    We are investigating the use of Pareto multi-objective global optimization (PMOGO) methods to solve numerically complicated geophysical inverse problems. PMOGO methods can be applied to highly nonlinear inverse problems, to those where derivatives are discontinuous or simply not obtainable, and to those were multiple minima exist in the problem space. PMOGO methods generate a suite of solutions that minimize multiple objectives (e.g. data misfits and regularization terms) in a Pareto-optimal sense. This allows a more complete assessment of the possibilities and provides opportunities to calculate statistics regarding the likelihood of particular model features. We are applying PMOGO methods to four classes of inverse problems. The first are discrete-body problems where the inversion determines values of several parameters that define the location, orientation, size and physical properties of an anomalous body represented by a simple shape, for example a sphere, ellipsoid, cylinder or cuboid. A PMOGO approach can determine not only the optimal shape parameters for the anomalous body but also the optimal shape itself. Furthermore, when one expects several anomalous bodies in the subsurface, a PMOGO inversion approach can determine an optimal number of parameterized bodies. The second class of inverse problems are standard mesh-based problems where the physical property values in each cell are treated as continuous variables. The third class of problems are lithological inversions, which are also mesh-based but cells can only take discrete physical property values corresponding to known or assumed rock units. In the fourth class, surface geometry inversions, we consider a fundamentally different type of problem in which a model comprises wireframe surfaces representing contacts between rock units. The physical properties of each rock unit remain fixed while the inversion controls the position of the contact surfaces via control nodes. Surface geometry inversion can be

  13. Valuing hydrological alteration in Multi-Objective reservoir management

    Science.gov (United States)

    Bizzi, S.; Pianosi, F.; Soncini-Sessa, R.

    2012-04-01

    Water management through dams and reservoirs is worldwide necessary to support key human-related activities ranging from hydropower production to water allocation for agricultural production, and flood risk mitigation. Advances in multi-objectives (MO) optimization techniques and ever growing computing power make it possible to design reservoir operating policies that represent Pareto-optimal tradeoffs between the multiple interests analysed. These progresses if on one hand are likely to enhance performances of commonly targeted objectives (such as hydropower production or water supply), on the other risk to strongly penalize all the interests not directly (i.e. mathematically) optimized within the MO algorithm. Alteration of hydrological regime, although is a well established cause of ecological degradation and its evaluation and rehabilitation are commonly required by recent legislation (as the Water Framework Directive in Europe), is rarely embedded as an objective in MO planning of optimal releases from reservoirs. Moreover, even when it is explicitly considered, the criteria adopted for its evaluation are doubted and not commonly trusted, undermining the possibility of real implementation of environmentally friendly policies. The main challenges in defining and assessing hydrological alterations are: how to define a reference state (referencing); how to define criteria upon which to build mathematical indicators of alteration (measuring); and finally how to aggregate the indicators in a single evaluation index that can be embedded in a MO optimization problem (valuing). This paper aims to address these issues by: i) discussing benefits and constrains of different approaches to referencing, measuring and valuing hydrological alteration; ii) testing two alternative indices of hydrological alteration in the context of MO problems, one based on the established framework of Indices of Hydrological Alteration (IHA, Richter et al., 1996), and a novel satisfying the

  14. Evo-devo: Hydra raises its Noggin

    Indian Academy of Sciences (India)

    Kalpana Chandramore; Surendra Ghaskadbi

    2011-08-01

    Noggin, along with other secreted bone morphogenetic protein (BMP) inhibitors, plays a crucial role in neural induction and neural tube patterning as well as in somitogenesis, cardiac morphogenesis and formation of the skeleton in vertebrates. The BMP signalling pathway is one of the seven fundamental pathways that drive embryonic development and pattern formation in animals. Understanding its evolutionary origin and role in pattern formation is, therefore, important to evolutionary developmental biology (evo-devo).We have studied the evolutionary origin of BMP–Noggin antagonism in hydra, which is a powerful diploblastic model to study evolution of pattern-forming mechanisms because of the unusual cellular dynamics during its pattern formation and its remarkable ability to regenerate. We cloned and characterized the noggin gene from hydra and found it to exhibit considerable similarity with its orthologues at the amino acid level. Microinjection of hydra Noggin mRNA led to duplication of the dorsoventral axis in Xenopus embryos, demonstrating its functional conservation across the taxa. Our data, along with those of others, indicate that the evolutionarily conserved antagonism between BMP and its inhibitors predates bilateral divergence. This article reviews the various roles of Noggin in different organisms and some of our recent work on hydra Noggin in the context of evolution of developmental signalling pathways.

  15. The Hydra-k Partial Fields

    NARCIS (Netherlands)

    R. Pendavingh; S.H.M. van Zwam (Stefan)

    2010-01-01

    htmlabstractIn the paper "Confinement of matroid representations to subsets of partial fields" (arXiv:0806.4487) we introduced the Hydra-k partial fields to study quinary matroids with inequivalent representations. The proofs of some results on these partial fields require extensive computations.

  16. 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...

  17. CCD Readout Electronics for the Subaru Prime Focus Spectrograph

    CERN Document Server

    Hope, Stephen C; Loomis, Craig P; Fitzgerald, Roger E; Peacock, Grant O

    2014-01-01

    We present details of the design for the CCD readout electronics for the Subaru Telescope Prime Focus Spectrograph (PFS). The spectrograph is comprised of four identical spectrograph modules, each collecting roughly 600 spectra. The spectrograph modules provide simultaneous wavelength coverage over the entire band from 380 nm to 1260 nm through the use of three separate optical channels: blue, red, and near infrared (NIR). A camera in each channel images the multi-object spectra onto a 4k x 4k, 15 um pixel, detector format. The two visible cameras use a pair of Hamamatsu 2k x 4k CCDs with readout provided by custom electronics, while the NIR camera uses a single Teledyne HgCdTe 4k x 4k detector and ASIC Sidecar to read the device. The CCD readout system is a custom design comprised of three electrical subsystems: the Back End Electronics (BEE), the Front End Electronics (FEE), and a Pre-amplifier. The BEE is an off-the-shelf PC104 computer, with an auxiliary Xilinx FPGA module. The computer serves as the main...

  18. THE COSMIC ORIGINS SPECTROGRAPH

    Energy Technology Data Exchange (ETDEWEB)

    Green, James C.; Michael Shull, J.; Snow, Theodore P.; Stocke, John [Department of Astrophysical and Planetary Sciences, University of Colorado, 391-UCB, Boulder, CO 80309 (United States); Froning, Cynthia S.; Osterman, Steve; Beland, Stephane; Burgh, Eric B.; Danforth, Charles; France, Kevin [Center for Astrophysics and Space Astronomy, University of Colorado, 389-UCB, Boulder, CO 80309 (United States); Ebbets, Dennis [Ball Aerospace and Technologies Corp., 1600 Commerce Street, Boulder, CO 80301 (United States); Heap, Sara H. [NASA Goddard Space Flight Center, Code 681, Greenbelt, MD 20771 (United States); Leitherer, Claus; Sembach, Kenneth [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); Linsky, Jeffrey L. [JILA, University of Colorado and NIST, Boulder, CO 80309-0440 (United States); Savage, Blair D. [Department of Astronomy, University of Wisconsin-Madison, 475 North Charter Street, Madison, WI 53706 (United States); Siegmund, Oswald H. W. [Astronomy Department, University of California, Berkeley, CA 94720 (United States); Spencer, John; Alan Stern, S. [Southwest Research Institute, 1050 Walnut Street, Suite 300, Boulder, CO 80302 (United States); Welsh, Barry [Space Sciences Laboratory, University of California, 7 Gauss Way, Berkeley, CA 94720 (United States); and others

    2012-01-01

    The Cosmic Origins Spectrograph (COS) is a moderate-resolution spectrograph with unprecedented sensitivity that was installed into the Hubble Space Telescope (HST) in 2009 May, during HST Servicing Mission 4 (STS-125). We present the design philosophy and summarize the key characteristics of the instrument that will be of interest to potential observers. For faint targets, with flux F{sub {lambda}} Almost-Equal-To 1.0 Multiplication-Sign 10{sup -14} erg cm{sup -2} s{sup -1} A{sup -1}, COS can achieve comparable signal to noise (when compared to Space Telescope Imaging Spectrograph echelle modes) in 1%-2% of the observing time. This has led to a significant increase in the total data volume and data quality available to the community. For example, in the first 20 months of science operation (2009 September-2011 June) the cumulative redshift pathlength of extragalactic sight lines sampled by COS is nine times than sampled at moderate resolution in 19 previous years of Hubble observations. COS programs have observed 214 distinct lines of sight suitable for study of the intergalactic medium as of 2011 June. COS has measured, for the first time with high reliability, broad Ly{alpha} absorbers and Ne VIII in the intergalactic medium, and observed the He II reionization epoch along multiple sightlines. COS has detected the first CO emission and absorption in the UV spectra of low-mass circumstellar disks at the epoch of giant planet formation, and detected multiple ionization states of metals in extra-solar planetary atmospheres. In the coming years, COS will continue its census of intergalactic gas, probe galactic and cosmic structure, and explore physics in our solar system and Galaxy.

  19. Million object spectrograph

    Science.gov (United States)

    Ditto, Thomas D.; Ritter, Joseph M.

    2008-07-01

    A new class of astronomical telescope with a primary objective grating (POG) has been studied as an alternative to mirrors. Nineteenth century POG telescopes suffered from low resolution and ambiguity of overlapping spectra as well as background noise. The present design uses a conventional secondary spectrograph to disambiguate all objects while enjoying a very wide instantaneous field-of-view, up to 40°. The POG competes with mirrors, in part, because diffraction gratings provide the very chromatic dispersion that mirrors defeat. The resulting telescope deals effectively with long-standing restrictions on multiple object spectrographs (MOS). The combination of a POG operating in the first-order, coupled to a spectrographic astronomical telescope, isolates spectra from all objects in the free spectral range of the primary. First disclosed as a concept in year 2002, a physical proof-of-principle is now reported. The miniature laboratory model used a 50 mm plane grating primary and was able to disambiguate between objects appearing at angular resolutions of 55 arcseconds and spectral spacings of 0.15 nm. Astronomical performance is a matter of increasing instrument size. A POG configured according to our specifications has no moving parts during observations and is extensible to any length that can be held flat to tolerances approaching float glass. The resulting telescope could record over one million spectra per night of objects in a line of right ascension. The novel MOS does not require pre-imaging to start acquisition of uncharted star fields. Problems are anticipated in calibration and integration time. We propose means to ameliorate them.

  20. Two-color double-labeling in situ hybridization of whole-mount Hydra using RNA probes for five different Hydra neuropeptide preprohormones: evidence for colocalization

    DEFF Research Database (Denmark)

    Hansen, G N; Williamson, M; Grimmelikhuijzen, C J

    2000-01-01

    -terminal sequence Lys-Val-NH2 (Hydra-KVamide). The various Hydra-RFamides are synthesized by three different preprohormones: preprohormone-A, -B, and -C. The various Hydra-LWamides are synthesized by a single preprohormone (prepro-Hydra-LWamide), as is Hydra-KVamide (prepro-Hydra-KVamide). Using a wholemount double-labeling...... exists that expresses both preprohormones-A and preproHydra-KVamide mRNAs. The functional significance of this coexpression is unclear. This is the first report on the coexpression of two well-characterized preprohormones (yielding two well-characterized neurohormone families) in cnidarians. This report...

  1. Acceleration of solving the dynamic multi-objective network design problem using response surface methods

    NARCIS (Netherlands)

    Wismans, L.J.J.; Berkum, van E.C.; Bliemer, M.C.J.

    2014-01-01

    Optimization of externalities and accessibility using dynamic traffic management measures on a strategic level is a specific example of solving a multi-objective network design problem. Solving this optimization problem is time consuming, because heuristics like evolutionary multi objective algorith

  2. The Aggregate Homotopy Method for Multi-objective Max-min Problems

    Directory of Open Access Journals (Sweden)

    He Li

    2011-03-01

    Full Text Available Multi-objective programming problem was transformed into a class of simple unsmooth single-objective programming problem by Max-min ways. After smoothing with aggregate function, a new homotopy mapping was constructed. The minimal weak efficient solution of the multi-objective optimization problem was obtained by path tracking. Numerical simulation confirmed the viability of this method.

  3. WES - Weihai Echelle Spectrograph

    CERN Document Server

    Gao, Dong-Yang; Cao, Chen; Hu, Shao-Ming; Wittenmyer, Robert A; Hu, Zhong-Wen; Grupp, Frank; Kellermann, Hanna; Li, Kai; Guo, Di-Fu

    2016-01-01

    The Weihai Echelle Spectrograph (WES) is the first fiber-fed echelle spectrograph for astronomical observation in China. It is primarily used for chemical abundance and asteroseismology studies of nearby bright stars, as well as radial velocity detections for exoplanets. The optical design of WES is based on the widely demonstrated and well-established white-pupil concept. We describe the WES in detail and present some examples of its performance. A single exposure echelle image covers the spectral region 371-1,100 nm in 107 spectral orders over the rectangular CCD. The spectral resolution $R=\\lambda/\\Delta\\lambda$ changes from 40,600 to 57,000 through adjusting the entrance slit width from full to 2.2 pixels sampling at the fiber-exit. The limiting magnitude scales to $V=8$ with a signal-to-noise ratio (SNR) of more than 100 in $V$ for an hour exposure, at the spectral resolution R$\\approx$40,000 in the median seeing of 1.7$^{\\prime\\prime}$ at Weihai Observatory (WHO) for the 1-meter telescope. The radial ve...

  4. The Cosmic Origins Spectrograph

    CERN Document Server

    Green, James C; Osterman, Steve; Ebbets, Dennis; Heap, Sara H; Linsky, Claus Leitherer Jeffrey L; Savage, Blair D; Sembach, Kenneth; Shull, J Michael; Siegmund, Oswald H W; Snow, Theodore P; Spencer, John; Stern, S Alan; Stocke, John; Welsh, Barry; Beland, Stephane; Burgh, Eric B; Danforth, Charles; France, Kevin; Keeney, Brian; McPhate, Jason; Penton, Steven V; Andrews, John; Brownsberger, Kenneth; Morse, Jon; Wilkinson, Erik

    2011-01-01

    The Cosmic Origins Spectrograph (COS) is a moderate-resolution spectrograph with unprecedented sensitivity that was installed into the Hubble Space Telescope (HST) in May 2009, during HST Servicing Mission 4 (STS-125). We present the design philosophy and summarize the key characteristics of the instrument that will be of interest to potential observers. For faint targets, with flux F_lambda ~ 1.0E10-14 ergs/s/cm2/Angstrom, COS can achieve comparable signal to noise (when compared to STIS echelle modes) in 1-2% of the observing time. This has led to a significant increase in the total data volume and data quality available to the community. For example, in the first 20 months of science operation (September 2009 - June 2011) the cumulative redshift pathlength of extragalactic sight lines sampled by COS is 9 times that sampled at moderate resolution in 19 previous years of Hubble observations. COS programs have observed 214 distinct lines of sight suitable for study of the intergalactic medium as of June 2011....

  5. Wave-front error breakdown in laser guide star multi-object adaptive optics validated on-sky by Canary

    Science.gov (United States)

    Martin, O. A.; Gendron, É.; Rousset, G.; Gratadour, D.; Vidal, F.; Morris, T. J.; Basden, A. G.; Myers, R. M.; Correia, C. M.; Henry, D.

    2017-01-01

    Context. Canary is the multi-object adaptive optics (MOAO) on-sky pathfinder developed in the perspective of multi-object spectrograph on extremely large telescopes (ELTs). In 2013, Canary was operated on-sky at the William Herschel telescope (WHT), using three off-axis natural guide stars (NGS) and four off-axis Rayleigh laser guide stars (LGS), in open-loop, with the on-axis compensated turbulence observed with a H-band imaging camera and a Truth wave-front sensor (TS) for diagnostic purposes. Aims: Our purpose is to establish a reliable and accurate wave-front error breakdown for LGS MOAO. This will enable a comprehensive analysis of Canary on-sky results and provide tools for validating simulations of MOAO systems for ELTs. Methods: To evaluate the MOAO performance, we compared the Canary on-sky results running in MOAO, in single conjugated adaptive optics (SCAO) and in ground layer adaptive optics (GLAO) modes, over a large set of data acquired in 2013. We provide a statistical study of the seeing. We also evaluated the wave-front error breakdown from both analytic computations, one based on a MOAO system modelling and the other on the measurements from the Canary TS. We have focussed especially on the tomographic error and we detail its vertical error decomposition. Results: We show that Canary obtained 30.1%, 21.4% and 17.1% H-band Strehl ratios in SCAO, MOAO and GLAO respectively, for median seeing conditions with 0.66'' of total seeing including 0.59'' at the ground. Moreover, we get 99% of correlation over 4500 samples, for any AO modes, between two analytic computations of residual phase variance. Based on these variances, we obtain a reasonable Strehl-ratio (SR) estimation when compared to the measured IR image SR. We evaluate the gain in compensation for the altitude turbulence brought by MOAO when compared to GLAO.

  6. A multi-object detection and tracking method in wireless video sensor networks

    Science.gov (United States)

    Chu, Zheng; Zhang, Jing; Zhuo, Li

    2012-04-01

    Most multi-object detection and tracking techniques suffer from the well-known "multi-object occlusion" problem. The abundant nodes of wireless video sensor networks (WVSNs) can be utilized to solve the problem, and the video nodes in WVSN have limited calculation capability and energy. In order to achieve effective multi-object tracking using WVSN, the main contributions of our proposed method are that: (1) the limits of field of view (FOV) of every video nodes are utilized to establish the consistent labeling of the objects in different views. (2) Mobile Agent is employed to communicate among network nodes, so the objects are assigned correct labels after multi-object occlusion. The performance of the approach has been demonstrated on real-world and the experimental results show that the proposed method is effective for resolving multi-object occlusions and meets the requirement of WVSN.

  7. Isolation of a substance activating foot formation in hydra

    DEFF Research Database (Denmark)

    Grimmelikhuijzen, C J; Schaller, H C

    1977-01-01

    -forming potential of the tissue (2) It does not accelerate head regeneration, nor do the head factors of hydra discovered by Schaller (1973) and Berking (1977) accelerate foot regeneration. We propose that the foot-activating substance is a morphogen responsible for foot formation in hydra. The foot activator can...... be extracted from hydra tissue with methanol and separated from other known morphogens of hydra by gel filtration and ion-exchange chromatography. A substance with similar biological and physicochemical properties can be isolated from sea anemones....

  8. 2D analytical modeling of distortion and sky background in multi-fiber spectrographs the case of the Norris spectrograph at Palomar Mountain

    CERN Document Server

    Viton, M; Viton, Maurice; Milliard, Bruno

    2002-01-01

    A method for optimal reduction of data taken with multi-fiber spectrographs is described, based on global correction of their geometrical distortion. Though it was specifically developed for reducing observations performed at Palomar Mountain using the Norris fiber spectrograph, this method can be adapted to other types of multi-object spectrographs such as the multi-slit ones. Combined with a 2D analytical interpolation of sky-background that accounts for non-uniform spectral resolution, the Norris software package achieves very high accuracy in airglow subtraction, even in the near infrared (7000-9000A) where molecular band-emissions commonly induce strong artefacts that preclude clean sky subtraction whenever standard image processing techniques are used. Correlatively, an improvement by a factor of 2 on the precision of radial velocities is achievable. Throughout the paper possible improvements to the method are suggested for those devising similar packages for other instruments.

  9. The effects of dopamine synthesis inhibitors and dopamine antagonists on regeneration in the hydra Hydra attenuata.

    Science.gov (United States)

    Ostroumova, T V; Markova, L N

    2002-01-01

    The effects of catecholamine synthesis inhibitors (alpha-methyltyrosine, 3-iodotyrosine, and alpha-methyl-DOPA) and dopamine receptor blockers (haloperidol and spiperone) on the regeneration of apical, gastral, and basal fragments of the hydra Hydra attenuata were studied. These experiments showed that alpha-methyltyrosine and 3-iodotyrosine significantly inhibited regeneration but did not produce morphological anomalies. Alpha-Methyl-DOPA produce less inhibition of regeneration, but induced ectopic tentacles and outgrowths in gastral regenerates. Haloperidol and spiperone had no significant effect on the rate of regeneration but induced significant numbers of morphogenetic anomalies in gastral regenerates. Apical and basal regenerates, which retained their natural organizers (the head and base respectively) never yielded morphogenetic anomalies in the presence of either dopamine receptor blockers or dopamine synthesis inhibitors. The possible role of neurotransmitters. particularly dopamine, in morphogenesis in hydras is discussed.

  10. The Cosmic Origins Spectrograph

    Science.gov (United States)

    Green, James C.; Froning, Cynthia S.; Osterman, Steve; Ebbets, Dennis; Heap, Sara H.; Leitherer, Claus; Linsky, Jeffrey L.; Savage, Blair D.; Sembach, Kenneth; Shull, J. Michael; Siegmund, Oswald H. W.; Snow, Theodore P.; Spencer, John; Stern, S. Alan; Stocke, John; Welsh, Barry; Beland, Stephane; Burgh, Eric B.; Danforth, Charles; France, Kevin; Keeney, Brian; McPhate, Jason; Penton, Steven V; Andrews, John; Morse, Jon

    2010-01-01

    The Cosmic Origins Spectrograph (COS) is a moderate-resolution spectrograph with unprecedented sensitivity that was installed into the Hubble Space Telescope (HST) in May 2009, during HST Servicing Mission 4 (STS-125). We present the design philosophy and summarize the key characteristics of the instrument that will be of interest to potential observers. For faint targets, with flux F(sub lambda) approximates 1.0 X 10(exp -14) ergs/s/cm2/Angstrom, COS can achieve comparable signal to noise (when compared to STIS echelle modes) in 1-2% of the observing time. This has led to a significant increase in the total data volume and data quality available to the community. For example, in the first 20 months of science operation (September 2009 - June 2011) the cumulative redshift pathlength of extragalactic sight lines sampled by COS is 9 times that sampled at moderate resolution in 19 previous years of Hubble observations. COS programs have observed 214 distinct lines of sight suitable for study of the intergalactic medium as of June 2011. COS has measured, for the first time with high reliability, broad Lya absorbers and Ne VIII in the intergalactic medium, and observed the HeII reionization epoch along multiple sightlines. COS has detected the first CO emission and absorption in the UV spectra of low-mass circumstellar disks at the epoch of giant planet formation, and detected multiple ionization states of metals in extra-solar planetary atmospheres. In the coming years, COS will continue its census of intergalactic gas, probe galactic and cosmic structure, and explore physics in our solar system and Galaxy.

  11. On the Effect of Populations in Evolutionary Multi-Objective Optimisation

    DEFF Research Database (Denmark)

    Giel, Oliver; Lehre, Per Kristian

    2010-01-01

    Multi-objective evolutionary algorithms (MOEAs) have become increasingly popular as multi-objective problem solving techniques. An important open problem is to understand the role of populations in MOEAs. We present two simple bi-objective problems which emphasise when populations are needed....... Rigorous runtime analysis points out an exponential runtime gap between the population-based algorithm Simple Evolutionary Multi-objective Optimiser (SEMO) and several single individual-based algorithms on this problem. This means that among the algorithms considered, only the population-based MOEA...

  12. Fibre positioning algorithms for the WEAVE spectrograph

    Science.gov (United States)

    Terrett, David L.; Lewis, Ian J.; Dalton, Gavin; Abrams, Don Carlos; Aguerri, J. Alfonso L.; Bonifacio, Piercarlo; Middleton, Kevin; Trager, Scott C.

    2014-07-01

    WEAVE is the next-generation wide-field optical spectroscopy facility for the William Herschel Telescope (WHT) in La Palma, Canary Islands, Spain. It is a multi-object "pick and place" fibre fed spectrograph with more than one thousand fibres, similar in concept to the Australian Astronomical Observatory's 2dF1 instrument with two observing plates, one of which is observing the sky while other is being reconfigured by a robotic fibre positioner. It will be capable of acquiring more than 10000 star or galaxy spectra a night. The WEAVE positioner concept uses two robots working in tandem in order to reconfigure a fully populated field within the expected 1 hour dwell-time for the instrument (a good match between the required exposure times and the limit of validity for a given configuration due to the effects of differential refraction). This presents additional constraints and complications for the software that determines the optimal path from one configuration to the next, particularly given the large number of fibre crossings implied by the 1000 fibre multiplex. This paper describes the algorithms and programming techniques used in the prototype implementations of the field configuration tool and the fibre positioner robot controller developed to support the detailed design of WEAVE.

  13. Bombesin-like immunoreactivity in the nervous system of hydra

    DEFF Research Database (Denmark)

    Grimmelikhuijzen, C J; Dockray, G J; Yanaihara, N

    1981-01-01

    With immunocytochemical methods, nerve cells have been detected in Hydra attenuata containing bombesin-like immunoreactivity. These nerve cells are located in ectoderm of all body regions of the animal and are especially abundant in basal disk and tentacles. Radioimmunoassay of extracts of hydra ...

  14. Neurotensin-like immunoreactivity in the nervous system of hydra

    DEFF Research Database (Denmark)

    Grimmelikhuijzen, C J; Carraway, R E; Rökaeus, A

    1981-01-01

    Neurotensin-like immunoreactivity is found in nerve fibers present in all body regions of hydra. The nerve fibers are especially numerous in the ectoderm at the bases of the tentacles and in the ectoderm at a site just above the foot. Radioimmunoassays of acetic-acid extracts of hydra, using vari...

  15. HYDRA: a decision support model for irrigation water management

    NARCIS (Netherlands)

    Jacucci, G.; Kabat, P.; Verrier, P.J.; Teixeira, J.L.; Steduto, P.; Bertanzon, G.; Giannerini, G.; Huygen, J.; Fernando, R.M.; Hooijer, A.A.; Simons, W.; Toller, G.; Tziallas, G.; Uhrik, C.; Broek, van den B.J.; Vera Munoz, J.; Yovchev, P.

    1995-01-01

    HYDRA introduces information modelling and decision-support systems (DSS) to farmers and authorities in European Mediterranean agriculture in order to improve irrigation practices at different levels. Key components of HYDRA-DSS are a hierarchical setof water balance and crop growth simulation

  16. Bombesin-like immunoreactivity in the nervous system of hydra

    DEFF Research Database (Denmark)

    Grimmelikhuijzen, C J; Dockray, G J; Yanaihara, N

    1981-01-01

    With immunocytochemical methods, nerve cells have been detected in Hydra attenuata containing bombesin-like immunoreactivity. These nerve cells are located in ectoderm of all body regions of the animal and are especially abundant in basal disk and tentacles. Radioimmunoassay of extracts of hydra...

  17. 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.

  18. 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.

  19. 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...

  20. Sensitivity analysis of multi-objective optimization of CPG parameters for quadruped robot locomotion

    Science.gov (United States)

    Oliveira, Miguel; Santos, Cristina P.; Costa, Lino

    2012-09-01

    In this paper, a study based on sensitivity analysis is performed for a gait multi-objective optimization system that combines bio-inspired Central Patterns Generators (CPGs) and a multi-objective evolutionary algorithm based on NSGA-II. In this system, CPGs are modeled as autonomous differential equations, that generate the necessary limb movement to perform the required walking gait. In order to optimize the walking gait, a multi-objective problem with three conflicting objectives is formulated: maximization of the velocity, the wide stability margin and the behavioral diversity. The experimental results highlight the effectiveness of this multi-objective approach and the importance of the objectives to find different walking gait solutions for the quadruped robot.

  1. Conceptual design of IR multi-IFU spectrograph with MOAO

    Science.gov (United States)

    Tomono, Daigo; Gaessler, Wolfgang; Nishimura, Tetsuo

    2008-07-01

    To study properties of cold dark matter (CDM), which can only be observed through its gravitational interaction with galaxies, spatially resolved spectra at least to the K-band are desirable. We started designing a spectrograph which observes multiple targets spatially resolved in a telescope field of view fed with multi-object adaptive optics (MOAO). The current design either places field lenses on the telescope field of view to image the pupil onto steering mirrors, or uses a single set of field lens to deliver beams to pick-off arms. The steering mirror on the pupil image tilts and selects a sub-field from each of the telescope field of view physically split by the field lenses. This allows cheaper and more robust construction of a method to select the target fields with a limitation in selections of the target fields. On the other hand, the pick-off arm implementation allows more flexibility in assigning targets to fields of the integral field units (IFUs) especially when targets are clustered. The IFU arranges spatial elements of each of sub-field of view to be fed into the spectrograph. If enough pixels are afforded, using microlens arrays, which image pupils of spatial elements onto the object plane of the spectrograph is ideal in robustness. Otherwise, an image slicer is to be located to arrange the sub-field of view onto the entrance slit. The instrument should be built as modules to allow expeditious scientific results.

  2. On the Origin of Pluto's Minor Moons, Nix and Hydra

    CERN Document Server

    Lithwick, Yoram

    2008-01-01

    How did Pluto's recently discovered minor moons form? Ward and Canup propose an elegant solution in which Nix and Hydra formed in the collision that produced Charon, then were caught into corotation resonances with Charon, and finally were transported to their current location as Charon migrated outwards. We show with numerical integrations that, if Charon's eccentricity is judiciously chosen, this scenario works beautifully for either Nix or Hydra. However, it cannot work for both Nix and Hydra simultaneously. To transport Nix, Charon's eccentricity must satisfy e_C 0.7 R_p/a_C > 0.04; otherwise migration would be faster than libration, and Hydra would slip out of resonance. These two restrictions conflict. Having ruled out this scenario, we suggest an alternative: that many small bodies were captured from the nebular disk, and they were responsible for forming, migrating and damping Nix and Hydra. If this is true, small moons could be common around large Kuiper belt objects.

  3. HYDRA: a Java library for Markov Chain Monte Carlo

    Directory of Open Access Journals (Sweden)

    Gregory R. Warnes

    2002-03-01

    Full Text Available Hydra is an open-source, platform-neutral library for performing Markov Chain Monte Carlo. It implements the logic of standard MCMC samplers within a framework designed to be easy to use, extend, and integrate with other software tools. In this paper, we describe the problem that motivated our work, outline our goals for the Hydra pro ject, and describe the current features of the Hydra library. We then provide a step-by-step example of using Hydra to simulate from a mixture model drawn from cancer genetics, first using a variable-at-a-time Metropolis sampler and then a Normal Kernel Coupler. We conclude with a discussion of future directions for Hydra.

  4. Multi-objective Optimization of Process Performances when Cutting Carbon Steel with Abrasive Water Jet

    Directory of Open Access Journals (Sweden)

    M. Radovanović

    2016-12-01

    Full Text Available Multi-objective optimization of process performances (perpendicularity deviation, surface roughness and productivity when cutting carbon steel EN S235 with abrasive water jet is presented in this paper. Cutting factors (abrasive flow rate, traverse rate and standoff distance were determined when perpendicularity deviation and surface roughness are minimal and productivity is maximal. Multi-objective genetic algorithm (MOGA was used for the determination set of nondominated optimal points, known as Pareto front.

  5. Fuzzy Multi-Objective Decision Model of Supplier Selection with Preference Information

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Supplier selection is a multi-objective decision problem, which must be considered many objectives, someobjectives are qualitative, and others are quantitative. Meanwhile, manufacturer has preference for different suppliers.In this paper, a new multi-objective decision model with preference information of supplier is established. A practicalexample of supplier selection problem utilizing this model is studied. The result demonstrates the feasibility andeffectiveness of the methods proposed in the paper.

  6. 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.

  7. A Multi-Objective Optimal Evolutionary Algorithm Based on Tree-Ranking

    Institute of Scientific and Technical Information of China (English)

    Shi Chuan; Kang Li-shan; Li Yan; Yan Zhen-yu

    2003-01-01

    Multi-objective optimal evolutionary algorithms (MOEAs) are a kind of new effective algorithms to solve Multi-objective optimal problem (MOP). Because ranking, a method which is used by most MOEAs to solve MOP, has some shortcoming s, in this paper, we proposed a new method using tree structure to express the relationship of solutions. Experiments prove that the method can reach the Pare to front, retain the diversity of the population, and use less time.

  8. Simulation and experimental validation of powertrain mounting bracket design obtained from multi-objective topology optimization

    OpenAIRE

    Qinghai Zhao; Xiaokai Chen; Lu Wang; Jianfeng Zhu; Zheng-Dong Ma; Yi Lin

    2015-01-01

    A framework of multi-objective topology optimization for vehicle powertrain mounting bracket design with consideration of multiple static and dynamic loading conditions is developed in this article. Incorporating into the simplified isotropic material with penalization model, compromise programming method is employed to describe the multi-objective and multi-stiffness topology optimization under static loading conditions, whereas mean eigenvalue formulation is proposed to analyze vibration op...

  9. Application of a fast and elitist multi-objective genetic algorithm to Reactive Power Dispatch

    OpenAIRE

    2009-01-01

    This paper presents an Elitist Non-Dominated Sorting Genetic Algorithm version II (NSGA-II), for solving the Reactive Power Dispatch (RPD) problem. The optimal RPD problem is a nonlinear constrained multi-objective optimization problem where the real power loss and the bus voltage deviations are to be minimized. Since the problem is treated as a true multi-objective optimization problem, different trade-off solutions are provided. The decision maker has an option to choose a solution among th...

  10. Genetic Algorithm-Based Multi-objective Optimisation for QoS-Aware Web Services Composition

    Science.gov (United States)

    Li, Li; Yang, Pengyi; Ou, Ling; Zhang, Zili; Cheng, Peng

    Finding an optimal solution for QoS-aware Web service composition with various restrictions on qualities is a multi-objective optimisation problem. A popular multi-objective genetic algorithm, NSGA-II, is studied in order to provide a set of optimal solutions for QoS-based service composition. Experiments with different numbers of abstract and concrete services confirm the expected behaviour of the algorithm.

  11. An adaptive evolutionary multi-objective approach based on simulated annealing.

    Science.gov (United States)

    Li, H; Landa-Silva, D

    2011-01-01

    A multi-objective optimization problem can be solved by decomposing it into one or more single objective subproblems in some multi-objective metaheuristic algorithms. Each subproblem corresponds to one weighted aggregation function. For example, MOEA/D is an evolutionary multi-objective optimization (EMO) algorithm that attempts to optimize multiple subproblems simultaneously by evolving a population of solutions. However, the performance of MOEA/D highly depends on the initial setting and diversity of the weight vectors. In this paper, we present an improved version of MOEA/D, called EMOSA, which incorporates an advanced local search technique (simulated annealing) and adapts the search directions (weight vectors) corresponding to various subproblems. In EMOSA, the weight vector of each subproblem is adaptively modified at the lowest temperature in order to diversify the search toward the unexplored parts of the Pareto-optimal front. Our computational results show that EMOSA outperforms six other well established multi-objective metaheuristic algorithms on both the (constrained) multi-objective knapsack problem and the (unconstrained) multi-objective traveling salesman problem. Moreover, the effects of the main algorithmic components and parameter sensitivities on the search performance of EMOSA are experimentally investigated.

  12. The infrared imaging spectrograph (IRIS) for TMT: spectrograph design

    CERN Document Server

    Moore, Anna M; Barton, Elizabeth J; Crampton, David; Delacroix, Alex; Larkin, James E; Simard, Luc; Suzuki, Ryuji; Wright, Shelley A

    2010-01-01

    The Infra-Red Imaging Spectrograph (IRIS) is one of the three first light instruments for the Thirty Meter Telescope (TMT) and is the only one to directly sample the diffraction limit. The instrument consists of a parallel imager and off-axis Integral Field Spectrograph (IFS) for optimum use of the near infrared (0.84um-2.4um) Adaptive Optics corrected focal surface. We present an overview of the IRIS spectrograph that is designed to probe a range of scientific targets from the dynamics and morphology of high-z galaxies to studying the atmospheres and surfaces of solar system objects, the latter requiring a narrow field and high Strehl performance. The IRIS spectrograph is a hybrid system consisting of two state of the art IFS technologies providing four plate scales (4mas, 9mas, 25mas, 50mas spaxel sizes). We present the design of the unique hybrid system that combines the power of a lenslet spectrograph and image slicer spectrograph in a configuration where major hardware is shared. The result is a powerful...

  13. Three different prohormones yield a variety of Hydra-RFamide (Arg-Phe-NH2) neuropeptides in Hydra magnipapillata

    DEFF Research Database (Denmark)

    Darmer, D; Hauser, F; Nothacker, H P;

    1998-01-01

    from H. magnipapillata, each of which gives rise to a variety of RFamide neuropeptides. Preprohormone A contains one copy of unprocessed Hydra-RFamide I (QWLGGRFG), II (QWFNGRFG), III/IV [(KP)HLRGRFG] and two putative neuropeptide sequences (QLMSGRFG and QLMRGRFG). Preprohormone B has the same general...... organization as preprohormone A, but instead of unprocessed Hydra-RFamide III/IV it contains a slightly different neuropeptide sequence [(KP)HYRGRFG]. Preprohormone C contains one copy of unprocessed Hydra-RFamide I and seven additional putative neuropeptide sequences (with the common N-terminal sequence QWF....../LSGRFGL). The two Hydra-RFamide II copies (in preprohormones A and B) are preceded by Thr residues, and the single Hydra-RFamide III/IV copy (in preprohormone A) is preceded by an Asn residue, confirming that cnidarians use unconventional processing signals to generate neuropeptides from their precursor proteins...

  14. Using commercial amateur astronomical spectrographs

    CERN Document Server

    Hopkins, Jeffrey L

    2014-01-01

    Amateur astronomers interested in learning more about astronomical spectroscopy now have the guide they need. It provides detailed information about how to get started inexpensively with low-resolution spectroscopy, and then how to move on to more advanced  high-resolution spectroscopy. Uniquely, the instructions concentrate very much on the practical aspects of using commercially-available spectroscopes, rather than simply explaining how spectroscopes work. The book includes a clear explanation of the laboratory theory behind astronomical spectrographs, and goes on to extensively cover the practical application of astronomical spectroscopy in detail. Four popular and reasonably-priced commercially available diffraction grating spectrographs are used as examples. The first is a low-resolution transmission diffraction grating, the Star Analyser spectrograph. The second is an inexpensive fiber optic coupled bench spectrograph that can be used to learn more about spectroscopy. The third is a newcomer, the ALPY ...

  15. A new species of green hydra (Hydrozoa: Hydrida) from China.

    Science.gov (United States)

    Wang, An-Tai; Deng, Li; Lai, Jing-Qi; Li, Juan

    2009-09-01

    A new species of green freshwater hydra (Cnidaria, Hydrozoa: Hydrida), Hydra sinensis, is described from Guangdong Province, China. The chief distinction between H. sinensis sp. nov. and three other green hydras (H. hadleyi, H. viridissima, and H. plagiodesmica) is in the holotrichous isorhizae. Hydra sinensis sp. nov. differs from H. plagiodesmica in the shape of the holotrichous isorhlzae, and from H. viridissima and H. hadleyi in the tubule of the capsule of the holotrichous isorhlzae. The capsule tubule colls two times in 86% and three times in 14% of holotrlchous isorhlzae (n=50) In H. sinensis sp. nov.; we observed no tubules coiling four times. In contrast, the capsule tubule coils three or four times in H. viridissima and H. hadleyi, and no tubules coiling two times have been reported. In addition, holotrichous isorhlzae, which are mainly located around the hypostome, are sparse in the tentacles of H. sinensis sp. nov., whereas the majority of holotrichous isorhlzae is located on the tentacles in most other hydras. A molecular phylogenetic analysis using the nuclear small subunlt (18S) ribosomal RNA gene Indicated a close relationship between H. sinensis and H. viridissima. Hydra viridissima did not group within a clade of four Individuals of H. sinensis, Indicating a possible sister-species relationship between the two species. Morphological characters in combination with the molecular phylogenetic evidence support Hydra sinensis as a new species.

  16. LAMOST Spectrograph Response Curves: Stability and Application to Flux Calibration

    Science.gov (United States)

    Du, Bing; Luo, A.-Li; Kong, Xiao; Zhang, Jian-Nan; Guo, Yan-Xin; Cook, Neil James; Hou, Wen; Yang, Hai-Feng; Li, Yin-Bi; Song, Yi-Han; Chen, Jian-Jun; Zuo, Fang; Wu, Ke-Fei; Wang, Meng-Xin; Wu, Yue; Wang, You-Fen; Zhao, Yong-Heng

    2016-12-01

    The task of flux calibration for Large sky Area Multi-Object Spectroscopic Telescope (LAMOST) spectra is difficult due to many factors, such as the lack of standard stars, flat-fielding for large field of view, and variation of reddening between different stars, especially at low Galactic latitudes. Poor selection, bad spectral quality, or extinction uncertainty of standard stars not only might induce errors to the calculated spectral response curve (SRC) but also might lead to failures in producing final 1D spectra. In this paper, we inspected spectra with Galactic latitude | b| ≥slant 60^\\circ and reliable stellar parameters, determined through the LAMOST Stellar Parameter Pipeline (LASP), to study the stability of the spectrograph. To guarantee that the selected stars had been observed by each fiber, we selected 37,931 high-quality exposures of 29,000 stars from LAMOST DR2, and more than seven exposures for each fiber. We calculated the SRCs for each fiber for each exposure and calculated the statistics of SRCs for spectrographs with both the fiber variations and time variations. The result shows that the average response curve of each spectrograph (henceforth ASPSRC) is relatively stable, with statistical errors ≤10%. From the comparison between each ASPSRC and the SRCs for the same spectrograph obtained by the 2D pipeline, we find that the ASPSRCs are good enough to use for the calibration. The ASPSRCs have been applied to spectra that were abandoned by the LAMOST 2D pipeline due to the lack of standard stars, increasing the number of LAMOST spectra by 52,181 in DR2. Comparing those same targets with the Sloan Digital Sky Survey (SDSS), the relative flux differences between SDSS spectra and LAMOST spectra with the ASPSRC method are less than 10%, which underlines that the ASPSRC method is feasible for LAMOST flux calibration.

  17. Effective multi-objective optimization with the coral reefs optimization algorithm

    Science.gov (United States)

    Salcedo-Sanz, S.; Pastor-Sánchez, A.; Portilla-Figueras, J. A.; Prieto, L.

    2016-06-01

    In this article a new algorithm for multi-objective optimization is presented, the Multi-Objective Coral Reefs Optimization (MO-CRO) algorithm. The algorithm is based on the simulation of processes in coral reefs, such as corals' reproduction and fight for space in the reef. The adaptation to multi-objective problems is a process based on domination or non-domination during the process of fight for space in the reef. The final MO-CRO is an easily-implemented and fast algorithm, simple and robust, since it is able to keep diversity in the population of corals (solutions) in a natural way. The experimental evaluation of this new approach for multi-objective optimization problems is carried out on different multi-objective benchmark problems, where the MO-CRO has shown excellent performance in cases with limited computational resources, and in a real-world problem of wind speed prediction, where the MO-CRO algorithm is used to find the best set of features to predict the wind speed, taking into account two objective functions related to the performance of the prediction and the computation time of the regressor.

  18. 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.

  19. Multi-objective optimization of empirical hydrological model for streamflow prediction

    Science.gov (United States)

    Guo, Jun; Zhou, Jianzhong; Lu, Jiazheng; Zou, Qiang; Zhang, Huajie; Bi, Sheng

    2014-04-01

    Traditional calibration of hydrological models is performed with a single objective function. Practical experience with the calibration of hydrologic models reveals that single objective functions are often inadequate to properly measure all of the characteristics of the hydrologic system. To circumvent this problem, in recent years, a lot of studies have looked into the automatic calibration of hydrological models with multi-objective functions. In this paper, the multi-objective evolution algorithm MODE-ACM is introduced to solve the multi-objective optimization of hydrologic models. Moreover, to improve the performance of the MODE-ACM, an Enhanced Pareto Multi-Objective Differential Evolution algorithm named EPMODE is proposed in this research. The efficacy of the MODE-ACM and EPMODE are compared with two state-of-the-art algorithms NSGA-II and SPEA2 on two case studies. Five test problems are used as the first case study to generate the true Pareto front. Then this approach is tested on a typical empirical hydrological model for monthly streamflow forecasting. The results of these case studies show that the EPMODE, as well as MODE-ACM, is effective in solving multi-objective problems and has great potential as an efficient and reliable algorithm for water resources applications.

  20. The Pulsation Spectrum of VX Hydrae

    Science.gov (United States)

    Templeton, M. R.; Samolyk, G.; Dvorak, S.; Poklar, R.; Butterworth, N.; Gerner, H.

    2009-10-01

    We present the results of a two-year, multisite observing campaign investigating the high-amplitude δ Scuti star VX Hydrae during the 2006 and 2007 observing seasons. The final data set consists of nearly 8500 V-band observations spanning HJD 2453763.6 to 2454212.7 (2006 January 28 to 2007 April 22). Separate analyses of the two individual seasons of data yield 25 confidently detected frequencies common to both data sets, of which two are pulsation modes, and the remaining 23 are Fourier harmonics or beat frequencies of these two modes. The 2006 data set had five additional frequencies with amplitudes less than 1.5 mmag, and the 2007 data had one additional frequency. Analysis of the full 2006–2007 data set yields 22 of the 25 frequencies found in the individual seasons of data. There are no significant peaks in the spectrum other than these between 0 and 60 cycles day-1. The frequencies of the two main pulsation modes derived from the 2006 and 2007 observing seasons individually do not differ at the level of 3σ, and thus we find no conclusive evidence for period change over the span of these observations. However, the amplitude of changed significantly between the two seasons, while the amplitude of remained constant; amplitudes of the Fourier harmonics and beat frequencies of f1 also changed. Similar behavior was seen in the 1950s, and it is clear that VX Hydrae undergoes significant amplitude changes over time.

  1. No junctional communication between epithelial cells in hydra

    DEFF Research Database (Denmark)

    de Laat, S W; Tertoolen, L G; Grimmelikhuijzen, C J

    1980-01-01

    junctions between epithelial cells of hydra. However, until now, there has been no report published on whether these junctions enable the epithelial cells to exchange molecules of small molecular weight, as has been described in other organisms. Therefore we decided to investigate the communicative...... properties of the junctional membranes by electrophysiological methods and by intracellular-dye iontophoresis. We report here that no electrotonic coupling is detectable between epithelial cells of Hydra attenuata in: (1) intact animals, (2) head-regenerating animals, (3) cell re-aggregates, and (4) hydra...

  2. Automatic Clustering Using Multi-objective Particle Swarm and Simulated Annealing.

    Directory of Open Access Journals (Sweden)

    Ahmad Abubaker

    Full Text Available This paper puts forward a new automatic clustering algorithm based on Multi-Objective Particle Swarm Optimization and Simulated Annealing, "MOPSOSA". The proposed algorithm is capable of automatic clustering which is appropriate for partitioning datasets to a suitable number of clusters. MOPSOSA combines the features of the multi-objective based particle swarm optimization (PSO and the Multi-Objective Simulated Annealing (MOSA. Three cluster validity indices were optimized simultaneously to establish the suitable number of clusters and the appropriate clustering for a dataset. The first cluster validity index is centred on Euclidean distance, the second on the point symmetry distance, and the last cluster validity index is based on short distance. A number of algorithms have been compared with the MOPSOSA algorithm in resolving clustering problems by determining the actual number of clusters and optimal clustering. Computational experiments were carried out to study fourteen artificial and five real life datasets.

  3. Automatic Clustering Using Multi-objective Particle Swarm and Simulated Annealing.

    Science.gov (United States)

    Abubaker, Ahmad; Baharum, Adam; Alrefaei, Mahmoud

    2015-01-01

    This paper puts forward a new automatic clustering algorithm based on Multi-Objective Particle Swarm Optimization and Simulated Annealing, "MOPSOSA". The proposed algorithm is capable of automatic clustering which is appropriate for partitioning datasets to a suitable number of clusters. MOPSOSA combines the features of the multi-objective based particle swarm optimization (PSO) and the Multi-Objective Simulated Annealing (MOSA). Three cluster validity indices were optimized simultaneously to establish the suitable number of clusters and the appropriate clustering for a dataset. The first cluster validity index is centred on Euclidean distance, the second on the point symmetry distance, and the last cluster validity index is based on short distance. A number of algorithms have been compared with the MOPSOSA algorithm in resolving clustering problems by determining the actual number of clusters and optimal clustering. Computational experiments were carried out to study fourteen artificial and five real life datasets.

  4. 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.)

  5. CONCEPTUAL FRAMEWORK OF MULTI-OBJECTIVE PLANNING WITH A CASE STUDY

    Directory of Open Access Journals (Sweden)

    Mehmet Mısır

    2005-04-01

    Full Text Available Forests management design of the day focuses on protection as well as the sustainable use of forest values. The basic requirement of multi-objective forest management planning is identify and quantify forest values and to determine management objectives. The priorities of management objectives, however, must be decided. Decision support tools such as operation research techniques and GIS, therefore, have effectively been used in management planning process over the last decade. Designing spatial data base including graphical data such as stand map, soil map, road map and attribute data such as stand volume, increment, number of trees and determining forest values are necessary steps for preparing a comprehensive forest management plan. This study aims to; establish conceptual framework of Multi-objective planning and prepare forest values maps necessary for management planning by using multi-objective planning models.

  6. 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.

  7. Multi-Objective Feature Subset Selection using Non-dominated Sorting Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    A. Khan

    2015-02-01

    Full Text Available This paper presents an evolutionary algorithm based technique to solve multi-objective feature subset selection problem. The data used for classification contains large number of features called attributes. Some of these attributes are not relevant and needs to be eliminated. In classification procedure, each feature has an effect on the accuracy, cost and learning time of the classifier. So, there is a strong requirement to select a subset of the features before building the classifier. This proposed technique treats feature subset selection as multi-objective optimization problem. This research uses one of the latest multi-objective genetic algorithms (NSGA - II. The fitness value of a particular feature subset is measured by using ID3. The testing accuracy acquired is then assigned to the fitness value. This technique is tested on several datasets taken from the UCI machine repository. The experiments demonstrate the feasibility of using NSGA-II for feature subset selection.

  8. A new fuzzy multi-objective higher order moment portfolio selection model for diversified portfolios

    Science.gov (United States)

    Yue, Wei; Wang, Yuping

    2017-01-01

    Due to the important effect of the higher order moments to portfolio returns, the aim of this paper is to make use of the third and fourth moments for fuzzy multi-objective portfolio selection model. Firstly, in order to overcome the low diversity of the obtained solution set and lead to corner solutions for the conventional higher moment portfolio selection models, a new entropy function based on Minkowski measure is proposed as a new objective function and a novel fuzzy multi-objective weighted possibilistic higher order moment portfolio model is presented. Secondly, to solve the proposed model efficiently, a new multi-objective evolutionary algorithm is designed. Thirdly, several portfolio performance evaluation techniques are used to evaluate the performance of the portfolio models. Finally, some experiments are conducted by using the data of Shanghai Stock Exchange and the results indicate the efficiency and effectiveness of the proposed model and algorithm.

  9. 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 ...

  10. Multi-objective metaheuristics for preprocessing EEG data in brain-computer interfaces

    Science.gov (United States)

    Aler, Ricardo; Vega, Alicia; Galván, Inés M.; Nebro, Antonio J.

    2012-03-01

    In the field of brain-computer interfaces, one of the main issues is to classify the electroencephalogram (EEG) accurately. EEG signals have a good temporal resolution, but a low spatial one. In this article, metaheuristics are used to compute spatial filters to improve the spatial resolution. Additionally, from a physiological point of view, not all frequency bands are equally relevant. Both spatial filters and relevant frequency bands are user-dependent. In this article a multi-objective formulation for spatial filter optimization and frequency-band selection is proposed. Several multi-objective metaheuristics have been tested for this purpose. The experimental results show, in general, that multi-objective algorithms are able to select a subset of the available frequency bands, while maintaining or improving the accuracy obtained with the whole set. Also, among the different metaheuristics tested, GDE3, which is based on differential evolution, is the most useful algorithm in this context.

  11. 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.

  12. Two-phase application of multi-objective genetic algorithms in green building design

    Energy Technology Data Exchange (ETDEWEB)

    Wang, W.; Zmeureanu, R. [Concordia Univ., Centre for Building Studies, Montreal, PQ (Canada). Dept. of Building, Civil and Environmental Engineering; Rivard, H. [Ecole de Technologie Superieure, Montreal, PQ (Canada). Dept. of Construction Engineering

    2005-07-01

    The application of multi-objective genetic algorithms for green building design in two phases were presented in order to better help designers in the decision-making process. The purpose is to minimize two conflicting criteria: the life-cycle cost and the life-cycle environmental impact. Environmental impact criteria examined include energy and non-energy natural resources, global warming, and acidification. Variables focus on building envelope-related parameters. The application of multi-objective genetic algorithms is divided into two phases. The first phase intends to help designers in understanding the trade-off relationship between the two conflicting criteria. The second phase intends to refine the performance region that is of the designer's interest. The results after the two-phase application of the multi objective genetic algorithm were then presented. 13 refs., 4 tabs., 3 figs.

  13. Multi-Objective Optimization of Mechanical Running Conditions of Large Scale Statically Indeterminate Rotary Kiln

    Institute of Scientific and Technical Information of China (English)

    Hu Xiaoping; Xiao Yougang; Wang Guangbin

    2006-01-01

    Combined with the second rotary kiln of Alumina Factory in Great Wall Aluminum Company, the mechanics characteristics of statically indeterminate large-scale rotary kiln with variable cross-sections is analyzed. In order to adjusting the runing axis of rotary kiln, taking the force equilibrium of the rollers and the minimum of relative axis deflection as the optimization goal, the multi-objective optimization model of mechanical running conditions of kiln rotary is set up. The mechanical running conditions of the second rotary kiln after multi-objective optimization adjustment are compared with those before adjustment and after routine adjustment. It shows that multi-objective optimization adjustment can make axis as direct as possible and can distribute kiln loads equally.

  14. Design of multi-objective damping controller for gate-controlled series capacitor

    Indian Academy of Sciences (India)

    Amin Safari; Navid Rezaei

    2014-04-01

    This paper proposes an optimization procedure based on eigenvalues to carry out the stabilization function of the Gate-Controlled Series Capacitor (GCSC) in a power system. It is aimed to provide a reliable damping framework by means of a GCSC based multi-objective damping controller. The proposed method employs Particle Swarm Optimization (PSO) to search for optimal parameter settings of a widely used multi-objective lead-lag damping controller. The eigenvalue analysis is considered as the cornerstone of the performed studies in order to investigate the multi-objective methodology in which the unstable or lightly damped modes are scheduled to effectively shift to some prescribed stability zones in the s-plane. The effectiveness of the suggested approach in damping local and interarea oscillations modes in a multi-machine power system, over a wide range of loading conditions, is confirmed through eigenvalue analysis and time simulation.

  15. Application of a fast and elitist multi-objective genetic algorithm to Reactive Power Dispatch

    Directory of Open Access Journals (Sweden)

    Subramanian Ramesh

    2009-01-01

    Full Text Available This paper presents an Elitist Non-Dominated Sorting Genetic Algorithm version II (NSGA-II, for solving the Reactive Power Dispatch (RPD problem. The optimal RPD problem is a nonlinear constrained multi-objective optimization problem where the real power loss and the bus voltage deviations are to be minimized. Since the problem is treated as a true multi-objective optimization problem, different trade-off solutions are provided. The decision maker has an option to choose a solution among the different trade-off solutions provided in the pareto-optimal front. The standard IEEE 30-bus test system is used and the results show the effectiveness of NSGA-II and confirm its potential to solve the multi-objective RPD problem. The results obtained by NSGA-II are compared and validated with conventional weighted sum method using Real-coded Genetic Algorithm (RGA and NSGA.

  16. 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.

  17. Fibre positioning concept for the WEAVE spectrograph at the WHT

    Science.gov (United States)

    Lewis, Ian J.; Dalton, Gavin B.; Brock, Matthew; Gilbert, James; Abrams, Don C.; Aguerri, J. Alfonso L.; Bonifacio, Piercarlo; Middleton, Kevin; Trager, Scott C.

    2014-07-01

    WEAVE is the next-generation wide-field optical spectroscopy facility for the William Herschel Telescope (WHT) in La Palma, Canary Islands, Spain. It is a multi-object "pick and place" fibre fed spectrograph with more than one thousand fibres behind a new dedicated 2° prime focus corrector, This is similar in concept to the Australian Astronomical Observatory's 2dF instrument1 with two observing plates, one of which is observing the sky while other is being reconfigured by a robotic fibre positioner. It will be capable of acquiring more than 10000 star or galaxy spectra a night. The WEAVE positioner concept uses two robots working in tandem in order to reconfigure a fully populated field within the expected 1 hour dwell-time for the instrument (a good match between the required exposure times and the limit of validity for a given configuration due to the effects of differential refraction).

  18. Multi Objective Optimization Using Biogeography Based Optimization and Differentional Evolution Algorithm

    Directory of Open Access Journals (Sweden)

    Samira Abdi

    2012-11-01

    The proposed algorithm (MOBBO/DE makes the use of nondominated sorting approach improve the convergence ability efficiently and hence it can generate the promising candidate solutions. It also combines crowding distance to guarantee the diversity of Pareto optimal solutions. The proposed approach is validated using several test functions and some metrics taken from the standard literature on evolutionary multi-objective optimization. Results indicate that the approach is highly competitive and that can be considered a viable alternative to solve multi-objective optimization problems.

  19. 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.

  20. Multi-Objective Hybrid Optimal Control for Multiple-Flyby Interplanetary Mission Design Using Chemical Propulsion

    Science.gov (United States)

    Englander, Jacob; Vavrina, Matthew

    2015-01-01

    The customer (scientist or project manager) most often does not want just one point solution to the mission design problem Instead, an exploration of a multi-objective trade space is required. For a typical main-belt asteroid mission the customer might wish to see the trade-space of: Launch date vs. Flight time vs. Deliverable mass, while varying the destination asteroid, planetary flybys, launch year, etcetera. To address this question we use a multi-objective discrete outer-loop which defines many single objective real-valued inner-loop problems.

  1. Recognition of Gene Acceptor Site Based on Multi-objective Optimization

    Institute of Scientific and Technical Information of China (English)

    Jing ZHAO; Yue-Min ZHU; Pei-Ming SONG; Qing FANG; Jian-Hua LUO

    2005-01-01

    A new method for predicting the gene acceptor site based on multi-objective optimization is introduced in this paper. The models for the acceptor, branch and distance between acceptor site and branch site were constructed according to the characteristics of the sequences from the exon-intron database and using common biological knowledge. The acceptor function, branch function and distance function were defined respectively, and the multi-objective optimization model was constructed to recognize the splice site. The test results show that the algorithm used in this study performs better than the SplicePredictor,which is one of the leading acceptor site detectors.

  2. Visual Multi-Object Tracking in the Presence of Cluttered Scenes

    Directory of Open Access Journals (Sweden)

    Xu-Sheng Gan

    2013-07-01

    Full Text Available The aim of this study was to investigate the visual multi-object tracking in the presence of cluttered scenes. A improved algorithm of fusing multi-source information including location and color evidences were introduced based on Dezert-Smarandache Theory (DSmT and Particle Filters (PF. Results showed that the conflict strategy and DSmT combination model were available and the proposed approach exhibited a significantly better performance for dealing with high conflict between evidences than a conventional PF. The suggested approach can easily be generalized to deal with larger number of visual multi-object and additional cues in the presence of cluttered scenes.

  3. 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

  4. Multi-Objective Optimization and Analysis Model of Sintering Process Based on BP Neural Network

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jun-hong; XIE An-guo; SHEN Feng-man

    2007-01-01

    A multi-objective optimization and analysis model of the sintering process based on BP neural network is presented. Genetic algorithms are combined to simplify the BP neural network, which can reduce the learning time and increase the forecasting accuracy of the network model. This model has been experimented in the sintering process, and the production cost, the energy consumption, the quality (revolving intensity), and the output are considered at the same time. Moreover, the relation between some factors and the multi-objectives has been analyzed, and the results are consistent with the process. Different objectives are emphasized at different practical periods, and this can provide a theoretical basis for the manager.

  5. Multi-objective robust controller synthesis for discrete-time systems with convex polytopic uncertain domain

    Institute of Scientific and Technical Information of China (English)

    ZHANG Yan-hu; YAN Wen-jun; LU Jian-ning; ZHAO Guang-zhou

    2005-01-01

    Multi-objective robust state-feedback controller synthesis problems for linear discrete-time uncertain systems are addressed. Based on parameter-dependent Lyapunov functions, the Gl2 and GH2 norm expressed in terms of LMI (Linear Matrix Inequality) characterizations are further generalized to cope with the robust analysis for convex polytopic uncertain system.Robust state-feedback controller synthesis conditions are also derived for this class of uncertain systems. Using the above results,multi-objective state-feedback controller synthesis procedures which involve the LMI optimization technique are developed and less conservative than the existing one. An illustrative example verified the validity of the approach.

  6. A New Definition and Calculation Model for Evolutionary Multi-Objective Optimization

    Institute of Scientific and Technical Information of China (English)

    Zhou Ai-min; Kang Li-shan; Chen Yu-ping; Huang Yu-zhen

    2003-01-01

    We present a new definition (Evolving Solutions) for Multi objective Optimization Problem (MOP) to answer the basic question (what's multi-objective optimal solution?) and advance an asynchronous evolutionary model (MINT Model) to solve MOPs. The new theory is based on our understanding of the natural evolution and the analysis of the difference between natural evolution and MOP, thus it is not only different from the Converting Optimization but also different from Pareto Optimization.Some tests prove that our new theory may conquer disadvantages of the upper two methods to some extent.

  7. Multi-objective dynamic optimization model for China's road transport energy technology switching

    Institute of Scientific and Technical Information of China (English)

    Dan GAO; Zheng LI; Feng FU; Linwei MA

    2009-01-01

    Deducting the future switching of the road transport energy technology is one of the key preconditions for relative technology development planning. However,one of the difficulties is to address the issue of multi-objective and conflicting constrains, e.g., minimizing the climate mitigation or minimizing economic cost. In this paper, a dynamic optimization model was established, which can be used to analyze the road transport energy technology switching under multi-objective constrains.Through one case study, a series of solutions could be derived to provide decision-makers with the flexibility to choose the appropriate solution with respect to the given situation.

  8. 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 aimi...... calculation is included in the metaheuristics approach to allow taking into account the network constraints. A case study with a 33-bus distribution network and 1800 V2G resources is used to illustrate the performance of the proposed method....

  9. Multi-Objective Optimization of A Semisubmersible for Ultra-Deep Water

    Institute of Scientific and Technical Information of China (English)

    CHEN Xin-quan; TAN Jia-hua

    2008-01-01

    Semisubmersible will work well when oil exploitation goes to ultra-deep water because of its variable load capacities, and good motion performance in extreme waves. It is considered to be a main type of platform while the water depth is more than 3000 meters. This paper establishes a multi-objective optimization model of semisubmersible for ultra-deep water, and it is solved by a multi-objective genetic algorithm-NSGA-II. The model is applied to a practical design, and Pareto results are obtained. The effectiveness of the method is verified by hydrodynamic analysis.

  10. IR wireless cluster synapses of HYDRA very large neural networks

    Science.gov (United States)

    Jannson, Tomasz; Forrester, Thomas

    2008-04-01

    RF/IR wireless (virtual) synapses are critical components of HYDRA (Hyper-Distributed Robotic Autonomy) neural networks, already discussed in two earlier papers. The HYDRA network has the potential to be very large, up to 10 11-neurons and 10 18-synapses, based on already established technologies (cellular RF telephony and IR-wireless LANs). It is organized into almost fully connected IR-wireless clusters. The HYDRA neurons and synapses are very flexible, simple, and low-cost. They can be modified into a broad variety of biologically-inspired brain-like computing capabilities. In this third paper, we focus on neural hardware in general, and on IR-wireless synapses in particular. Such synapses, based on LED/LD-connections, dominate the HYDRA neural cluster.

  11. Prime focus spectrograph: Subaru's future

    OpenAIRE

    Sugai, Hajime; Dekany, Richard G.; Ellis, Richard S.; Seiffert, Michael D.; Smith, Roger M.

    2012-01-01

    The Prime Focus Spectrograph (PFS) of the Subaru Measurement of Images and Redshifts (SuMIRe) project has been endorsed by Japanese community as one of the main future instruments of the Subaru 8.2-meter telescope at Mauna Kea, Hawaii. This optical/near-infrared multi-fiber spectrograph targets cosmology with galaxy surveys, Galactic archaeology, and studies of galaxy/AGN evolution. Taking advantage of Subaru’s wide field of view, which is further extended with the recently completed Wide Fie...

  12. Evidence that polycystins are involved in Hydra cnidocyte discharge.

    Science.gov (United States)

    McLaughlin, Susan

    2017-03-01

    Like other cnidarians, the freshwater organism Hydra is characterized by the possession of cnidocytes (stinging cells). Most cnidocytes are located on hydra tentacles, where they are organized along with sensory cells and ganglion cells into battery complexes. The function of the battery complexes is to integrate multiple types of stimuli for the regulation of cnidocyte discharge. The molecular mechanisms controlling the discharge of cnidocytes are not yet fully understood, but it is known that discharge depends on extracellular Ca(2+) and that mechanically induced cnidocyte discharge can be enhanced by the presence of prey extracts and other chemicals. Experiments in this paper show that a PKD2 (polycystin 2) transient receptor potential (TRP) channel is expressed in hydra tentacles and bases. PKD2 (TRPP) channels belong to the TRP channel superfamily and are non-selective Ca(2+) channels involved in the transduction of both mechanical and chemical stimuli in other organisms. Non-specific PKD2 channel inhibitors Neo (neomycin) and Gd(3+) (gadolinium) inhibit both prey capture and cnidocyte discharge in hydra. The PKD2 activator Trip (triptolide) enhances cnidocyte discharge in both starved and satiated hydra and reduces the inhibition of cnidocyte discharge caused by Neo. PKD1 and 2 proteins are known to act together to transduce mechanical and chemical stimuli; in situ hybridization experiments show that a PKD1 gene is expressed in hydra tentacles and bases, suggesting that polycystins play a direct or indirect role in cnidocyte discharge.

  13. 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

  14. 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.

  15. Accelerating solving the dynamic multi-objective nework design problem using response surface methods

    NARCIS (Netherlands)

    Wismans, Luc J.J.; Berkum, van Eric C.; Bliemer, Michiel C.J.

    2011-01-01

    Multi objective optimization of externalities of traffic solving a network design problem in which Dynamic Traffic Management measures are used, is time consuming while heuristics are needed and solving the lower level requires solving the dynamic user equilibrium problem. Use of response surface me

  16. Multi-objective optimization in formation tasks of leather and fur materials

    Directory of Open Access Journals (Sweden)

    Ольга Викторовна Сангинова

    2014-09-01

    Full Text Available The comparative analysis of the efficiency of different ways to obtain a compromise solution in the multi-objective constrained optimization tasks has been conducted. The analysis was performed for a number of innovative technologies of leather and fur materials forming.

  17. Improving multi-objective reservoir operation optimization with sensitivity-informed problem decomposition

    Science.gov (United States)

    Chu, J. G.; Zhang, C.; Fu, G. T.; Li, Y.; Zhou, H. C.

    2015-04-01

    This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce the computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed problem decomposition dramatically reduces the computational demands required for attaining high quality approximations of optimal tradeoff relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed problem decomposition and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform problem decomposition when solving the complex multi-objective reservoir operation problems.

  18. Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction

    Science.gov (United States)

    Chu, J.; Zhang, C.; Fu, G.; Li, Y.; Zhou, H.

    2015-08-01

    This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed method dramatically reduces the computational demands required for attaining high-quality approximations of optimal trade-off relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed dimension reduction and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform dimension reduction of optimization problems when solving complex multi-objective reservoir operation problems.

  19. Analysis of Various Multi-Objective Optimization Evolutionary Algorithms for Monte Carlo Treatment Planning System

    CERN Document Server

    Tydrichova, Magdalena

    2017-01-01

    In this project, various available multi-objective optimization evolutionary algorithms were compared considering their performance and distribution of solutions. The main goal was to select the most suitable algorithms for applications in cancer hadron therapy planning. For our purposes, a complex testing and analysis software was developed. Also, many conclusions and hypothesis have been done for the further research.

  20. 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.

  1. An interactive visualization tool for the analysis of multi-objective embedded systems design space exploration

    NARCIS (Netherlands)

    Taghavi, T.; Pimentel, A.D.

    2011-01-01

    The design of today’s embedded systems involves a complex Design Space Exploration (DSE) process. Typically, multiple and conflicting criteria (objectives) should be optimized simultaneously such as performance, power, cost, etc. Usually, Multi-Objective Evolutionary Algorithms (MOEAs) are used to

  2. An environmental-economic framework to support multi-objective policy-making

    NARCIS (Netherlands)

    Pacini, G.C.

    2003-01-01

    Keywords: environmental accounting, environmental indicators, farming systems, sustainability, organic farming, ecological-economic modelling, spatial analysis, multi-objective policy-making, opportunity cost.There is a growing awareness in present-day society of the potent

  3. Multi-objective random search algorithm for simultaneously optimizing wind farm layout and number of turbines

    DEFF Research Database (Denmark)

    Feng, Ju; Shen, Wen Zhong; Xu, Chang

    2016-01-01

    A new algorithm for multi-objective wind farm layout optimization is presented. It formulates the wind turbine locations as continuous variables and is capable of optimizing the number of turbines and their locations in the wind farm simultaneously. Two objectives are considered. One is to maximi...

  4. Multi-objective optimization of riparian buffer networks; valuing present and future benefits

    Science.gov (United States)

    Multi-objective optimization has emerged as a popular approach to support water resources planning and management. This approach provides decision-makers with a suite of management options which are generated based on metrics that represent different social, economic, and environ...

  5. Multi-objective radiomics model for predicting distant failure in lung SBRT

    Science.gov (United States)

    Zhou, Zhiguo; Folkert, Michael; Iyengar, Puneeth; Westover, Kenneth; Zhang, Yuanyuan; Choy, Hak; Timmerman, Robert; Jiang, Steve; Wang, Jing

    2017-06-01

    Stereotactic body radiation therapy (SBRT) has demonstrated high local control rates in early stage non-small cell lung cancer patients who are not ideal surgical candidates. However, distant failure after SBRT is still common. For patients at high risk of early distant failure after SBRT treatment, additional systemic therapy may reduce the risk of distant relapse and improve overall survival. Therefore, a strategy that can correctly stratify patients at high risk of failure is needed. The field of radiomics holds great potential in predicting treatment outcomes by using high-throughput extraction of quantitative imaging features. The construction of predictive models in radiomics is typically based on a single objective such as overall accuracy or the area under the curve (AUC). However, because of imbalanced positive and negative events in the training datasets, a single objective may not be ideal to guide model construction. To overcome these limitations, we propose a multi-objective radiomics model that simultaneously considers sensitivity and specificity as objective functions. To design a more accurate and reliable model, an iterative multi-objective immune algorithm (IMIA) was proposed to optimize these objective functions. The multi-objective radiomics model is more sensitive than the single-objective model, while maintaining the same levels of specificity and AUC. The IMIA performs better than the traditional immune-inspired multi-objective algorithm.

  6. Solutions of Multi Objective Fuzzy Transportation Problems with Non-Linear Membership Functions

    Directory of Open Access Journals (Sweden)

    Dr. M. S. Annie Christi

    2016-11-01

    Full Text Available Multi-objective transportation problem with fuzzy interval numbers are considered. The solution of linear MOTP is obtained by using non-linear membership functions. The optimal compromise solution obtained is compared with the solution got by using a linear membership function. Some numerical examples are presented to illustrate this.

  7. SOME RATIONALITY CONDITIONS OF JOINT EFFICIENT MAPPING IN GROUP MULTI-OBJECTIVE PROGRAMMING

    Institute of Scientific and Technical Information of China (English)

    Jing LI; Yuda HU

    2007-01-01

    The joint efficient ordering method is a fundamental method of ordering alternatives in group multi-objective programming problems. In this paper, the rational properties of the joint efficient mapping corresponding to the joint efficient ordering method are studied, and some necessary conditions of this mapping are proven.

  8. Study on the Reliability Evaluation of Qualitative Indices in Multi-Objective Decision

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Qualitative indices in multi-objective decision can usually be evaluated and measured by mathematical methods or models, but the obtained results are sometimes inaccurate because of fuzziness of indices. To improve the accuracy and reliability of the evaluation results, set-value statistic principle is applied, and accordingly four evaluation methods are obtained. Meanwhile, these methods are compared briefly.

  9. Performance of a genetic algorithm for solving the multi-objective, multimodel transportation network design problem

    NARCIS (Netherlands)

    Brands, Ties; van Berkum, Eric C.

    2014-01-01

    The optimization of infrastructure planning in a multimodal network is defined as a multi-objective network design problem, with accessibility, use of urban space by parking, operating deficit and climate impact as objectives. Decision variables are the location of park and ride facilities, train

  10. A Multi-objective Optimization Application in Friction Stir Welding: Considering Thermo-mechanical Aspects

    DEFF Research Database (Denmark)

    Tutum, Cem Celal; Hattel, Jesper Henri

    2010-01-01

    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 thermomechanical...

  11. Multi-objective Optimization of Process Parameters in Friction Stir Welding

    DEFF Research Database (Denmark)

    Tutum, Cem Celal; Hattel, Jesper Henri

    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...

  12. 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.

  13. 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.

  14. 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.

  15. Design Optimization of an Axial Fan Blade Through Multi-Objective Evolutionary Algorithm

    Science.gov (United States)

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

    2010-06-01

    This paper presents design optimization of an axial fan blade with hybrid multi-objective evolutionary algorithm (hybrid MOEA). Reynolds-averaged Navier-Stokes equations with shear stress transport turbulence model are discretized by the finite volume approximations and solved on hexahedral grids for the flow analyses. The validation of the numerical results was performed with the experimental data for the axial and tangential velocities. Six design variables related to the blade lean angle and blade profile are selected and the Latin hypercube sampling of design of experiments is used to generate design points within the selected design space. Two objective functions namely total efficiency and torque are employed and the multi-objective optimization is carried out to enhance total efficiency and to reduce the torque. The flow analyses are performed numerically at the designed points to obtain values of the objective functions. The Non-dominated Sorting of Genetic Algorithm (NSGA-II) with ɛ -constraint strategy for local search coupled with surrogate model is used for multi-objective optimization. The Pareto-optimal solutions are presented and trade-off analysis is performed between the two competing objectives in view of the design and flow constraints. It is observed that total efficiency is enhanced and torque is decreased as compared to the reference design by the process of multi-objective optimization. The Pareto-optimal solutions are analyzed to understand the mechanism of the improvement in the total efficiency and reduction in torque.

  16. 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

  17. Ensemble-based multi-objective optimization of on-off control devices under geological uncertainty

    NARCIS (Netherlands)

    Fonseca, R.M.; Leeuwenburgh, O.; Rossa, E.D.; Hof, P.M.J. van den; Jansen, J.D.

    2015-01-01

    We consider robust ensemble-based (EnOpt) multi-objective production optimization of on-off inflow control devices (ICDs) for a sector model inspired on a real-field case. The use of on-off valves as optimization variables leads to a discrete control problem. We propose a re-parameterization of such

  18. 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.

  19. Robust Multi-Objective PQ Scheduling for Electric Vehicles in Flexible Unbalanced Distribution Grids

    DEFF Research Database (Denmark)

    Knezovic, Katarina; Soroudi, Alireza; Marinelli, Mattia

    2017-01-01

    With increased penetration of distributed energy resources and electric vehicles (EVs), different EV management strategies can be used for mitigating adverse effects and supporting the distribution grid. This paper proposes a robust multi-objective methodology for determining the optimal day...

  20. Multi-Objective Differential Evolution for Automatic Clustering with Application to Micro-Array Data Analysis

    Directory of Open Access Journals (Sweden)

    Sang Yong Han

    2009-05-01

    Full Text Available This paper applies the Differential Evolution (DE algorithm to the task of automatic fuzzy clustering in a Multi-objective Optimization (MO framework. It compares the performances of two multi-objective variants of DE over the fuzzy clustering problem, where two conflicting fuzzy validity indices are simultaneously optimized. The resultant Pareto optimal set of solutions from each algorithm consists of a number of non-dominated solutions, from which the user can choose the most promising ones according to the problem specifications. A real-coded representation of the search variables, accommodating variable number of cluster centers, is used for DE. The performances of the multi-objective DE-variants have also been contrasted to that of two most well-known schemes of MO clustering, namely the Non Dominated Sorting Genetic Algorithm (NSGA II and Multi-Objective Clustering with an unknown number of Clusters K (MOCK. Experimental results using six artificial and four real life datasets of varying range of complexities indicate that DE holds immense promise as a candidate algorithm for devising MO clustering schemes.

  1. Performance of a genetic algorithm for solving the multi-objective, multimodel transportation network design problem

    NARCIS (Netherlands)

    Brands, T.; Berkum, van E.C.

    2014-01-01

    The optimization of infrastructure planning in a multimodal network is defined as a multi-objective network design problem, with accessibility, use of urban space by parking, operating deficit and climate impact as objectives. Decision variables are the location of park and ride facilities, train st

  2. Multi-objective differential evolution for automatic clustering with application to micro-array data analysis.

    Science.gov (United States)

    Suresh, Kaushik; Kundu, Debarati; Ghosh, Sayan; Das, Swagatam; Abraham, Ajith; Han, Sang Yong

    2009-01-01

    This paper applies the Differential Evolution (DE) algorithm to the task of automatic fuzzy clustering in a Multi-objective Optimization (MO) framework. It compares the performances of two multi-objective variants of DE over the fuzzy clustering problem, where two conflicting fuzzy validity indices are simultaneously optimized. The resultant Pareto optimal set of solutions from each algorithm consists of a number of non-dominated solutions, from which the user can choose the most promising ones according to the problem specifications. A real-coded representation of the search variables, accommodating variable number of cluster centers, is used for DE. The performances of the multi-objective DE-variants have also been contrasted to that of two most well-known schemes of MO clustering, namely the Non Dominated Sorting Genetic Algorithm (NSGA II) and Multi-Objective Clustering with an unknown number of Clusters K (MOCK). Experimental results using six artificial and four real life datasets of varying range of complexities indicate that DE holds immense promise as a candidate algorithm for devising MO clustering schemes.

  3. 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.

  4. Multi Objective Optimization for Calibration and Efficient Uncertainty Analysis of Computationally Expensive Watershed Models

    Science.gov (United States)

    Akhtar, T.; Shoemaker, C. A.

    2011-12-01

    Assessing the sensitivity of calibration results to different calibration criteria can be done through multi objective optimization that considers multiple calibration criteria. This analysis can be extended to uncertainty analysis by comparing the results of simulation of the model with parameter sets from many points along a Pareto Front. In this study we employ multi-objective optimization in order to understand which parameter values should be used for flow parameters of a SWAT model, (Soil and Water Assessment Tool) designed to simulate flow in the Cannonsville Reservoir in upstate New York. The comprehensive analysis procedure encapsulates identification of suitable objectives, analysis of trade-offs obtained through multi-objective optimization, and the impact of the trade-offs uncertainty. Examples of multiple criteria can include a) quality of the fit in different seasons, b) quality of the fit for high flow events and for low flow events, c) quality of the fit for different constituents (e.g. water versus nutrients). Many distributed watershed models are computationally expensive and include a large number of parameters that are to be calibrated. Efficient optimization algorithms are hence needed to find good solutions to multi-criteria calibration problems in a feasible amount of time. We apply a new algorithm called Gap Optimized Multi-Objective Optimization using Response Surfaces (GOMORS), for efficient multi-criteria optimization of the Cannonsville SWAT watershed calibration problem. GOMORS is a stochastic optimization method, which makes use of Radial Basis Functions for approximation of the computationally expensive objectives. GOMORS performance is also compared against other multi-objective algorithms ParEGO and NSGA-II. ParEGO is a kriging based efficient multi-objective optimization algorithm, whereas NSGA-II is a well-known multi-objective evolutionary optimization algorithm. GOMORS is more efficient than both ParEGO and NSGA-II in providing

  5. 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.

  6. 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

  7. 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.

  8. A fast new cadioptric design for fiber-fed spectrographs

    CERN Document Server

    Saunders, Will

    2012-01-01

    The next generation of massively multiplexed multi-object spectrographs (DESpec, SUMIRE, BigBOSS, 4MOST, HECTOR) demand fast, efficient and affordable spectrographs, with higher resolutions (R = 3000-5000) than current designs. Beam-size is a (relatively) free parameter in the design, but the properties of VPH gratings are such that, for fixed resolution and wavelength coverage, the effect on beam-size on overall VPH efficiency is very small. For alltransmissive cameras, this suggests modest beam-sizes (say 80-150mm) to minimize costs; while for cadioptric (Schmidt-type) cameras, much larger beam-sizes (say 250mm+) are preferred to improve image quality and to minimize obstruction losses. Schmidt designs have benefits in terms of image quality, camera speed and scattered light performance, and recent advances such as MRF technology mean that the required aspherics are no longer a prohibitive cost or risk. A new Schmidt/Maksutov-derived design is presented, which differs from previous designs in having the det...

  9. Economic and environmental multi-objective optimization to evaluate the impact of Belgian policy on solar power and electric vehicles

    OpenAIRE

    De Schepper, Ellen; Van Passel, Steven; Lizin, Sebastien; Vincent, Thomas; Martin, Benjamin; Gandibleux, Xavier

    2015-01-01

    This research uses multi-objective optimization to determine the optimal mixture of energy and transportation technologies, while optimizing economic and environmental impacts. We demonstrate the added value of using multi-objective mixed integer linear programming (MOMILP) considering economies of scale versus using continuous multi-objective linear programming (MOLP) assuming average cost intervals. This paper uses an improved version to solve MOMILPs exactly (Vincent, et al. 2013). To diff...

  10. Multi-Objective Optimization with Function Approximation Including Application to Computationally Expensive Groundwater Remediation Design

    Science.gov (United States)

    Akhtar, T.; Shoemaker, C. A.

    2009-12-01

    Water Resources design decisions frequently entail trade-offs between conflicting objectives, for instance cost minimization and contaminant(s) concentration minimization. Multi-objective optimization methods (including those based on evolutionary methods) typically require a very large number of simulations to find a solution. Many groundwater remediation problems are modeled by computationally intensive systems of Partial Differential Equations and simulations. Hence it is desirable that these models are calibrated via algorithms that require less number of simulations. A new strategy called Gap Optimized Multi-Objective Optimization using Response Surfaces (GOMORS) is proposed for multi-objective optimization of computationally expensive problems. A multi-objective management framework is devised to analyze the trade-offs between conflicting objectives. We will present applications to test functions and to a groundwater contamination problem. The pumping rates at different well locations and management periods are the decision variables, and cost and contaminant concentration are the objectives to be minimized. The optimization strategy is iterative and makes use of Radial Basic Functions to develop response surfaces as an approximation of the computationally expensive objectives. A novel method called the Gap Optimization method is introduced. The gap optimization method incorporates use of a multi-objective evolutionary optimization (MOEA) method that is applied to select the next point for expensive evaluation and consequent improvement of the surrogate model. In order to provide sound alternatives to the decision makers, the evaluation point selection procedure strives to ensure that the final trade-off curve generated from the algorithm is close to the true Pareto front and includes a diverse set of solutions. After the final iteration, a set of candidate solutions is selected via the iterative Gap Optimization procedure and the last MOEA iteration, and

  11. Constant mortality and fertility over age in Hydra.

    Science.gov (United States)

    Schaible, Ralf; Scheuerlein, Alexander; Dańko, Maciej J; Gampe, Jutta; Martínez, Daniel E; Vaupel, James W

    2015-12-22

    Senescence, the increase in mortality and decline in fertility with age after maturity, was thought to be inevitable for all multicellular species capable of repeated breeding. Recent theoretical advances and compilations of data suggest that mortality and fertility trajectories can go up or down, or remain constant with age, but the data are scanty and problematic. Here, we present compelling evidence for constant age-specific death and reproduction rates in Hydra, a basal metazoan, in a set of experiments comprising more than 3.9 million days of observations of individual Hydra. Our data show that 2,256 Hydra from two closely related species in two laboratories in 12 cohorts, with cohort age ranging from 0 to more than 41 y, have extremely low, constant rates of mortality. Fertility rates for Hydra did not systematically decline with advancing age. This falsifies the universality of the theories of the evolution of aging that posit that all species deteriorate with age after maturity. The nonsenescent life history of Hydra implies levels of maintenance and repair that are sufficient to prevent the accumulation of damage for at least decades after maturity, far longer than the short life expectancy of Hydra in the wild. A high proportion of stem cells, constant and rapid cell turnover, few cell types, a simple body plan, and the fact that the germ line is not segregated from the soma are characteristics of Hydra that may make nonsenescence feasible. Nonsenescence may be optimal because lifetime reproduction may be enhanced more by extending adult life spans than by increasing daily fertility.

  12. A multi objective geometric programming approach for electronic product pricing problem

    Directory of Open Access Journals (Sweden)

    Mohsen Fathollah Bayati

    2011-07-01

    Full Text Available Nowadays electronic commerce plays an important role in many business activities, operations, and transaction processing. The recent advances on e-businesses have created tremendous opportunities to increase profitability. This paper presents a multi-objective marketing planning model which simultaneously determines efficient marketing expenditure, service cost and product's selling price in two competitive markets. To solve the proposed model, we discuss a multi-objective geometric programming (GP approach based on compromise programming method. Since our proposed model is a signomial GP and global optimality is not guaranteed for the problem, we transform the model to posynomial form. Finally, the solution procedure is illustrated via a numerical example and a sensitivity analysis is presented.

  13. 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.

  14. 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.

  15. Multi-objective process parameter optimization for energy saving in injection molding process

    Institute of Scientific and Technical Information of China (English)

    Ning-yun LU; Gui-xia GONG; Yi YANG; Jian-hua LU

    2012-01-01

    This paper deals with a multi-objective parameter optimization framework for energy saving in injection molding process.It combines an experimental design by Taguchi's method,a process analysis by analysis of variance (ANOVA),a process modeling algorithm by artificial neural network (ANN),and a multi-objective parameter optimization algorithm by genetic algorithm (GA)-based lexicographic method.Local and global Pareto analyses show the trade-off between product quality and energy consumption.The implementation of the proposed framework can reduce the energy consumption significantly in laboratory scale tests,and at the same time,the product quality can meet the pre-determined requirements.

  16. A modified interactive procedure to solve multi-objective group decision making problem

    Directory of Open Access Journals (Sweden)

    Mohammad Izadikhah

    2014-08-01

    Full Text Available Multi-objective optimization and multiple criteria decision making problems are the process of designing the best alternative by considering the incommensurable and conflicting objectives simultaneously. One of the first interactive procedures to solve multiple criteria decision making problems is STEM method. In this paper we propose a modified interactive procedure based on STEM method by calculating the weight vector of objectives which emphasize that more important objectives be closer to ideal one. We use the AHP and TOPSIS method to find these weights and develop a multi-objective group decision making procedure. Therefore the presented method tries to increase the rate of satisfactoriness of the obtained solution. Finally, a numerical example for illustration of the new method is given to clarify the main results developed in this paper.

  17. Extraction of battery parameters of the equivalent circuit model using a multi-objective genetic algorithm

    Science.gov (United States)

    Brand, Jonathan; Zhang, Zheming; Agarwal, Ramesh K.

    2014-02-01

    A simple but reasonably accurate battery model is required for simulating the performance of electrical systems that employ a battery for example an electric vehicle, as well as for investigating their potential as an energy storage device. In this paper, a relatively simple equivalent circuit based model is employed for modeling the performance of a battery. A computer code utilizing a multi-objective genetic algorithm is developed for the purpose of extracting the battery performance parameters. The code is applied to several existing industrial batteries as well as to two recently proposed high performance batteries which are currently in early research and development stage. The results demonstrate that with the optimally extracted performance parameters, the equivalent circuit based battery model can accurately predict the performance of various batteries of different sizes, capacities, and materials. Several test cases demonstrate that the multi-objective genetic algorithm can serve as a robust and reliable tool for extracting the battery performance parameters.

  18. 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

    acids, while maintaining sufficiently high growth rate and minimizing the secretion of undesired byproducts. Homo-productions of acetic, lactic and succinic acids were targeted as examples. Engineered E. coli strains capable of producing homo-acetic and homo-lactic acids could be developed by taking...... this systems approach for the minimal identification of gene knockout targets. Also, failure to predict effective gene knockout targets for the homo-succinic acid production suggests that the multi-objective optimization is useful in assessing the suitability of a microorganism as a host strain......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...

  19. Learned filters for object detection in multi-object visual tracking

    Science.gov (United States)

    Stamatescu, Victor; Wong, Sebastien; McDonnell, Mark D.; Kearney, David

    2016-05-01

    We investigate the application of learned convolutional filters in multi-object visual tracking. The filters were learned in both a supervised and unsupervised manner from image data using artificial neural networks. This work follows recent results in the field of machine learning that demonstrate the use learned filters for enhanced object detection and classification. Here we employ a track-before-detect approach to multi-object tracking, where tracking guides the detection process. The object detection provides a probabilistic input image calculated by selecting from features obtained using banks of generative or discriminative learned filters. We present a systematic evaluation of these convolutional filters using a real-world data set that examines their performance as generic object detectors.

  20. 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.

  1. A Hybrid Multi Objective Particle Swarm Optimization Method to Discover Biclusters in Microarray Data

    CERN Document Server

    lashkargir, Mohsen; Dastjerdi, Ahmad Baraani

    2009-01-01

    In recent years, with the development of microarray technique, discovery of useful knowledge from microarray data has become very important. Biclustering is a very useful data mining technique for discovering genes which have similar behavior. In microarray data, several objectives have to be optimized simultaneously and often these objectives are in conflict with each other. A Multi Objective model is capable of solving such problems. Our method proposes a Hybrid algorithm which is based on the Multi Objective Particle Swarm Optimization for discovering biclusters in gene expression data. In our method, we will consider a low level of overlapping amongst the biclusters and try to cover all elements of the gene expression matrix. Experimental results in the bench mark database show a significant improvement in both overlap among biclusters and coverage of elements in the gene expression matrix.

  2. A MULTI-OBJECTIVE ROBUST OPERATION MODEL FORELECTRONIC MARKET ENABLED SUPPLY CHAIN WITH UNCERTAIN DEMANDS

    Institute of Scientific and Technical Information of China (English)

    Jiawang XU; Xiaoyuan HUANG; Nina YAN

    2007-01-01

    A multi-objective robust operation model is proposed in this paper for an electronic market enabled supply chain consisting of multi-supplier and multi-customer with uncertain demands.Suppliers in this supply chain provide many kinds of products to different customers directly or through electronic market.Uncertain demands are described as a scenario set with certain probability; the supply chain operation model is constructed by using the robust optimization method based on scenario analyses.The operation model we proposed is a multi-objective programming problem satisfying several conflict objectives,such as meeting the demands of all customers,minimizing the system cost,the availabilities of suppliers' capacities not below a certain level,and robustness of decision to uncertain demands.The results of numerical examples proved that the solution of the model is most conservative; however,it can ensure the robustness of the operation of the supply chain effectively.

  3. Design for Sustainability of Industrial Symbiosis based on Emergy and Multi-objective Particle Swarm Optimization

    DEFF Research Database (Denmark)

    Ren, Jingzheng; Liang, Hanwei; Dong, Liang

    2016-01-01

    Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative...... approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex. Through incorporating the emergy theory, the model is formulated as a multi-objective approach that can optimize both the economic benefit and sustainable...... performance of the integrated industrial system. A set of emergy based evaluation index are designed. Multi-objective Particle Swarm Algorithm is proposed to solve the model, and the decision-makers are allowed to choose the suitable solutions form the Pareto solutions. An illustrative case has been studied...

  4. 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.

  5. Multi-objective Optimization of Industrial Purified Terephthalic Acid Oxidation Process

    Institute of Scientific and Technical Information of China (English)

    牟盛静; 苏宏业; 古勇; 褚健

    2003-01-01

    Multi-objective optimization of a purified terephthalic acid (PTA) oxidation unit is carried out in this paper by using a process model that has been proved to describe industrial process quite well. The model is a semiempirical structured into two series ideal continuously stirred tank reactor (CSTR) models. The optimal objectives include maximizing the yield or inlet rate and minimizing the concentration of 4-carboxy-benzaldhyde, which is the main undesirable intermediate product in the reaction process. The multi-objective optimization algorithm applied in this study is non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ). The performance of NSGA-II is further illustrated by application to the title process.

  6. Multi-objective mean-variance-skewness model for generation portfolio allocation in electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    Pindoriya, N.M.; Singh, S.N. [Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur 208016 (India); Singh, S.K. [Indian Institute of Management Lucknow, Lucknow 226013 (India)

    2010-10-15

    This paper proposes an approach for generation portfolio allocation based on mean-variance-skewness (MVS) model which is an extension of the classical mean-variance (MV) portfolio theory, to deal with assets whose return distribution is non-normal. The MVS model allocates portfolios optimally by considering the maximization of both the expected return and skewness of portfolio return while simultaneously minimizing the risk. Since, it is competing and conflicting non-smooth multi-objective optimization problem, this paper employed a multi-objective particle swarm optimization (MOPSO) based meta-heuristic technique to provide Pareto-optimal solution in a single simulation run. Using a case study of the PJM electricity market, the performance of the MVS portfolio theory based method and the classical MV method is compared. It has been found that the MVS portfolio theory based method can provide significantly better portfolios in the situation where non-normally distributed assets exist for trading. (author)

  7. Multi-objective Evolutionary Algorithms for MILP and MINLP in Process Synthesis

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    Steady-state non-dominated sorting genetic algorithm (SNSGA), a new form of multi-objective genetic algorithm, is implemented by combining the steady-state idea in steady-state genetic algorithms (SSGA) and the fitness assignment strategy of non-dominated sorting genetic algorithm (NSGA). The fitness assignment strategy is improved and a new self-adjustment scheme of σshare is proposed. This algorithm is proved to be very efficient both computationally and in terms of the quality of the Pareto fronts produced with five test problems including GA difficult problem and GA deceptive one. Finally, SNSGA is introduced to solve multi-objective mixed integer linear programming (MILP) and mixed integer non-linear programming (MINLP) problems in process synthesis.

  8. Multi-objective optimal power flow for active distribution network considering the stochastic characteristic of photovoltaic

    Science.gov (United States)

    Zhou, Bao-Rong; Liu, Si-Liang; Zhang, Yong-Jun; Yi, Ying-Qi; Lin, Xiao-Ming

    2017-05-01

    To mitigate the impact on the distribution networks caused by the stochastic characteristic and high penetration of photovoltaic, a multi-objective optimal power flow model is proposed in this paper. The regulation capability of capacitor, inverter of photovoltaic and energy storage system embedded in active distribution network are considered to minimize the expected value of active power the T loss and probability of voltage violation in this model. Firstly, a probabilistic power flow based on cumulant method is introduced to calculate the value of the objectives. Secondly, NSGA-II algorithm is adopted for optimization to obtain the Pareto optimal solutions. Finally, the best compromise solution can be achieved through fuzzy membership degree method. By the multi-objective optimization calculation of IEEE34-node distribution network, the results show that the model can effectively improve the voltage security and economy of the distribution network on different levels of photovoltaic penetration.

  9. An Archived Multi Objective Simulated Annealing Method to Discover Biclusters in Microarray Data

    Directory of Open Access Journals (Sweden)

    Mohsen Lashkargir

    2011-01-01

    Full Text Available With the advent of microarray technology it has been possible to measure thousands of expression values of genes in a single experiment. Analysis of large scale geonomics data, notably gene expression, has initially focused on clustering methods. Recently, biclustering techniques were proposed for revealing submatrices showing unique patterns. Biclustering or simultaneous clustering of both genes and conditions is challenging particularly for the analysis of high-dimensional gene expression data in information retrieval, knowledge discovery, and data mining. In biclustering of microarray data, several objectives have to be optimized simultaneously and often these objectives are in conflict with each other. A multi objective model is very suitable for solving this problem. Our method proposes a algorithm which is based on multi objective Simulated Annealing for discovering biclusters in gene expression data. Experimental result in bench mark data base present a significant improvement in overlap among biclusters and coverage of elements in gene expression and quality of biclusters.

  10. [Location selection for Shenyang urban parks based on GIS and multi-objective location allocation model].

    Science.gov (United States)

    Zhou, Yuan; Shi, Tie-Mao; Hu, Yuan-Man; Gao, Chang; Liu, Miao; Song, Lin-Qi

    2011-12-01

    Based on geographic information system (GIS) technology and multi-objective location-allocation (LA) model, and in considering of four relatively independent objective factors (population density level, air pollution level, urban heat island effect level, and urban land use pattern), an optimized location selection for the urban parks within the Third Ring of Shenyang was conducted, and the selection results were compared with the spatial distribution of existing parks, aimed to evaluate the rationality of the spatial distribution of urban green spaces. In the location selection of urban green spaces in the study area, the factor air pollution was most important, and, compared with single objective factor, the weighted analysis results of multi-objective factors could provide optimized spatial location selection of new urban green spaces. The combination of GIS technology with LA model would be a new approach for the spatial optimizing of urban green spaces.

  11. Solving Multi Objective ORPD Problem Using AIS Based Clonal Selection Algorithm with UPFC

    Directory of Open Access Journals (Sweden)

    B. Srinivasa Rao

    2017-03-01

    Full Text Available In this paper, a solution for the multi objective optimal reactive power dispatch problem by using an artificial immune system (AIS based clonal selection algorithm was presented. The proposed AIS based clonal selection algorithm uses cloning of antibodies and followed by hyper maturation to minimize the voltage stability index (L-index, voltage deviations at all load buses and the transmission real power losses by incorporating the multi type FACTS device namely the UPFC. The proposed algorithm also uses concepts of non dominated sorting and crowding distance comparison procedures to solve the multi objective optimization problem. Finally, a fuzzy decision maker strategy is applied to find the best compromise solution. The algorithm was implemented and tested on two standard IEEE 30-bus and 57-bus test systems with UPFC. The proposed results are compared with and without placing the UPFC by considering two objectives for optimization.

  12. Simulation and experimental validation of powertrain mounting bracket design obtained from multi-objective topology optimization

    Directory of Open Access Journals (Sweden)

    Qinghai Zhao

    2015-06-01

    Full Text Available A framework of multi-objective topology optimization for vehicle powertrain mounting bracket design with consideration of multiple static and dynamic loading conditions is developed in this article. Incorporating into the simplified isotropic material with penalization model, compromise programming method is employed to describe the multi-objective and multi-stiffness topology optimization under static loading conditions, whereas mean eigenvalue formulation is proposed to analyze vibration optimization. To yield well-behaved optimal topologies, minimum member size and draw constraint are settled for meeting manufacturing feasibility requirements. The ultimate mounting bracket is reconstructed based on the optimum results. Numerical analyses of the bracket are performed, followed by physical tests. It is proven that topology optimization methodology is promising and effective for vehicle component design.

  13. Evolution strategies and multi-objective optimization of permanent magnet motor

    DEFF Research Database (Denmark)

    Andersen, Søren Bøgh; Santos, Ilmar

    2012-01-01

    of evolution strategies, ES to effectively design and optimize parameters of permanent magnet motors. Single as well as multi-objective optimization procedures are carried out. A modified way of creating the strategy parameters for the ES algorithm is also proposed and has together with the standard ES...... algorithm undergone a comprehensive parameter study for the parameters ρ and λ. The results of this parameter study show a significant improvement in stability and speed with the use of the modified ES version. To find the most effective selector for a multi-objective optimization, MOO, of the motor...... a performance examination of 4 different selectors from the group of programs called PISA has been made and compared for MOO of the efficiency and cost of the motor. This performance examination showed that the indicator based evolutionary algorithm, IBEA, and hypervolume estimation algorithm, HypE, selectors...

  14. Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model

    Institute of Scientific and Technical Information of China (English)

    WANG Ya-lin; MA Jie; GUI Wei-hua; YANG Chun-hua; ZHANG Chuan-fu

    2006-01-01

    A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0 %, which effectively stabilizes the agglomerate compositions and the permeability.

  15. Multi-objective control for active vehicle suspension with wheelbase preview

    Science.gov (United States)

    Li, Panshuo; Lam, James; Cheung, Kie Chung

    2014-10-01

    This paper presents a multi-objective control method with wheelbase preview for active vehicle suspension. A four-degree-of-freedom half-car model with active suspension is considered in this study. H∞ norm and generalized H2 norm are used to improve ride quality and ensure that hard constraints are satisfied. Disturbances at the front wheel are obtained as preview information for the rear wheel. Static output-feedback is utilized in designing controllers, the solution is derived by iterative linear matrix inequality (ILMI) and cone complementarity linearization (CCL) algorithms. Simulation results confirm that multi-objective control with wheelbase preview achieves a significant improvement of ride quality (a maximum 27 percent and 60 percent improvement on vertical and angular acceleration, respectively) comparing with that of control without preview, while suspension deflections, tyre deflections and actuator forces remaining within given bounds. The extent of the improvement on the ride quality for different amount of preview information used is also illustrated.

  16. MULTI-OBJECTIVE OPTIMIZATION OF EDM PARAMETERS USING GREY RELATION ANALYSIS

    Directory of Open Access Journals (Sweden)

    N. RADHIKA

    2015-01-01

    Full Text Available This paper involves the multi-objective optimization of process parameters of AlSi10Mg/9 wt% alumina/3 wt% graphite in Electrical Discharge Machining for obtaining minimum surface roughness, minimum tool wear rate and maximum material removal rate. The important machining parameters were selected as peak current, flushing pressure and pulse-on time. Experiments were conducted by selecting different operating levels for the three parameters according to Taguchi’s Design of Experiments. The multi-objective optimization was performed using Grey Relation Analysis to determine the optimal solution. The Grey Relation Grade values were then analysed using Analysis of Variance to determine the most contributing input parameter. On analysis it was found that peak current, flushing pressure and pulse-on time had an influence of 61.36%, 17.81% and 8.09% respectively on the optimal solution.

  17. Solving A Kind of High Complexity Multi-Objective Problems by A Fast Algorithm

    Institute of Scientific and Technical Information of China (English)

    Zeng San-you; Ding Li-xin; Kang Li-shan

    2003-01-01

    A fast algorithm is proposed to solve a kind of high complexity multi-objective problems in this paper. It takes advantages of both the orthogonal design method to search evenly, and the statistical optimal method to speed up the computation. It is very suitable for solving high complexity problems, and quickly yields solutions which converge to the Pareto-optimal set with high precision and uniform distribution. Some complicated multi objective problems are solved by the algorithm and the results show that the algorithm is not only fast but also superior to other MCGAS and MOEAs, such as the currently efficient algorithm SPEA, in terms of the precision, quantity and distribution of solutions.

  18. A GA-based Multi-Objective Optimization for Service Restoration in Power Distribution Systems

    Science.gov (United States)

    Inagaki, Jun; Nakajima, Jun; Haseyama, Miki; Kitajima, Hideo

    Service restoration problem in distribution systems is formulated as a multi-objective optimization problem which is demanded not only for minimizing the amount of unrestored total loads but also for minimizing the number of the switching operations. The solution of the multi-objective optimization problem is usually obtained with a set of Pareto optimal solutions. The Pareto optimal solutions for the service restoration problem are useful for users to obtain their desired restoration by comparing a Pareto optimal solution with the others. However, the conventional methods cannot obtain plural Pareto optimal solutions in one trial. Therefore, this paper proposes a method for obtaining a Pareto optimal set for the service restoration problem with a genetic algorithm. The genetic algorithm produces many possible solutions in its search process. By utilizing this feature, the proposed method can obtain the Pareto optimal set.

  19. A multi-objective method for solving assembly line balancing problem

    Directory of Open Access Journals (Sweden)

    Hadi Pazoki Toroudi

    2017-01-01

    Full Text Available Modeling the simple assembly line balancing (SALB problem has covered a wide range of real-world applications. The recent advances in optimization problems have created the opportunities to tackle more challenging problems. This paper presents a multi-objective decision making problem to consider two objectives, cost and cycle time, for simple assembly line balancing. The problem is formulated as a mixed integer nonlinear optimization and the proposed study of this paper uses two metaheuristics to solve the resulted problem on some benchmark problems. The preliminary results have indicated that multi objective particle swarm optimization (MOPSO has provided better quality solutions while the hybrid method based on MOPSO and simulated annealing has yielded more non-dominated Pareto solutions.

  20. Multi-objective genetic algorithm for the optimization of a flat-plate solar thermal collector.

    Science.gov (United States)

    Mayer, Alexandre; Gaouyat, Lucie; Nicolay, Delphine; Carletti, Timoteo; Deparis, Olivier

    2014-10-20

    We present a multi-objective genetic algorithm we developed for the optimization of a flat-plate solar thermal collector. This collector consists of a waffle-shaped Al substrate with NiCrOx cermet and SnO(2) anti-reflection conformal coatings. Optimal geometrical parameters are determined in order to (i) maximize the solar absorptance α and (ii) minimize the thermal emittance ε. The multi-objective genetic algorithm eventually provides a whole set of Pareto-optimal solutions for the optimization of α and ε, which turn out to be competitive with record values found in the literature. In particular, a solution that enables α = 97.8% and ε = 4.8% was found.

  1. Multi-objective particle swarm and genetic algorithm for the optimization of the LANSCE linac operation

    Energy Technology Data Exchange (ETDEWEB)

    Pang, X., E-mail: xpang@lanl.gov; Rybarcyk, L.J.

    2014-03-21

    Particle swarm optimization (PSO) and genetic algorithm (GA) are both nature-inspired population based optimization methods. Compared to GA, whose long history can trace back to 1975, PSO is a relatively new heuristic search method first proposed in 1995. Due to its fast convergence rate in single objective optimization domain, the PSO method has been extended to optimize multi-objective problems. In this paper, we will introduce the PSO method and its multi-objective extension, the MOPSO, apply it along with the MOGA (mainly the NSGA-II) to simulations of the LANSCE linac and operational set point optimizations. Our tests show that both methods can provide very similar Pareto fronts but the MOPSO converges faster.

  2. Multi objective optimization of line pack management of gas pipeline system

    Science.gov (United States)

    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.

  3. Multi-objective particle swarm and genetic algorithm for the optimization of the LANSCE linac operation

    Science.gov (United States)

    Pang, X.; Rybarcyk, L. J.

    2014-03-01

    Particle swarm optimization (PSO) and genetic algorithm (GA) are both nature-inspired population based optimization methods. Compared to GA, whose long history can trace back to 1975, PSO is a relatively new heuristic search method first proposed in 1995. Due to its fast convergence rate in single objective optimization domain, the PSO method has been extended to optimize multi-objective problems. In this paper, we will introduce the PSO method and its multi-objective extension, the MOPSO, apply it along with the MOGA (mainly the NSGA-II) to simulations of the LANSCE linac and operational set point optimizations. Our tests show that both methods can provide very similar Pareto fronts but the MOPSO converges faster.

  4. A multi-objective approach in the optimization of optical systems taking into account tolerancing

    Science.gov (United States)

    de Albuquerque, Bráulio F. C.; Liao, Lin-Yao; Montes, Amauri Silva; de Sousa, Fabiano Luis; Sasián, José

    2011-10-01

    A Multi-Objective approach for lens design optimization was verified. The optimization problem was approached by addressing simultaneously, but separately, image quality and system tolerancing. In contrast to other previous published methods, the error functions were not combined into a single merit function. As a result the method returns a set of nondominated solutions that generates a Pareto Front. Our method resulted in alternate and useful insights about the trade off solutions for a lens design problem. This Multi-objective optimization can conveniently be implemented with evolutionary methods of optimization that have established success in lens design. We provided an example of the insights and usefulness of our approach in the design of a Telephoto lens system using NSGA-II, a popular multiobjective evolutionary optimization algorithm.

  5. Multi-objective optimization of lithium-ion battery model using genetic algorithm approach

    Science.gov (United States)

    Zhang, Liqiang; Wang, Lixin; Hinds, Gareth; Lyu, Chao; Zheng, Jun; Li, Junfu

    2014-12-01

    A multi-objective parameter identification method for modeling of Li-ion battery performance is presented. Terminal voltage and surface temperature curves at 15 °C and 30 °C are used as four identification objectives. The Pareto fronts of two types of Li-ion battery are obtained using the modified multi-objective genetic algorithm NSGA-II and the final identification results are selected using the multiple criteria decision making method TOPSIS. The simulated data using the final identification results are in good agreement with experimental data under a range of operating conditions. The validation results demonstrate that the modified NSGA-II and TOPSIS algorithms can be used as robust and reliable tools for identifying parameters of multi-physics models for many types of Li-ion batteries.

  6. Multi-Objective Optimization Algorithms Design based on Support Vector Regression Metamodeling

    Directory of Open Access Journals (Sweden)

    Qi Zhang

    2013-11-01

    Full Text Available In order to solve the multi-objective optimization problem in the complex engineering, in this paper a NSGA-II multi-objective optimization algorithms based on Support Vector Regression Metamodeling is presented. Appropriate design parameter samples are selected by experimental design theories, and the response samples are obtained from the experiments or numerical simulations, used the SVM method to establish the metamodels of the objective performance functions and constraints, and reconstructed the original optimal problem. The reconstructed metamodels was solved by NSGA-II algorithm and took the structure optimization of the microwave power divider as an example to illustrate the proposed methodology and solve themulti-objective optimization problem. The results show that this methodology is feasible and highly effective, and thus it can be used in the optimum design of engineering fields.

  7. Multi-objective evolutionary optimization of biological pest control with impulsive dynamics in soybean crops.

    Science.gov (United States)

    Cardoso, Rodrigo T N; da Cruz, André R; Wanner, Elizabeth F; Takahashi, Ricardo H C

    2009-08-01

    The biological pest control in agriculture, an environment-friendly practice, maintains the density of pests below an economic injury level by releasing a suitable quantity of their natural enemies. This work proposes a multi-objective numerical solution to biological pest control for soybean crops, considering both the cost of application of the control action and the cost of economic damages. The system model is nonlinear with impulsive control dynamics, in order to cope more effectively with the actual control action to be applied, which should be performed in a finite number of discrete time instants. The dynamic optimization problem is solved using the NSGA-II, a fast and trustworthy multi-objective genetic algorithm. The results suggest a dual pest control policy, in which the relative price of control action versus the associated additional harvest yield determines the usage of either a low control action strategy or a higher one.

  8. Multi-Objective Genetic Programming with Redundancy-Regulations for Automatic Construction of Image Feature Extractors

    Science.gov (United States)

    Watchareeruetai, Ukrit; Matsumoto, Tetsuya; Takeuchi, Yoshinori; Kudo, Hiroaki; Ohnishi, Noboru

    We propose a new multi-objective genetic programming (MOGP) for automatic construction of image feature extraction programs (FEPs). The proposed method was originated from a well known multi-objective evolutionary algorithm (MOEA), i.e., NSGA-II. The key differences are that redundancy-regulation mechanisms are applied in three main processes of the MOGP, i.e., population truncation, sampling, and offspring generation, to improve population diversity as well as convergence rate. Experimental results indicate that the proposed MOGP-based FEP construction system outperforms the two conventional MOEAs (i.e., NSGA-II and SPEA2) for a test problem. Moreover, we compared the programs constructed by the proposed MOGP with four human-designed object recognition programs. The results show that the constructed programs are better than two human-designed methods and are comparable with the other two human-designed methods for the test problem.

  9. Multi-objective optimal design of active vibration absorber with delayed feedback

    Science.gov (United States)

    Huan, Rong-Hua; Chen, Long-Xiang; Sun, Jian-Qiao

    2015-03-01

    In this paper, a multi-objective optimal design of delayed feedback control of an actively tuned vibration absorber for a stochastically excited linear structure is investigated. The simple cell mapping (SCM) method is used to obtain solutions of the multi-objective optimization problem (MOP). The continuous time approximation (CTA) method is applied to analyze the delayed system. Stability is imposed as a constraint for MOP. Three conflicting objective functions including the peak frequency response, vibration energy of primary structure and control effort are considered. The Pareto set and Pareto front for the optimal feedback control design are presented for two examples. Numerical results have found that the Pareto optimal solutions provide effective delayed feedback control design.

  10. 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

  11. A modified interactive procedure to solve multi-objective group decision making problem

    OpenAIRE

    Mohammad Izadikhah

    2014-01-01

    Multi-objective optimization and multiple criteria decision making problems are the process of designing the best alternative by considering the incommensurable and conflicting objectives simultaneously. One of the first interactive procedures to solve multiple criteria decision making problems is STEM method. In this paper we propose a modified interactive procedure based on STEM method by calculating the weight vector of objectives which emphasize that more important objectives be closer to...

  12. Collaborative Emission Reduction Model Based on Multi-Objective Optimization for Greenhouse Gases and Air Pollutants.

    Directory of Open Access Journals (Sweden)

    Qing-chun Meng

    Full Text Available CO2 emission influences not only global climate change but also international economic and political situations. Thus, reducing the emission of CO2, a major greenhouse gas, has become a major issue in China and around the world as regards preserving the environmental ecology. Energy consumption from coal, oil, and natural gas is primarily responsible for the production of greenhouse gases and air pollutants such as SO2 and NOX, which are the main air pollutants in China. In this study, a mathematical multi-objective optimization method was adopted to analyze the collaborative emission reduction of three kinds of gases on the basis of their common restraints in different ways of energy consumption to develop an economic, clean, and efficient scheme for energy distribution. The first part introduces the background research, the collaborative emission reduction for three kinds of gases, the multi-objective optimization, the main mathematical modeling, and the optimization method. The second part discusses the four mathematical tools utilized in this study, which include the Granger causality test to analyze the causality between air quality and pollutant emission, a function analysis to determine the quantitative relation between energy consumption and pollutant emission, a multi-objective optimization to set up the collaborative optimization model that considers energy consumption, and an optimality condition analysis for the multi-objective optimization model to design the optimal-pole algorithm and obtain an efficient collaborative reduction scheme. In the empirical analysis, the data of pollutant emission and final consumption of energies of Tianjin in 1996-2012 was employed to verify the effectiveness of the model and analyze the efficient solution and the corresponding dominant set. In the last part, several suggestions for collaborative reduction are recommended and the drawn conclusions are stated.

  13. Genetic algorithm-based multi-objective model for scheduling of linear construction projects

    OpenAIRE

    Senouci, Ahmed B.; Al-Derham, H.R.

    2007-01-01

    This paper presents a genetic algorithm-based multi-objective optimization model for the scheduling of linear construction projects. The model allows construction planners to generate and evaluate optimal/near-optimal construction scheduling plans that minimize both project time and cost. The computations in the present model are organized in three major modules. A scheduling module that develops practical schedules for linear construction projects. A cost module that computes the project's c...

  14. Artificial emotion triggered stochastic behavior transitions with motivational gain effects for multi-objective robot tasks

    Science.gov (United States)

    Dağlarli, Evren; Temeltaş, Hakan

    2007-04-01

    This paper presents artificial emotional system based autonomous robot control architecture. Hidden Markov model developed as mathematical background for stochastic emotional and behavior transitions. Motivation module of architecture considered as behavioral gain effect generator for achieving multi-objective robot tasks. According to emotional and behavioral state transition probabilities, artificial emotions determine sequences of behaviors. Also motivational gain effects of proposed architecture can be observed on the executing behaviors during simulation.

  15. Multi-objective Optimization of a Parallel Ankle Rehabilitation Robot Using Modified Differential Evolution Algorithm

    Institute of Scientific and Technical Information of China (English)

    WANG Congzhe; FANG Yuefa; GUO Sheng

    2015-01-01

    Dimensional synthesis is one of the most difficult issues in the field of parallel robots with actuation redundancy. To deal with the optimal design of a redundantly actuated parallel robot used for ankle rehabilitation, a methodology of dimensional synthesis based on multi-objective optimization is presented. First, the dimensional synthesis of the redundant parallel robot is formulated as a nonlinear constrained multi-objective optimization problem. Then four objective functions, separately reflecting occupied space, input/output transmission and torque performances, and multi-criteria constraints, such as dimension, interference and kinematics, are defined. In consideration of the passive exercise of plantar/dorsiflexion requiring large output moment, a torque index is proposed. To cope with the actuation redundancy of the parallel robot, a new output transmission index is defined as well. The multi-objective optimization problem is solved by using a modified Differential Evolution(DE) algorithm, which is characterized by new selection and mutation strategies. Meanwhile, a special penalty method is presented to tackle the multi-criteria constraints. Finally, numerical experiments for different optimization algorithms are implemented. The computation results show that the proposed indices of output transmission and torque, and constraint handling are effective for the redundant parallel robot; the modified DE algorithm is superior to the other tested algorithms, in terms of the ability of global search and the number of non-dominated solutions. The proposed methodology of multi-objective optimization can be also applied to the dimensional synthesis of other redundantly actuated parallel robots only with rotational movements.

  16. Low-Carbon Based Multi-Objective Bi-Level Power Dispatching under Uncertainty

    OpenAIRE

    2016-01-01

    This research examines a low-carbon power dispatch problem under uncertainty. A hybrid uncertain multi-objective bi-level model with one leader and multiple followers is established to support the decision making of power dispatch and generation. The upper level decision maker is the regional power grid corporation which allocates power quotas to each follower based on the objectives of reasonable returns, a small power surplus and low carbon emissions. The lower level decision makers are the...

  17. Collaborative Emission Reduction Model Based on Multi-Objective Optimization for Greenhouse Gases and Air Pollutants.

    Science.gov (United States)

    Meng, Qing-chun; Rong, Xiao-xia; Zhang, Yi-min; Wan, Xiao-le; Liu, Yuan-yuan; Wang, Yu-zhi

    2016-01-01

    CO2 emission influences not only global climate change but also international economic and political situations. Thus, reducing the emission of CO2, a major greenhouse gas, has become a major issue in China and around the world as regards preserving the environmental ecology. Energy consumption from coal, oil, and natural gas is primarily responsible for the production of greenhouse gases and air pollutants such as SO2 and NOX, which are the main air pollutants in China. In this study, a mathematical multi-objective optimization method was adopted to analyze the collaborative emission reduction of three kinds of gases on the basis of their common restraints in different ways of energy consumption to develop an economic, clean, and efficient scheme for energy distribution. The first part introduces the background research, the collaborative emission reduction for three kinds of gases, the multi-objective optimization, the main mathematical modeling, and the optimization method. The second part discusses the four mathematical tools utilized in this study, which include the Granger causality test to analyze the causality between air quality and pollutant emission, a function analysis to determine the quantitative relation between energy consumption and pollutant emission, a multi-objective optimization to set up the collaborative optimization model that considers energy consumption, and an optimality condition analysis for the multi-objective optimization model to design the optimal-pole algorithm and obtain an efficient collaborative reduction scheme. In the empirical analysis, the data of pollutant emission and final consumption of energies of Tianjin in 1996-2012 was employed to verify the effectiveness of the model and analyze the efficient solution and the corresponding dominant set. In the last part, several suggestions for collaborative reduction are recommended and the drawn conclusions are stated.

  18. Robust multi-objective optimization of state feedback controllers for heat exchanger system with probabilistic uncertainty

    Science.gov (United States)

    Lotfi, Babak; Wang, Qiuwang

    2013-07-01

    The performance of thermal control systems has, in recent years, improved in numerous ways due to developments in control theory and information technology. The shell-and-tube heat exchanger (STHX) is a medium where heat transfer process occurred. The accuracy of the heat exchanger depends on the performance of both elements. Therefore, both components need to be controlled in order to achieve a substantial result in the process. For this purpose, the actual dynamics of both shell and tube of the heat exchanger is crucial. In this paper, optimal reliability-based multi-objective Pareto design of robust state feedback controllers for a STHX having parameters with probabilistic uncertainties. Accordingly, the probabilities of failure of those objective functions are also considered in the reliability-based design optimization (RBDO) approach. A new multi-objective uniform-diversity genetic algorithm (MUGA) is presented and used for Pareto optimum design of linear state feedback controllers for STHX problem. In this way, Pareto front of optimum controllers is first obtained for the nominal deterministic STHX using the conflicting objective functions in time domain. Such Pareto front is then obtained for STHX having probabilistic uncertainties in its parameters using the statistical moments of those objective functions through a Hammersley Sequence Sampling (HSS) approach. It is shown that multi-objective reliability-based Pareto optimization of the robust state feedback controllers using MUGA includes those that may be obtained by various crisp threshold values of probability of failures and, thus, remove the difficulty of selecting suitable crisp values. Besides, the multi-objective Pareto optimization of such robust feedback controllers using MUGA unveils some very important and informative trade-offs among those objective functions. Consequently, some optimum robust state feedback controllers can be compromisingly chosen from the Pareto frontiers.

  19. Multi-objective Truss Optimization Using Different Types of the BB-BC Algorithm

    Directory of Open Access Journals (Sweden)

    Milajić Aleksandar

    2016-01-01

    Full Text Available Optimum design of truss structures is considered as a benchmark problem in the field of the structural optimization. In order to solve this hard combinatorial problem, it is necessary to implement adequate optimization tool that would provide sufficiently wide range of possible solutions within a reasonable time as well as to obtain good exploration and exploitation of search space. The aim of presented study was to compare efficiency of different multi-objective algorithms in solving this task.

  20. 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.

  1. Using multi-objective optimisation to integrate alpine regions in groundwater flow models

    Directory of Open Access Journals (Sweden)

    V. Rojanschi

    2005-01-01

    Full Text Available Within the research project GLOWA Danube, a groundwater flow model was developed for the Upper Danube basin. This paper reports on a preliminary study to include the alpine part of the catchment in the model. A conceptual model structure was implemented and tested using multi-objective optimisation analysis. The performance of the model and the identifiability of the parameters were studied. A possible over-parameterisation of the model was also tested using principal component analysis.

  2. A New Non-dominated Sorting Genetic Algorithm for Multi-Objective Optimization

    OpenAIRE

    2010-01-01

    This study imitates the gene-therapy process at the forefront of medicine and proposes an innovative evaluative crossover operator. The evaluative crossover integrates a geneevaluation method with a gene-therapy approach in the traditional NSGA-II for finding uniformly distributed Pareto-optimal front of multi-objective optimization problems. To further enhance the advantages of fast non-dominate sorting and diversity preservation in NSGA-II, the proposed gene-evaluation method partially eval...

  3. Multi-objective optimization to predict muscle tensions in a pinch function using genetic algorithm

    Science.gov (United States)

    Bensghaier, Amani; Romdhane, Lotfi; Benouezdou, Fethi

    2012-03-01

    This work is focused on the determination of the thumb and the index finger muscle tensions in a tip pinch task. A biomechanical model of the musculoskeletal system of the thumb and the index finger is developed. Due to the assumptions made in carrying out the biomechanical model, the formulated force analysis problem is indeterminate leading to an infinite number of solutions. Thus, constrained single and multi-objective optimization methodologies are used in order to explore the muscular redundancy and to predict optimal muscle tension distributions. Various models are investigated using the optimization process. The basic criteria to minimize are the sum of the muscle stresses, the sum of individual muscle tensions and the maximum muscle stress. The multi-objective optimization is solved using a Pareto genetic algorithm to obtain non-dominated solutions, defined as the set of optimal distributions of muscle tensions. The results show the advantage of the multi-objective formulation over the single objective one. The obtained solutions are compared to those available in the literature demonstrating the effectiveness of our approach in the analysis of the fingers musculoskeletal systems when predicting muscle tensions.

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

    Science.gov (United States)

    Kudryashov, Nikolay A.; Shilnikov, Kirill E.

    2016-06-01

    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.

  5. An Efficacious Multi-Objective Fuzzy Linear Programming Approach for Optimal Power Flow Considering Distributed Generation.

    Directory of Open Access Journals (Sweden)

    Warid Warid

    Full Text Available This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve. Fuzzy membership functions for these objectives are designed with extreme targets, whereas the inequality constraints are treated as hard constraints. The multi-objective fuzzy optimal power flow (OPF formulation was converted into a crisp OPF in a successive linear programming (SLP framework and solved using an efficient interior point method (IPM. To test the efficacy of the proposed approach, simulations are performed on the IEEE 30-busand IEEE 118-bus test systems. The MFLP optimization is solved for several optimization cases. The obtained results are compared with those presented in the literature. A unique solution with a high satisfaction for the assigned targets is gained. Results demonstrate the effectiveness of the proposed MFLP technique in terms of solution optimality and rapid convergence. Moreover, the results indicate that using the optimal DG location with the MFLP algorithm provides the solution with the highest quality.

  6. Multi-Objective Configuration Optimization of a Hybrid Energy Storage System

    Directory of Open Access Journals (Sweden)

    Shan Cheng

    2017-02-01

    Full Text Available This study aims to investigate multi-objective configuration optimization of a hybrid energy storage system (HESS. In order to maximize the stability of the wind power output with minimized HESS investment, a multi-objective model for optimal HESS configuration has been established, which proposes decreasing the installation and operation & maintenance costs of an HESS and improving the compensation satisfaction rate of wind power fluctuation. Besides, fuzzy control has been used to allocate power in the HESS for lengthening battery lifetime and ensuring HESS with enough energy to compensate the fluctuation of the next time interval. Instead of converting multiple objectives into one, a multi-objective particle swarm optimization with integration of bacteria quorum sensing and circular elimination (BC-MOPSO has been applied to provide diverse alternative solutions. In order to illustrate the feasibility and effectiveness of the proposed model and the application of BC-MOPSO, simulations along with analysis and discussion are carried out. The results verified the feasibility and effectiveness of the proposed approach.

  7. Multi-Objective Synthesis of Filtering Dipole Array Based on Tuning-Space Mapping

    Directory of Open Access Journals (Sweden)

    P. Vsetula

    2015-09-01

    Full Text Available In the paper, we apply tuning-space mapping to multi-objective synthesis of a filtering antenna. The antenna is going to be implemented as a planar dipole array with serial feeding. Thanks to the multi-objective approach, we can deal with conflicting requirements on gain, impedance matching, side-lobe level, and main-lobe direction. MOSOMA algorithm is applied to compute Pareto front of optimal solutions by changing lengths of dipoles and parameters of transmission lines connecting them into a serial array. Exploitation of tuning space mapping significantly reduces CPU-time demands of the multi-objective synthesis: a coarse optimization evaluates objectives using a wire model of the filtering array (4NEC2, method of moments, and a fine optimization exploits a realistic planar model of the array (CST Microwave Studio, finite integration technique. The synthesized filtering antenna was manufactured, and its parameters were measured to be compared with objectives. The number of dipoles in the array is shown to influence the match of measured parameters and objectives.

  8. Multi-objective PID Optimization for Speed Control of an Isolated Steam Turbine using Gentic Algorithm

    Directory of Open Access Journals (Sweden)

    Sanjay Kr. Singh

    2014-05-01

    Full Text Available 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 not being connected to the grid; hence is usually used in refineries as steam turbine, where a hydraulic governor is used for the speed control. The PID controller for the system has been designed and implemented using MATLAB and SIMULINK and the results of the design methods have been compared, analysed and conclusions indicates that the significant improvement of results have been obtained by the Multi-Objective GA based optimization of PID as much faster response is obtained as compared to the ordinary GA and Ziegler Nichols method.

  9. An Efficacious Multi-Objective Fuzzy Linear Programming Approach for Optimal Power Flow Considering Distributed Generation.

    Science.gov (United States)

    Warid, Warid; Hizam, Hashim; Mariun, Norman; Abdul-Wahab, Noor Izzri

    2016-01-01

    This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF) problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve. Fuzzy membership functions for these objectives are designed with extreme targets, whereas the inequality constraints are treated as hard constraints. The multi-objective fuzzy optimal power flow (OPF) formulation was converted into a crisp OPF in a successive linear programming (SLP) framework and solved using an efficient interior point method (IPM). To test the efficacy of the proposed approach, simulations are performed on the IEEE 30-busand IEEE 118-bus test systems. The MFLP optimization is solved for several optimization cases. The obtained results are compared with those presented in the literature. A unique solution with a high satisfaction for the assigned targets is gained. Results demonstrate the effectiveness of the proposed MFLP technique in terms of solution optimality and rapid convergence. Moreover, the results indicate that using the optimal DG location with the MFLP algorithm provides the solution with the highest quality.

  10. Relevance and Applicability of Multi-objective Resource Constrained Project Scheduling Problem: Review Article

    Directory of Open Access Journals (Sweden)

    V. Oladokun

    2011-12-01

    Full Text Available Resource-Constrained Project Scheduling Problem (RCPSP is a Non Polynomial (NP - Hard optimization problem that considers how to assign activities to available resources in order to meet predefined objectives. The problem is usually characterized by precedence relationship between activities with limited capacity of renewable resources. In an environment where resources are limited, projects still have to be finished on time, within the approved budget and in accordance with the preset specifications. Inherently, these tend to make RCPSP, a multi-objective problem. However, it has been treated as a single objective problem with project makespan often recognized as the most relevant objective. As a result of not understanding the multi-objective dimension of some projects, where these objectives need to be simultaneously considered, distraction and conflict of interest have ultimately lead to abandoned or totally failed projects. The aim of this article is to holistically review the relevance and applicability of multi-objective performance dimension of RCPSP in an environment where optimal use of limited resources is important.

  11. CFD-based multi-objective optimization method for ship design

    Science.gov (United States)

    Tahara, Yusuke; Tohyama, Satoshi; Katsui, Tokihiro

    2006-10-01

    This paper concerns development and demonstration of a computational fluid dynamics (CFD)-based multi-objective optimization method for ship design. Three main components of the method, i.e. computer-aided design (CAD), CFD, and optimizer modules are functionally independent and replaceable. The CAD used in the present study is NAPA system, which is one of the leading CAD systems in ship design. The CFD method is FLOWPACK version 2004d, a Reynolds-averaged Navier-Stokes (RaNS) solver developed by the present authors. The CFD method is implemented into a self-propulsion simulator, where the RaNS solver is coupled with a propeller-performance program. In addition, a maneuvering simulation model is developed and applied to predict ship maneuverability performance. Two nonlinear optimization algorithms are used in the present study, i.e. the successive quadratic programming and the multi-objective genetic algorithm, while the former is mainly used to verify the results from the latter. For demonstration of the present method, a multi-objective optimization problem is formulated where ship propulsion and maneuverability performances are considered. That is, the aim is to simultaneously minimize opposite hydrodynamic performances in design tradeoff. In the following, an overview of the present method is given, and results are presented and discussed for tanker stern optimization problem including detailed verification work on the present numerical schemes.

  12. Multi-objective calibration of a distributed hydrological model (WetSpa using a genetic algorithm

    Directory of Open Access Journals (Sweden)

    M. Shafii

    2009-01-01

    Full Text Available A multi-objective genetic algorithm, NSGA-II, is applied to calibrate a distributed hydrological model (WetSpa for predicting river discharge. The evaluation criteria considered are the model bias (mass balance, the model efficiency (Nash-Sutcliffe efficiency, and a logarithmic transformed model efficiency (to emphasize low-flow values. The concept of Pareto dominance is used to solve the multi-objective optimization problem and derive Pareto-optimal parameter sets. In order to analyze the applicability of the approach, a comparison is made with another calibration routine using the parameter estimator PEST to minimize the model efficiency. The two approaches are evaluated by applying the WetSpa model to the Hornad River (Slovakia for which observations of daily precipitation, temperature, potential evapotranspiration, and discharge are available for a 10 year period (1991–2000. The first 5 years of the data series are used for model calibration, while the second 5 years for model validation. The results revealed that the quality of the solutions obtained with NSGA-II is comparable or even better to what can be obtained with PEST, considering the same assumptions. Hence, NSGA-II is capable of locating Pareto optimal solutions in the parameter search space and the results obtained prove the excellent performance of the multi-objective model calibration methodology.

  13. An archived multi-objective simulated annealing for a dynamic cellular manufacturing system

    Science.gov (United States)

    Shirazi, Hossein; Kia, Reza; Javadian, Nikbakhsh; Tavakkoli-Moghaddam, Reza

    2014-05-01

    To design a group layout of a cellular manufacturing system (CMS) in a dynamic environment, a multi-objective mixed-integer non-linear programming model is developed. The model integrates cell formation, group layout and production planning (PP) as three interrelated decisions involved in the design of a CMS. This paper provides an extensive coverage of important manufacturing features used in the design of CMSs and enhances the flexibility of an existing model in handling the fluctuations of part demands more economically by adding machine depot and PP decisions. Two conflicting objectives to be minimized are the total costs and the imbalance of workload among cells. As the considered objectives in this model are in conflict with each other, an archived multi-objective simulated annealing (AMOSA) algorithm is designed to find Pareto-optimal solutions. Matrix-based solution representation, a heuristic procedure generating an initial and feasible solution and efficient mutation operators are the advantages of the designed AMOSA. To demonstrate the efficiency of the proposed algorithm, the performance of AMOSA is compared with an exact algorithm (i.e., ∈-constraint method) solved by the GAMS software and a well-known evolutionary algorithm, namely NSGA-II for some randomly generated problems based on some comparison metrics. The obtained results show that the designed AMOSA can obtain satisfactory solutions for the multi-objective model.

  14. DNA strand generation for DNA computing by using a multi-objective differential evolution algorithm.

    Science.gov (United States)

    Chaves-González, José M; Vega-Rodríguez, Miguel A

    2014-02-01

    In this paper, we use an adapted multi-objective version of the differential evolution (DE) metaheuristics for the design and generation of reliable DNA libraries that can be used for computation. DNA sequence design is a very relevant task in many recent research fields, e.g. nanotechnology or DNA computing. Specifically, DNA computing is a new computational model which uses DNA molecules as information storage and their possible biological interactions as processing operators. Therefore, the possible reactions and interactions among molecules must be strictly controlled to prevent incorrect computations. The design of reliable DNA libraries for bio-molecular computing is an NP-hard combinatorial problem which involves many heterogeneous and conflicting design criteria. For this reason, we modelled DNA sequence design as a multiobjective optimization problem and we solved it by using an adapted multi-objective version of DE metaheuristics. Seven different bio-chemical design criteria have been simultaneously considered to obtain high quality DNA sequences which are suitable for molecular computing. Furthermore, we have developed the multiobjective standard fast non-dominated sorting genetic algorithm (NSGA-II) in order to perform a formal comparative study by using multi-objective indicators. Additionally, we have also compared our results with other relevant results published in the literature. We conclude that our proposal is a promising approach which is able to generate reliable real-world DNA sequences that significantly improve other DNA libraries previously published in the literature.

  15. Multi-objective calibration of a distributed hydrological model (WetSpa) using a genetic algorithm

    Science.gov (United States)

    Shafii, M.; de Smedt, F.

    2009-11-01

    A multi-objective genetic algorithm, NSGA-II, is applied to calibrate a distributed hydrological model (WetSpa) for prediction of river discharges. The goals of this study include (i) analysis of the applicability of multi-objective approach for WetSpa calibration instead of the traditional approach, i.e. the Parameter ESTimator software (PEST), and (ii) identifiability assessment of model parameters. The objective functions considered are model efficiency (Nash-Sutcliffe criterion) known to be biased for high flows, and model efficiency for logarithmic transformed discharges to emphasize low-flow values. For the multi-objective approach, Pareto-optimal parameter sets are derived, whereas for the single-objective formulation, PEST is applied to give optimal parameter sets. The two approaches are evaluated by applying the WetSpa model to predict daily discharges in the Hornad River (Slovakia) for a 10 year period (1991-2000). The results reveal that NSGA-II performs favourably well to locate Pareto optimal solutions in the parameters search space. Furthermore, identifiability analysis of the WetSpa model parameters shows that most parameters are well-identifiable. However, in order to perform an appropriate model evaluation, more efforts should be focused on improving calibration concepts and to define robust methods to quantify different sources of uncertainties involved in the calibration procedure.

  16. 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.

  17. Effects of predation by Hydra (Cnidaria on cladocerans (Crustacea: Cladocera

    Directory of Open Access Journals (Sweden)

    Ligia Rivera-De la Parra

    2016-03-01

    Full Text Available Planktonic cladocerans have evolved different strategies to avoid predation from vertebrates; these include changes in morphology, behavior, physiology, and/or life-history traits. However, littoral cladocerans are better adapted to avoid invertebrate predation particularly from insect larvae by evolving morphological and physiological adaptations. Nevertheless, this has not been proven for some littoral predators such as Hydra. In this study, we provide quantitative data on how Hydra affects its zooplankton prey. We studied the predation behavior on Alona glabra, Ceridodaphnia dubia, Daphnia pulex, Daphnia cf. mendotae, Diaphanosoma birgei, Macrothrix triserialis, Moina macrocopa, Pleuroxus aduncus, Scapholeberis kingi, Simocephalus vetulus, Elaphoidella grandidieri, Brachionus rubens and Euchlanis dilatata. We also tested the indirect effect of allelochemicals from Hydra on the demography of Daphnia cf. mendotae. Littoral cladocerans are specially adapted to resist nematocyst injection and discharge of toxic substances from Hydra. A significant decrease in the population growth rate from 0.21 to 0.125 d-1 was observed at densities of 2 ind. ml-1. The role of carapace thickness as an adaptive strategy of littoral cladocerans against Hydra predation is discussed.

  18. Prime Focus Spectrograph - Subaru's future -

    CERN Document Server

    Sugai, Hajime; Takato, Naruhisa; Tamura, Naoyuki; Shimono, Atsushi; Ohyama, Youichi; Ueda, Akitoshi; Ling, Hung-Hsu; de Arruda, Marcio Vital; Barkhouser, Robert H; Bennett, Charles L; Bickerton, Steve; Braun, David F; Bruno, Robin J; Carr, Michael A; Oliveira, João Batista de Carvalho; Chang, Yin-Chang; Chen, Hsin-Yo; Dekany, Richard G; Dominici, Tania Pereira; Ellis, Richard S; Fisher, Charles D; Gunn, James E; Heckman, Timothy M; Ho, Paul T P; Hu, Yen-Shan; Jaquet, Marc; Karr, Jennifer; Kimura, Masahiko; Fèvre, Olivier Le; Mignant, David Le; Loomis, Craig; Lupton, Robert H; Madec, Fabrice; Marrara, Lucas Souza; Martin, Laurent; Murayama, Hitoshi; de Oliveira, Antonio Cesar; de Oliveira, Claudia Mendes; de Oliveira, Ligia Souza; Orndorff, Joe D; Vilaça, Rodrigo de Paiva; Macanhan, Vanessa Bawden de Paula; Prieto, Eric; Santos, Jesulino Bispo dos; Seiffert, Michael D; Smee, Stephen A; Smith, Roger M; Sodré, Laerte; Spergel, David N; Surace, Christian; Vives, Sebastien; Wang, Shiang-Yu; Yan, Chi-Hung

    2012-01-01

    The Prime Focus Spectrograph (PFS) of the Subaru Measurement of Images and Redshifts (SuMIRe) project has been endorsed by Japanese community as one of the main future instruments of the Subaru 8.2-meter telescope at Mauna Kea, Hawaii. This optical/near-infrared multi-fiber spectrograph targets cosmology with galaxy surveys, Galactic archaeology, and studies of galaxy/AGN evolution. Taking advantage of Subaru's wide field of view, which is further extended with the recently completed Wide Field Corrector, PFS will enable us to carry out multi-fiber spectroscopy of 2400 targets within 1.3 degree diameter. A microlens is attached at each fiber entrance for F-ratio transformation into a larger one so that difficulties of spectrograph design are eased. Fibers are accurately placed onto target positions by positioners, each of which consists of two stages of piezo-electric rotary motors, through iterations by using back-illuminated fiber position measurements with a wide-field metrology camera. Fibers then carry l...

  19. The survey operation software system development for Prime Focus Spectrograph (PFS) on Subaru Telescope

    CERN Document Server

    Takato, Naruhisa; Lupton, Robert H

    2016-01-01

    The Prime Focus Spectrograph (PFS) is a wide-field, multi-object spectrograph accommodating 2394 fibers to observe the sky at the prime focus of the Subaru telescope. The software system to operate a spectroscopic survey is structured by the four packages: Instrument control software, exposure targeting software, data reduction pipeline, and survey planning and tracking software. In addition, we operate a database system where various information such as properties of target objects, instrument configurations, and observation conditions is stored and is organized via a standardized data model for future references to update survey plans and to scientific researches. In this article, we present an overview of the software system and describe the workflows that need to be performed in the PFS operation, with some highlights on the database that organizes various information from sub-processes in the survey operation, and on the process of fiber configuration from the software perspectives.

  20. Design and performance of a F/#-conversion microlens for Prime Focus Spectrograph at Subaru Telescope

    CERN Document Server

    Takato, Naruhisa; Gunn, James E; Tamura, Naoyuki; Shimono, Atsushi; Sugai, Hajime; Karoji, Hiroshi; Ueda, Akitoshi; Waseda, Kouichi; Kimura, Masahiko; Ohyama, Youichi

    2014-01-01

    The PFS is a multi-object spectrograph fed by 2394 fibers at the prime focus of Subaru telescope. Since the F/# at the prime focus is too fast for the spectrograph, we designed a small concave-plano negative lens to be attached to the tip of each fiber that converts the telescope beam (F/2.2) to F/2.8. We optimized the lens to maximize the number of rays that can be confined inside F/2.8 while maintaining a 1.28 magnification. The microlenses are manufactured by glass molding, and an ultra-broadband AR coating (<1.5% for lambda=0.38-1.26 um) will be applied to the front surface.

  1. The survey operation software system development for Prime Focus Spectrograph (PFS) on Subaru Telescope

    Science.gov (United States)

    Shimono, Atsushi; Tamura, Naoyuki; Takato, Naruhisa; Yasuda, Naoki; Suzuki, Nao; Loomis, Craig P.; Lupton, Robert H.; Moritani, Yuki; Yabe, Kiyoto

    2016-07-01

    The Prime Focus Spectrograph (PFS) is a wide-field, multi-object spectrograph accommodating 2394 fibers to observe the sky at the prime focus of the Subaru telescope. The software system to operate a spectroscopic survey is structured by the four packages: Instrument control software, exposure targeting software, data reduction pipeline, and survey planning and tracking software. In addition, we operate a database system where various information such as properties of target objects, instrument configurations, and observation conditions is stored and is organized via a standardized data model for future references to update survey plans and to scientific researches. In this article, we present an overview of the software system and describe the workflows that need to be performed in the PFS operation, with some highlights on the database that organizes various information from sub-processes in the survey operation, and on the process of fiber configuration from the software perspectives.

  2. Optimal Design of Groundwater Remediation Problems under Uncertainty Using Probabilistic Multi-objective Evolutionary Technique

    Science.gov (United States)

    Yang, Y.; Wu, J.

    2011-12-01

    The previous work in the field of multi-objective optimization under uncertainty has concerned with the probabilistic multi-objective algorithm itself, how to effectively evaluate an estimate of uncertain objectives and identify a set of reliable Pareto optimal solutions. However, the design of a robust and reliable groundwater remediation system encounters major difficulties owing to the inherent uncertainty of hydrogeological parameters such as hydraulic conductivity (K). Thus, we need to make reduction of uncertainty associated with the site characteristics of the contaminated aquifers. In this study, we first use the Sequential Gaussian Simulation (SGSIM) to generate 1000 conditional realizations of lnK based on the sampled conditioning data acquired by field test. It is worthwhile to note that the cost for field test often weighs heavily upon the remediation cost and must thus be taken into account in the tradeoff between the solution reliability and remedial cost optimality. In this situation, we perform Monte Carlo simulation to make an uncertainty analysis of lnK realizations associated with the different number of conditioning data points. The results indicate that the uncertainty of the site characteristics and the contaminant concentration output from transport model is decreasing and then tends toward stabilization with the increase of conditioning data. This study presents a probabilistic multi-objective evolutionary algorithm (PMOEA) that integrates noisy genetic algorithm (NGA) and probabilistic multi-objective genetic algorithm (MOGA). The evident difference between deterministic MOGA and probabilistic MOGA is the use of probabilistic Pareto domination ranking and niche technique to ensure that each solution found is most reliable and robust. The proposed algorithm is then evaluated through a synthetic pump-and-treat (PAT) groundwater remediation test case. The 1000 lnK realizations generated by SGSIM with appropriate number of conditioning data (30

  3. 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

    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...

  4. Development of a multi-objective coagulation system for long-term fouling control in dead-end ultrafiltration

    NARCIS (Netherlands)

    Zondervan, Edwin; Blankert, Bastiaan; Betlem, Ben H.L.; Roffel, Brian

    2008-01-01

    In this paper, a multi-objective control system has been developed and experimentally tested. The multi-objective control system can be effectively used to control short-term fouling as well as long-term fouling. In an earlier study it was found that coagulant dosing in ultrafiltration can be used e

  5. Development of a multi-objective coagulation system for long-term fouling control in dead-end ultrafiltration

    NARCIS (Netherlands)

    Zondervan, Edwin; Blankert, Bastiaan; Betlem, Ben H. L.; Roffel, Brian

    2008-01-01

    In this paper, a multi-objective control system has been developed and experimentally tested. The multi-objective control system can be effectively used to control short-term fouling as well as long-term fouling. In an earlier Study it was found that coagulant dosing in ultrafiltration can be used e

  6. Multi-wavelength spectrophotometry of EX Hydrae

    CERN Document Server

    Eisenbart, S; Reinsch, K; Gänsicke, B T

    2002-01-01

    We present phase-resolved infrared and optical spectrophotometry of the intermediate polar EX Hya supplemented by archival ultraviolet data. The spin-modulated emission from the accretion funnel and the emission from the accretion disk or ring contain substantial optically thin components. The white dwarf dominates the unmodulated flux in the ultraviolet and is identified by numerous absorption lines. Metal absorption in the accretion curtain may add to the observed spectral features. The secondary star is of spectral type M4+-1 and is detected by its ellipsoidal modulation. We derive a distance of 65+-11 pc which makes EX Hydrae one of the closest cataclysmic variables with a known distance. The luminosity derived from the integrated overall spectral energy distribution is 3x10^32 erg/s. The accretion rate of 3x10^15 g/s (for an 0.6 Msun white dwarf) is in reasonable agreement with the rates expected from angular momentum loss by gravitational radiation and from the observed spin-up of the white dwarf

  7. The pulsation spectrum of VX Hydrae

    CERN Document Server

    Templeton, M R; Dvorak, S; Poklar, R; Butterworth, N; Gerner, H

    2009-01-01

    We present the results of a two-year, multisite observing campaign investigating the high-amplitude delta Scuti star VX Hydrae during the 2006 and 2007 observing seasons. The final data set consists of nearly 8500 V-band observations spanning HJD 2453763.6 to 2454212.7 (2006 January 28 to 2007 April 22). Separate analyses of the two individual seasons of data yield 25 confidently-detected frequencies common to both data sets, of which two are pulsation modes, and the remaining 23 are Fourier harmonics or beat frequencies of these two modes. The 2006 data set had five additional frequencies with amplitudes less than 1.5 mmag, and the 2007 data had one additional frequency. Analysis of the full 2006-2007 data set yields 22 of the 25 frequencies found in the individual seasons of data. There are no significant peaks in the spectrum other than these between 0 and 60 c/d. The frequencies of the two main pulsation modes derived from the 2006 and 2007 observing seasons individually do not differ at the level of 3-si...

  8. Hydra and Niccolo Paganini (1782-1840)--two peas in a pod? The molecular basis of extracellular matrix structure in the invertebrate, Hydra.

    Science.gov (United States)

    Sarras, M P; Deutzmann, R

    2001-08-01

    The body wall of Hydra is organized as an epithelial bilayer with an intervening extracellular matrix (ECM). Molecular and biochemical analyses of Hydra ECM have established that it contains components similar to those seen in more complicated vertebrates such as human. In terms of biophysical parameters, Hydra ECM is highly flexible; a property that facilitates continuous movements along the organism's longitudinal and radial axis. A more rigid ECM, as in vertebrates, would not be compatible with this degree of movement. The flexible nature of Hydra ECM can now be explained in part by the unique structure of the organism's collagens. Interestingly, some aspects of the structural features of Hydra collagens mimic what is seen in Ehlers-Danlos syndrome, an inherited condition in humans that results in an abnormally flexible ECM that can be debilitating in extreme cases. This review will focus on structure-function relationships of the ECM of Hydra.

  9. Hymyc1 downregulation promotes stem cell proliferation in Hydra vulgaris.

    Directory of Open Access Journals (Sweden)

    Alfredo Ambrosone

    Full Text Available Hydra is a unique model for studying the mechanisms underlying stem cell biology. The activity of the three stem cell lineages structuring its body constantly replenishes mature cells lost due to normal tissue turnover. By a poorly understood mechanism, stem cells are maintained through self-renewal while concomitantly producing differentiated progeny. In vertebrates, one of many genes that participate in regulating stem cell homeostasis is the protooncogene c-myc, which has been recently identified also in Hydra, and found expressed in the interstitial stem cell lineage. In the present paper, by developing a novel strategy of RNA interference-mediated gene silencing (RNAi based on an enhanced uptake of small interfering RNAi (siRNA, we provide molecular and biological evidence for an unexpected function of the Hydra myc gene (Hymyc1 in the homeostasis of the interstitial stem cell lineage. We found that Hymyc1 inhibition impairs the balance between stem cell self renewal/differentiation, as shown by the accumulation of stem cell intermediate and terminal differentiation products in genetically interfered animals. The identical phenotype induced by the 10058-F4 inhibitor, a disruptor of c-Myc/Max dimerization, demonstrates the specificity of the RNAi approach. We show the kinetic and the reversible feature of Hymyc1 RNAi, together with the effects displayed on regenerating animals. Our results show the involvement of Hymyc1 in the control of interstitial stem cell dynamics, provide new clues to decipher the molecular control of the cell and tissue plasticity in Hydra, and also provide further insights into the complex myc network in higher organisms. The ability of Hydra cells to uptake double stranded RNA and to trigger a RNAi response lays the foundations of a comprehensive analysis of the RNAi response in Hydra allowing us to track back in the evolution and the origin of this process.

  10. Conceptual design for an AIUC multi-purpose spectrograph camera using DMD technology

    Science.gov (United States)

    Rukdee, S.; Bauer, F.; Drass, H.; Vanzi, L.; Jordan, A.; Barrientos, F.

    2017-02-01

    Current and upcoming massive astronomical surveys are expected to discover a torrent of objects, which need groundbased follow-up observations to characterize their nature. For transient objects in particular, rapid early and efficient spectroscopic identification is needed. In particular, a small-field Integral Field Unit (IFU) would mitigate traditional slit losses and acquisition time. To this end, we present the design of a Digital Micromirror Device (DMD) multi-purpose spectrograph camera capable of running in several modes: traditional longslit, small-field patrol IFU, multi-object and full-field IFU mode via Hadamard spectra reconstruction. AIUC Optical multi-purpose CAMera (AIUCOCAM) is a low-resolution spectrograph camera of R 1,600 covering the spectral range of 0.45-0.85 μm. We employ a VPH grating as a disperser, which is removable to allow an imaging mode. This spectrograph is envisioned for use on a 1-2 m class telescope in Chile to take advantage of good site conditions. We present design decisions and challenges for a costeffective robotized spectrograph. The resulting instrument is remarkably versatile, capable of addressing a wide range of scientific topics.

  11. Algal endosymbiosis in brown hydra: host/symbiont specificity.

    Science.gov (United States)

    Rahat, M; Reich, V

    1986-12-01

    Host/symbiont specificity has been investigated in non-symbiotic and aposymbiotic brown and green hydra infected with various free-living and symbiotic species and strains of Chlorella and Chlorococcum. Morphology and ultrastructure of the symbioses obtained have been compared. Aposymbiotic Swiss Hydra viridis and Japanese H. magnipapillata served as controls. In two strains of H. attenuata stable hereditary symbioses were obtained with Chlorococcum isolated from H. magnipapillata. In one strain of H. vulgaris, in H. oligactis and in aposymbiotic H. viridis chlorococci persisted for more than a week. Eight species of free-living Chlorococcum, 10 symbiotic and 10 free-living strains of Chlorella disappeared from the brown hydra within 1-2 days. In H. magnipapillata there was a graded distribution of chlorococci along the polyps. In hypostomal cells there were greater than 30 algae/cell while in endodermal cells of the mid-section or peduncle less than 10 algae/cell were found. In H. attenuata the algal distribution was irregular, there were up to five chlorocci/cell, and up to 20 cells/hydra hosted algae. In the dark most cells of Chlorococcum disappeared from H. magnipapillata and aposymbiotic hydra were obtained. Chlorococcum is thus an obligate phototroph, and host-dependent heterotrophy is not required for the preservation of a symbiosis. The few chlorococci that survived in the dark seem to belong to a less-demanding physiological strain. In variance with known Chlorella/H. viridis endosymbioses the chlorococci in H. magnipapillata and H. attenuata were tightly enveloped in the vacuolar membrane of the hosting cells with no visible perialgal space. Chlorococcum reproduced in these vacuoles and up to eight daughter cells were found within the same vacuole. We suggest that the graded or scant distribution of chlorococci in the various brown hydra, their inability to live in H. viridis and the inability of the various chlorellae to live in brown hydra are the

  12. FMRFamide-like immunoreactivity in the nervous system of Hydra

    DEFF Research Database (Denmark)

    Grimmelikhuijzen, C J; Dockray, G J; Schot, L P

    1982-01-01

    FMRFamide-like immunoreactivity has been localized in different parts of the hydra nervous system. Immunoreactivity occurs in nerve perikarya and processes in the ectoderm of the lower peduncle region near the basal disk, in the ectoderm of the hypostome and in the ectoderm of the tentacles....... The immunoreactive nerve perikarya in the lower peduncle region form ganglion-like structures. Radioimmunoassays of extracts of hydra gave displacement curves parallel to standard FMRFamide and values of at least 8 pmol/gram wet weight of FMRFamide-like immunoreactivity. The immunoreactive material eluted from...

  13. Multi-objective global sensitivity analysis of the WRF model parameters

    Science.gov (United States)

    Quan, Jiping; Di, Zhenhua; Duan, Qingyun; Gong, Wei; Wang, Chen

    2015-04-01

    Tuning model parameters to match model simulations with observations can be an effective way to enhance the performance of numerical weather prediction (NWP) models such as Weather Research and Forecasting (WRF) model. However, this is a very complicated process as a typical NWP model involves many model parameters and many output variables. One must take a multi-objective approach to ensure all of the major simulated model outputs are satisfactory. This talk presents the results of an investigation of multi-objective parameter sensitivity analysis of the WRF model to different model outputs, including conventional surface meteorological variables such as precipitation, surface temperature, humidity and wind speed, as well as atmospheric variables such as total precipitable water, cloud cover, boundary layer height and outgoing long radiation at the top of the atmosphere. The goal of this study is to identify the most important parameters that affect the predictive skill of short-range meteorological forecasts by the WRF model. The study was performed over the Greater Beijing Region of China. A total of 23 adjustable parameters from seven different physical parameterization schemes were considered. Using a multi-objective global sensitivity analysis method, we examined the WRF model parameter sensitivities to the 5-day simulations of the aforementioned model outputs. The results show that parameter sensitivities vary with different model outputs. But three to four of the parameters are shown to be sensitive to all model outputs considered. The sensitivity results from this research can be the basis for future model parameter optimization of the WRF model.

  14. Multi-objective evolutionary optimization for greywater reuse in municipal sewer systems.

    Science.gov (United States)

    Penn, Roni; Friedler, Eran; Ostfeld, Avi

    2013-10-01

    Sustainable design and implementation of greywater reuse (GWR) has to achieve an optimum compromise between costs and potable water demand reduction. Studies show that GWR is an efficient tool for reducing potable water demand. This study presents a multi-objective optimization model for estimating the optimal distribution of different types of GWR homes in an existing municipal sewer system. Six types of GWR homes were examined. The model constrains the momentary wastewater (WW) velocity in the sewer pipes (which is responsible for solids movement). The objective functions in the optimization model are the total WW flow at the outlet of the neighborhoods sewer system and the cost of the on-site GWR treatment system. The optimization routing was achieved by an evolutionary multi-objective optimization coupled with hydrodynamic simulations of a representative sewer system of a neighborhood located at the coast of Israel. The two non-dominated best solutions selected were the ones having either the smallest WW flow discharged at the outlet of the neighborhood sewer system or the lowest daily cost. In both solutions most of the GWR types chosen were the types resulting with the smallest water usage. This lead to only a small difference between the two best solutions, regarding the diurnal patterns of the WW flows at the outlet of the neighborhood sewer system. However, in the upstream link a substantial difference was depicted between the diurnal patterns. This difference occurred since to the upstream links only few homes, implementing the same type of GWR, discharge their WW, and in each solution a different type of GWR was implemented in these upstream homes. To the best of our knowledge this is the first multi-objective optimization model aimed at quantitatively trading off the cost of local/onsite GW spatially distributed reuse treatments, and the total amount of WW flow discharged into the municipal sewer system under unsteady flow conditions.

  15. M2Align: parallel multiple sequence alignment with a multi-objective metaheuristic.

    Science.gov (United States)

    Zambrano-Vega, Cristian; Nebro, Antonio J; García-Nieto, José; Aldana Montes, José F

    2017-05-24

    Multiple Sequence Alignment (MSA) is an NP-complete optimization problem found in computational biology, where the time complexity of finding an optimal alignment raises exponentially along with the number of sequences and their lengths. Additionally, to assess the quality of a MSA, a number of objectives can be taken into account, such as maximizing the sum-of-pairs, maximizing the totally conserved columns, minimizing the number of gaps, or maximizing structural information based scores such as STRIKE. An approach to deal with MSA problems is to use multi-objective metaheuristics, which are non-exact stochastic optimization methods that can produce high quality solutions to complex problems having two or more objectives to be optimized at the same time. Our motivation is to provide a multi-objective metaheuristic for MSA that can run in parallel taking advantage of multi-core based computers. The software tool we propose, called M2Align (Multi-objective Multiple Sequence Alignment), is a parallel and more efficient version of the three-objective optimizer for sequence alignments MO-SAStrE, able of reducing the algorithm computing time by exploiting the computing capabilities of common multicore CPU clusters. Our performance evaluation over datasets of the benchmark BAliBASE (v3.0) shows that significant time reductions can be achieved by using up to 20 cores. Even in sequential executions, M2Align is faster than MO-SAStrE, thanks to the encoding method used for the alignments. M2Align is an open source project hosted in GitHub, where the source code and sample datasets can be freely obtained: https://github.com/KhaosResearch/M2Align. antonio@lcc.uma.es. Supplementary data are available at Bioinformatics online.

  16. A sustainable manufacturing system design: A fuzzy multi-objective optimization model.

    Science.gov (United States)

    Nujoom, Reda; Mohammed, Ahmed; Wang, Qian

    2017-08-10

    In the past decade, there has been a growing concern about the environmental protection in public society as governments almost all over the world have initiated certain rules and regulations to promote energy saving and minimize the production of carbon dioxide (CO2) emissions in many manufacturing industries. The development of sustainable manufacturing systems is considered as one of the effective solutions to minimize the environmental impact. Lean approach is also considered as a proper method for achieving sustainability as it can reduce manufacturing wastes and increase the system efficiency and productivity. However, the lean approach does not include environmental waste of such as energy consumption and CO2 emissions when designing a lean manufacturing system. This paper addresses these issues by evaluating a sustainable manufacturing system design considering a measurement of energy consumption and CO2 emissions using different sources of energy (oil as direct energy source to generate thermal energy and oil or solar as indirect energy source to generate electricity). To this aim, a multi-objective mathematical model is developed incorporating the economic and ecological constraints aimed for minimization of the total cost, energy consumption, and CO2 emissions for a manufacturing system design. For the real world scenario, the uncertainty in a number of input parameters was handled through the development of a fuzzy multi-objective model. The study also addresses decision-making in the number of machines, the number of air-conditioning units, and the number of bulbs involved in each process of a manufacturing system in conjunction with a quantity of material flow for processed products. A real case study was used for examining the validation and applicability of the developed sustainable manufacturing system model using the fuzzy multi-objective approach.

  17. Multi-Objective Optimization for Solid Amine CO2 Removal Assembly in Manned Spacecraft

    Directory of Open Access Journals (Sweden)

    Rong A

    2017-07-01

    Full Text Available Carbon Dioxide Removal Assembly (CDRA is one of the most important systems in the Environmental Control and Life Support System (ECLSS for a manned spacecraft. With the development of adsorbent and CDRA technology, solid amine is increasingly paid attention due to its obvious advantages. However, a manned spacecraft is launched far from the Earth, and its resources and energy are restricted seriously. These limitations increase the design difficulty of solid amine CDRA. The purpose of this paper is to seek optimal design parameters for the solid amine CDRA. Based on a preliminary structure of solid amine CDRA, its heat and mass transfer models are built to reflect some features of the special solid amine adsorbent, Polyethylenepolyamine adsorbent. A multi-objective optimization for the design of solid amine CDRA is discussed further in this paper. In this study, the cabin CO2 concentration, system power consumption and entropy production are chosen as the optimization objectives. The optimization variables consist of adsorption cycle time, solid amine loading mass, adsorption bed length, power consumption and system entropy production. The Improved Non-dominated Sorting Genetic Algorithm (NSGA-II is used to solve this multi-objective optimization and to obtain optimal solution set. A design example of solid amine CDRA in a manned space station is used to show the optimal procedure. The optimal combinations of design parameters can be located on the Pareto Optimal Front (POF. Finally, Design 971 is selected as the best combination of design parameters. The optimal results indicate that the multi-objective optimization plays a significant role in the design of solid amine CDRA. The final optimal design parameters for the solid amine CDRA can guarantee the cabin CO2 concentration within the specified range, and also satisfy the requirements of lightweight and minimum energy consumption.

  18. Enhancing multi-objective evolutionary algorithm performance with Markov Chain Monte Carlo

    Science.gov (United States)

    Shafii, M.; Vrugt, J. A.; Tolson, B.; Matott, L. S.

    2009-12-01

    Multi-Objective Evolutionary Algorithms (MOEAs) have emerged as successful optimization routines to solve complex and large-scale multi-objective model calibration problems. However, a common draw-back of these methods is that they require a relatively high number of function evaluations to produce an accurate approximation of Pareto front. This requirement can translate into incredibly large computational costs in hydrologic model calibration problems. Most research efforts to address this computational burden are focused on introducing or improving the operators applied in the MOEAs structure. However, population initialization, usually done through Random Sampling (RS) or Latin Hypercube Sampling (LHS), can also affect the searching efficiency and the quality of MOEA results. This study presents a novel approach to generate initial population of a MOEA (i.e. NSGA-II) by applying a Markov Chain Monte Carlo (MCMC) sampler. The basis of MCMC methods is a Markov chain generating a random walk through the search space, using a formal likelihood function to sample the high-probability-density regions of the parameter space. Therefore, these solutions, when used as initial population, are capable of carrying quite valuable information into MOEAs process. Instead of running the MCMC sampler (i.e. DREAM) to convergence, it is applied for a relatively small and fixed number of function evaluations. The MCMC samples are then processed to identify and archive the non-dominated solutions and this archive is used as NSGA-II’s initial population. In order to analyze the applicability of this approach, it is used for a number of benchmark mathematical problems, as well as multi-objective calibration of a rainfall-runoff model (HYMOD). Initial results show promising MOEA improvement when it is initialized with an MCMC based initial population. Results will be presented that comprehensively compares MOEA results with and without an MCMC based initial population in terms of the

  19. A multi-objective set covering problem: A case study of warehouse allocation in truck industry

    Directory of Open Access Journals (Sweden)

    Atefeh Malekinezhad

    2011-01-01

    Full Text Available Designing distribution centers is normally formulated in a form of set covering where is primary objective is to minimize the number of connected facilities. However, there are other issues affecting our decision on selecting suitable distribution centers such as weather conditions, temperature, infrastructure facilities, etc. In this paper, we propose a multi-objective set covering techniques where different objectives are considered in an integrated model. The proposed model of this paper is implemented for a real-world case study of truck-industry and the results are analyzed.

  20. Multi-objectives fuzzy optimization model for ship form demonstration based on information entropy

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Selecting optimization ship form scheme is an important content in the process of concept design of ship. Multi-objective fuzzy decision-making model for ship form demonstration is set up according to the fuzzy pattern-recognition theory. Weight coefficients of each target of ship form scheme are determined by information entropy and individual subjective partiality. This model is used to select the optimal ship form scheme,the example shows that the model is exact and the result is credible. It can provide a reference for choosing the optimization scheme of ship form.

  1. Multi-Objective Optimization of Spacecraft Trajectories for Small-Body Coverage Missions

    Science.gov (United States)

    Hinckley, David, Jr.; Englander, Jacob; Hitt, Darren

    2017-01-01

    Visual coverage of surface elements of a small-body object requires multiple images to be taken that meet many requirements on their viewing angles, illumination angles, times of day, and combinations thereof. Designing trajectories capable of maximizing total possible coverage may not be useful since the image target sequence and the feasibility of said sequence given the rotation-rate limitations of the spacecraft are not taken into account. This work presents a means of optimizing, in a multi-objective manner, surface target sequences that account for such limitations.

  2. An Efficient Multi-objective Approach for Designing of Communication Interfaces in Smart Grids

    DEFF Research Database (Denmark)

    Ghasemkhani, Amir; Anvari-Moghaddam, Amjad; Guerrero, Josep M.

    2016-01-01

    The next generation of power systems require to use smart grid technologies due to their unique features like high speed, reliable and secure data communications to monitor, control and protect system effectively. Hence, one of the main requirements of achieving a smart grid is optimal designing...... of telecommunication systems. In this study, a novel dynamic Multi-Objective Shortest Path (MOSP) algorithm is presented to design a spanning graph of a communication infrastructure using high speed Optimal Power Ground Wire (OPGW) cables and Phasor Measurement Units (PMUs). Applicability of the proposed model...

  3. Mean-Variance-Skewness-Entropy Measures: A Multi-Objective Approach for Portfolio Selection

    Directory of Open Access Journals (Sweden)

    Yeliz Mert Kantar

    2011-01-01

    Full Text Available In this study, we present a multi-objective approach based on a mean-variance-skewness-entropy portfolio selection model (MVSEM. In this approach, an entropy measure is added to the mean-variance-skewness model (MVSM to generate a well‑diversified portfolio. Through a variety of empirical data sets, we evaluate the performance of the MVSEM in terms of several portfolio performance measures. The obtained results show that the MVSEM performs well out-of sample relative to traditional portfolio selection models.

  4. 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

    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......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...

  5. Evolutionary multi-objective optimization: some current research trends and topics that remain to be explored

    Institute of Scientific and Technical Information of China (English)

    Carlos A. COELLO COELLO

    2009-01-01

    This paper provides a short review of some of the main topics in which the current research in evolutionary multi-objective optimization is being focused. The topics discussed include new algorithms, efficiency, relaxed forms of dominance, scalability, and alternative metaheuristics. This discussion motivates some further topics which,from the author's perspective, constitute good potential areas for future research, namely, constraint-handling techniques,incorporation of user's preferences and parameter control,This information is expected to be useful for those interested in pursuing research in this area.

  6. Performance Optimizing Multi-Objective Adaptive Control with Time-Varying Model Reference Modification

    Science.gov (United States)

    Nguyen, Nhan T.; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

    2017-01-01

    This paper presents a new adaptive control approach that involves a performance optimization objective. The problem is cast as a multi-objective optimal control. The control synthesis involves the design of a performance optimizing controller from a subset of control inputs. The effect of the performance optimizing controller is to introduce an uncertainty into the system that can degrade tracking of the reference model. An adaptive controller from the remaining control inputs is designed to reduce the effect of the uncertainty while maintaining a notion of performance optimization in the adaptive control system.

  7. Method of Designing Missile Controller Based on Multi-Objective Optimization

    Institute of Scientific and Technical Information of China (English)

    LIN Bo; MENG Xiu-yun; LIU Zao-zhen

    2006-01-01

    A method of designing robust controller based on genetic algorithm is presented in order to overcome the drawback of manual modification and trial in designing the control system of missile. Specification functions which reflect the dynamic performance in time domain and robustness in frequency domain are presented,then dynamic/static performance, control cost and robust stability are incorporated into a multi-objective optimization problem. Genetic algorithm is used to solve the problem and achieve the optimal controller directly.Simulation results show that the controller provides a good stability and offers a good dynamic performance in a large flight envelope. The results also validate the effectiveness of the method.

  8. Multi-objective genetic algorithm for the optimization of road surface cleaning process

    Institute of Scientific and Technical Information of China (English)

    CHEN Jie; GAO Dao-ming

    2006-01-01

    The parameters affecting road surface cleaning using waterjets were researched and a fuzzy neural network method of calculating cleaning rate was provided. A genetic algorithm was used to configure the cleaning parameters of pressure, standoff distance, traverse rate and angle of nozzles for the optimization of the cleaning effectiveness, efficiency, energy and water consumption, and a multi-objective optimization model was established. After calculation, the optimized results and the trend of variation of cleaning effectiveness, efficiency, energy and water consumption in different weighting factors were analyzed.

  9. Multi-objective optimization of cellular scanning strategy in selective laser melting

    DEFF Research Database (Denmark)

    Ahrari, Ali; Deb, Kalyanmoy; Mohanty, Sankhya

    2017-01-01

    The scanning strategy for selective laser melting - an additive manufacturing process - determines the temperature fields during the manufacturing process, which in turn affects residual stresses and distortions, two of the main sources of process-induced defects. The goal of this study...... is to develop a multi-objective approach to optimize the cellular scanning strategy such that the two aforementioned defects are minimized. The decision variable in the chosen problem is a combination of the sequence in which cells are processed and one of six scanning strategies applied to each cell. Thus...

  10. A fuzzy approach to the generation expansion planning problem in a multi-objective environment

    Directory of Open Access Journals (Sweden)

    Abass Samir A.

    2007-01-01

    Full Text Available In many power system problems, the use of optimization techniques has proved inductive to reducing the costs and losses of the system. A fuzzy multi-objective decision is used for solving power system problems. One of the most important issues in the field of power system engineering is the generation expansion planning problem. In this paper, we use the concepts of membership functions to define a fuzzy decision model for generating an optimal solution for this problem. Solutions obtained by the fuzzy decision theory are always efficient and constitute the best compromise. .

  11. 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...... with different compositions of objectives from the horticulture domain are formulated based on a state of the art micro-climate simulator, electricity prices and weather forecasts. The experimental results demonstrate that the Controleum framework support dynamic reconfiguration of the problem formulation...

  12. Multi-objective Design Optimization of a Parallel Schönflies-motion Robot

    DEFF Research Database (Denmark)

    Wu, Guanglei; Bai, Shaoping; Hjørnet, Preben

    2016-01-01

    This paper introduces a parallel Schoenflies-motion robot with rectangular workspace, which is suitable for pick-and-place operations. A multi-objective optimization problem is formulated to optimize the robot's geometric parameters with consideration of kinematic and dynamic performances....... The dynamic performance is concerned mainly the capability of force transmission in the parallel kinematic chain, for which transmission indices are defined. The Pareto-front is obtained to investigate the influence of the design variables to the robot performance. Dynamic characteristics for three Pareto...

  13. Improvements for multi-objective flow shop scheduling by Pareto Iterated Local Search

    CERN Document Server

    Geiger, Martin Josef

    2009-01-01

    The article describes the proposition and application of a local search metaheuristic for multi-objective optimization problems. It is based on two main principles of heuristic search, intensification through variable neighborhoods, and diversification through perturbations and successive iterations in favorable regions of the search space. The concept is successfully tested on permutation flow shop scheduling problems under multiple objectives and compared to other local search approaches. While the obtained results are encouraging in terms of their quality, another positive attribute of the approach is its simplicity as it does require the setting of only very few parameters.

  14. A KIND OF FUZZY MULTI-OBJECTIVE LINEAR PROGRAMMING PROBLEMS BASED ON INTERVAL VALUED FUZZY SETS

    Institute of Scientific and Technical Information of China (English)

    XU Jiuping

    2001-01-01

    This paper presents a general solution procedure and an interactive fuzzy satisfying method for a kind of fuzzy multi-objective linear programming problems based on interval valued fuzzy sets. Firstly, a fuzzy set of the fuzzy solutions, which can be focused on providing complete information for the final decision, can be obtained by the proposed tolerance analysis of a non-dominated set. Secondly, the satisfying solution for the decisionmaker can be derived from Pareto optimal solutions by updating the current reference membership levels on the basis of the current levels of the membership functions together with the trade-off rates between the membership functions.

  15. 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

  16. Electronic design automation of analog ICs combining gradient models with multi-objective evolutionary algorithms

    CERN Document Server

    Rocha, Frederico AE; Lourenço, Nuno CC; Horta, Nuno CG

    2013-01-01

    This book applies to the scientific area of electronic design automation (EDA) and addresses the automatic sizing of analog integrated circuits (ICs). Particularly, this book presents an approach to enhance a state-of-the-art layout-aware circuit-level optimizer (GENOM-POF), by embedding statistical knowledge from an automatically generated gradient model into the multi-objective multi-constraint optimization kernel based on the NSGA-II algorithm. The results showed allow the designer to explore the different trade-offs of the solution space, both through the achieved device sizes, or the resp

  17. Variance approach for multi-objective linear programming with fuzzy random of objective function coefficients

    Science.gov (United States)

    Indarsih, Indrati, Ch. Rini

    2016-02-01

    In this paper, we define variance of the fuzzy random variables through alpha level. We have a theorem that can be used to know that the variance of fuzzy random variables is a fuzzy number. We have a multi-objective linear programming (MOLP) with fuzzy random of objective function coefficients. We will solve the problem by variance approach. The approach transform the MOLP with fuzzy random of objective function coefficients into MOLP with fuzzy of objective function coefficients. By weighted methods, we have linear programming with fuzzy coefficients and we solve by simplex method for fuzzy linear programming.

  18. Multi-Objective and Multi-Constrained Non-Additive Shortest Path Problems

    DEFF Research Database (Denmark)

    Reinhardt, Line Blander; Pisinger, David

    of this paper is to give a general framework for dominance tests for problems involving a number of non-additive criteria. These dominance tests can help eliminate paths in a dynamic programming framework when using multiple objectives. Results on real-life multi-objective problems containing non......Shortest path problems appear as subproblems in numerous optimization problems. In most papers concerning multiple objective shortest path problems, additivity of the objective is a de-facto assumption, but in many real-life situations objectives and criteria, can be non-additive. The purpose...

  19. Multi-Objective and Multi-Constrained Non-Additive Shortest Path Problems

    DEFF Research Database (Denmark)

    Reinhardt, Line Blander; Pisinger, David

    2011-01-01

    of this paper is to give a general framework for dominance tests for problems involving a number of non-additive criteria. These dominance tests can help to eliminate paths in a dynamic programming framework when using multiple objectives. Results on real-life multi-objective problems containing non......Shortest path problems appear as subproblems in numerous optimization problems. In most papers concerning multiple objective shortest path problems, additivity of the objective is a de-facto assumption, but in many real-life situations objectives and criteria, can be non-additive. The purpose...

  20. A performance-oriented power transformer design methodology using multi-objective evolutionary optimization

    Directory of Open Access Journals (Sweden)

    Amr A. Adly

    2015-05-01

    Full Text Available Transformers are regarded as crucial components in power systems. Due to market globalization, power transformer manufacturers are facing an increasingly competitive environment that mandates the adoption of design strategies yielding better performance at lower costs. In this paper, a power transformer design methodology using multi-objective evolutionary optimization is proposed. Using this methodology, which is tailored to be target performance design-oriented, quick rough estimation of transformer design specifics may be inferred. Testing of the suggested approach revealed significant qualitative and quantitative match with measured design and performance values. Details of the proposed methodology as well as sample design results are reported in the paper.

  1. Multi-objective Fuzzy Optimization Algorithm for Separation-Recycle System

    Institute of Scientific and Technical Information of China (English)

    孙力; 樊希山; 姚平经

    2004-01-01

    Separation-recycle system is an important part in chemical process, and its optimization is a multiobjective problem. In this paper the process optimization procedure is proposed. The fuzzy optimization algorithm with the concept of relative importance degree (RID) is utilized to transfer multi-objective optimization (MO-O) model into a single-objective optimization (SO-O) framework. The treatment of process condensate in synthesisa mmonia plant is taken as example to illustrate the optimization procedure, and the satisfactory result demonstrates feasibility and effectiveness of the suggested method.

  2. Multi-objective optimization of an insulating product based on wood fibre material

    Science.gov (United States)

    Hobballah, Mohamad; Vignon, Pierre; Tran, Huyen

    2016-10-01

    This article addresses the optimization of the quality of an insulating material that is based on wood fibres. In a context where several conflicting objectives must be satisfied simultaneously in the design process, meta-heuristic approaches provide efficient methods for optimization. Multi-objective particle swarm optimization (MOPSO) has been chosen here to solve this complex problem in which physical properties such as thermal conductivity and thickness recovery, that are conflicting, are modelled through heterogeneous variables and nonlinear mathematical models. This is an ongoing work; Influence graph and the first mathematical model are presented in this paper while the preliminary optimization results will be presented during the ESAFROM conference.

  3. Fuzzy Multi-Objective Transportation Planning with Modified S-Curve Membership Function

    Science.gov (United States)

    Peidro, D.; Vasant, P.

    2009-08-01

    In this paper, the S-Curve membership function methodology is used in a transportation planning decision (TPD) problem. An interactive method for solving multi-objective TPD problems with fuzzy goals, available supply and forecast demand is developed. The proposed method attempts simultaneously to minimize the total production and transportation costs and the total delivery time with reference to budget constraints and available supply, machine capacities at each source, as well as forecast demand and warehouse space constraints at each destination. We compare in an industrial case the performance of S-curve membership functions, representing uncertainty goals and constraints in TPD problems, with linear membership functions.

  4. A multi-object, multi-field spectrometer and imager for a European ELT

    OpenAIRE

    Evans, Chris; Cunningham, Colin; Atad-Ettedgui, Eli; Allington-Smith, Jeremy; Assemat, Francois; Dalton, Gavin; Hastings, Peter; Hawarden, Timothy; Hook, Isobel; Ivison, Rob; Morris, Simon; Howat, Suzanne Ramsay; Strachan, Mel; Todd, Stephen

    2006-01-01

    One of the highlights of the European ELT Science Case book is the study of resolved stellar populations, potentially out to the Virgo Cluster of galaxies. A European ELT would enable such studies in a wide range of unexplored distant environments, in terms of both galaxy morphology and metallicity. As part of a small study, a revised science case has been used to shape the conceptual design of a multi-object, multi-field spectrometer and imager (MOMSI). Here we present an overview of some ke...

  5. 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...... geometrical details that are critical for electro-thermo-mechanical numerical simulations. © 2013 Elsevier Ltd. All rights reserved....

  6. 2D multi-objective placement algorithm for free-form components

    CERN Document Server

    Jacquenot, Guillaume; Maisonneuve, Jean-Jacques; Wenger, Philippe

    2009-01-01

    This article presents a generic method to solve 2D multi-objective placement problem for free-form components. The proposed method is a relaxed placement technique combined with an hybrid algorithm based on a genetic algorithm and a separation algorithm. The genetic algorithm is used as a global optimizer and is in charge of efficiently exploring the search space. The separation algorithm is used to legalize solutions proposed by the global optimizer, so that placement constraints are satisfied. A test case illustrates the application of the proposed method. Extensions for solving the 3D problem are given at the end of the article.

  7. Critical Comparison of Multi-objective Optimization Methods: Genetic Algorithms versus Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    V. Sedenka

    2010-09-01

    Full Text Available The paper deals with efficiency comparison of two global evolutionary optimization methods implemented in MATLAB. Attention is turned to an elitist Non-dominated Sorting Genetic Algorithm (NSGA-II and a novel multi-objective Particle Swarm Optimization (PSO. The performance of optimizers is compared on three different test functions and on a cavity resonator synthesis. The microwave resonator is modeled using the Finite Element Method (FEM. The hit rate and the quality of the Pareto front distribution are classified.

  8. Multi-Object Spectroscopy with OSIRIS at the 10.4 m GTC

    Science.gov (United States)

    Cabrera-Lavers, A.

    2016-10-01

    OSIRIS is the first light instrument of the 10.4 m GTC. Apart from standard imaging and spectroscopic observing modes, multi-object spectroscopic observations with OSIRIS instrument were initiated in March 2014, with extraordinary success both in the users' demand as well as in the data quality obtained. In this contribution we give a brief description of the process for requesting and defining MOS observations with OSIRIS. We present some numbers on the accuracy obtained in the mask design and on-sky positioning, based on real data obtained at the telescope during the first year of operation of this observing mode.

  9. Genetic algorithm as a tool for multi-objective optimization of permanent magnet disc motor

    Directory of Open Access Journals (Sweden)

    Cvetkovski Goga

    2016-06-01

    Full Text Available The analysed permanent magnet disc motor (PMDM is used for direct wheel drive in an electric vehicle. Therefore there are several objectives that could be tackled in the design procedure, such as an increased efficiency, reduced iron weight, reduced copper weight or reduced weight of the permanent magnets (reduced rotor weight. In this paper the optimal design of PMDM using a multi-objective genetic algorithm optimisation procedure is performed. A comparative analysis of the optimal motor solution and its parameters in relation to the prototype is presented.

  10. A performance-oriented power transformer design methodology using multi-objective evolutionary optimization.

    Science.gov (United States)

    Adly, Amr A; Abd-El-Hafiz, Salwa K

    2015-05-01

    Transformers are regarded as crucial components in power systems. Due to market globalization, power transformer manufacturers are facing an increasingly competitive environment that mandates the adoption of design strategies yielding better performance at lower costs. In this paper, a power transformer design methodology using multi-objective evolutionary optimization is proposed. Using this methodology, which is tailored to be target performance design-oriented, quick rough estimation of transformer design specifics may be inferred. Testing of the suggested approach revealed significant qualitative and quantitative match with measured design and performance values. Details of the proposed methodology as well as sample design results are reported in the paper.

  11. On the Instrument Profile of Slit Spectrographs

    OpenAIRE

    Casini, R.; de Wijn, A.G.

    2014-01-01

    We derive an analytic expression for the instrument profile of a slit spectrograph, also known as the line spread function. While this problem is not new, our treatment relies on the operatorial approach to the description of diffractive optical systems, which provides a general framework for the analysis of the performance of slit spectrographs under different illumination conditions. Based on our results, we propose an approximation to the spectral resolution of slit spectrographs, taking i...

  12. Mixed Gl2/GH2 multi-channel multi-objective control synthesis for discrete time systems

    Institute of Scientific and Technical Information of China (English)

    颜文俊; 张森林

    2004-01-01

    This paper proposes a new approach for multi-objective robust control.The approach extends the standard generalized l2(Gl2)and generalized H2(GH2)conditions to a set of new linear matrix inequality(LMI)constraints based on a new stability condition.A technique for variable parameterization is introduced to the multi-objective control problem to preserve the linearity of the synthesis variables.Consequently,the multi-channel multi-objective mixed Gl2/GH2 control problem can be solved less conservatively using computationally tractable algorithms developed in the paper.

  13. Improved Fuzzification Method for Multi-Objective Decision-Making and Its Application in Evaluation of Highway Planning

    Institute of Scientific and Technical Information of China (English)

    雷秀娟; 史忠科

    2003-01-01

    A new fuzzification method for multi-objective decision-making and selective sorting is proposed on the basis of the fuzzy consistent relation, and the specific algorithm is presented. The method is applied to the evaluation of highway planning of Zhanjiang city. To decrease the subjectivity in the process of decision-making, the LOWA operator is introduced, and a discussion on how to select appropriate weights involved in multi-objective sorting is made. It is concluded that it is feasible to apply the fuzzy consistent relation to multi-objective decision-making analysis, and the improved fuzzication method is workable.

  14. 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.

  15. Development of a multi-objective optimization algorithm using surrogate models for coastal aquifer management

    Science.gov (United States)

    Kourakos, George; Mantoglou, Aristotelis

    2013-02-01

    SummaryThe demand for fresh water in coastal areas and islands can be very high due to increased local needs and tourism. A multi-objective optimization methodology is developed, involving minimization of economic and environmental costs while satisfying water demand. The methodology considers desalinization of pumped water and injection of treated water into the aquifer. Variable density aquifer models are computationally intractable when integrated in optimization algorithms. In order to alleviate this problem, a multi-objective optimization algorithm is developed combining surrogate models based on Modular Neural Networks [MOSA(MNNs)]. The surrogate models are trained adaptively during optimization based on a genetic algorithm. In the crossover step, each pair of parents generates a pool of offspring which are evaluated using the fast surrogate model. Then, the most promising offspring are evaluated using the exact numerical model. This procedure eliminates errors in Pareto solution due to imprecise predictions of the surrogate model. The method has important advancements compared to previous methods such as precise evaluation of the Pareto set and alleviation of propagation of errors due to surrogate model approximations. The method is applied to an aquifer in the Greek island of Santorini. The results show that the new MOSA(MNN) algorithm offers significant reduction in computational time compared to previous methods (in the case study it requires only 5% of the time required by other methods). Further, the Pareto solution is better than the solution obtained by alternative algorithms.

  16. A diagnostic assessment of evolutionary algorithms for multi-objective surface water reservoir control

    Science.gov (United States)

    Zatarain Salazar, Jazmin; Reed, Patrick M.; Herman, Jonathan D.; Giuliani, Matteo; Castelletti, Andrea

    2016-06-01

    Globally, the pressures of expanding populations, climate change, and increased energy demands are motivating significant investments in re-operationalizing existing reservoirs or designing operating policies for new ones. These challenges require an understanding of the tradeoffs that emerge across the complex suite of multi-sector demands in river basin systems. This study benchmarks our current capabilities to use Evolutionary Multi-Objective Direct Policy Search (EMODPS), a decision analytic framework in which reservoirs' candidate operating policies are represented using parameterized global approximators (e.g., radial basis functions) then those parameterized functions are optimized using multi-objective evolutionary algorithms to discover the Pareto approximate operating policies. We contribute a comprehensive diagnostic assessment of modern MOEAs' abilities to support EMODPS using the Conowingo reservoir in the Lower Susquehanna River Basin, Pennsylvania, USA. Our diagnostic results highlight that EMODPS can be very challenging for some modern MOEAs and that epsilon dominance, time-continuation, and auto-adaptive search are helpful for attaining high levels of performance. The ɛ-MOEA, the auto-adaptive Borg MOEA, and ɛ-NSGAII all yielded superior results for the six-objective Lower Susquehanna benchmarking test case. The top algorithms show low sensitivity to different MOEA parameterization choices and high algorithmic reliability in attaining consistent results for different random MOEA trials. Overall, EMODPS poses a promising method for discovering key reservoir management tradeoffs; however algorithmic choice remains a key concern for problems of increasing complexity.

  17. Stability of multi-objective bi-level linear programming problems under fuzziness

    Directory of Open Access Journals (Sweden)

    Abo-Sinna Mahmoud A.

    2013-01-01

    Full Text Available This paper deals with multi-objective bi-level linear programming problems under fuzzy environment. In the proposed method, tentative solutions are obtained and evaluated by using the partial information on preference of the decision-makers at each level. The existing results concerning the qualitative analysis of some basic notions in parametric linear programming problems are reformulated to study the stability of multi-objective bi-level linear programming problems. An algorithm for obtaining any subset of the parametric space, which has the same corresponding Pareto optimal solution, is presented. Also, this paper established the model for the supply-demand interaction in the age of electronic commerce (EC. First of all, the study uses the individual objectives of both parties as the foundation of the supply-demand interaction. Subsequently, it divides the interaction, in the age of electronic commerce, into the following two classifications: (i Market transactions, with the primary focus on the supply demand relationship in the marketplace; and (ii Information service, with the primary focus on the provider and the user of information service. By applying the bi-level programming technique of interaction process, the study will develop an analytical process to explain how supply-demand interaction achieves a compromise or why the process fails. Finally, a numerical example of information service is provided for the sake of illustration.

  18. 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.

  19. Comparison of multi-objective evolutionary approaches for task scheduling in distributed computing systems

    Indian Academy of Sciences (India)

    G Subashini; M C Bhuvaneswari

    2012-12-01

    Parallel and distributed systems play an important part in the improvement of high performance computing. In these type of systems task scheduling is a key issue in achieving high performance of the system. In general, task scheduling problems have been shown to be NP-hard. As deterministic techniques consume much time in solving the problem, several heuristic methods are attempted in obtaining optimal solutions. This paper presents an application of Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and a Non-dominated Sorting Particle Swarm Optimization Algorithm (NSPSO) to schedule independent tasks in a distributed system comprising of heterogeneous processors. The problem is formulated as a multi-objective optimization problem, aiming to obtain schedules achieving minimum makespan and flowtime. The applied algorithms generate Pareto set of global optimal solutions for the considered multi-objective scheduling problem. The algorithms are validated against a set of benchmark instances and the performance of the algorithms evaluated using standard metrics. Experimental results and performance measures infer that NSGA-II produces quality schedules compared to NSPSO.

  20. Print-to-print: a facile multi-object micro-patterning technique.

    Science.gov (United States)

    Xing, Siyuan; Zhao, Siwei; Pan, Tingrui

    2013-04-01

    In recent years, micropatterning techniques have gained increasing popularity from a broad range of engineering and biology communities for the promise to establish highly quantitative investigations on miniature biological objects (e.g., cells and bacteria) with spatially defined microenvironments. However, majority of the existing techniques rely on cleanroom-based microfabrication and cannot be easily extended to a regular biological laboratory. In this paper, we present a simple versatile printing-based method, referred to as Print-to-Print (P2P), to form multi-object micropatterns for potential biological applications, along with our recent efforts to deliver out-of-cleanroom microfabrication solutions to the general public (Zhao et al. 2009), (Xing et al. 2011), (Wang et al. 2009), (Pan and Wang 2011), (Zhao et al. 2011). The P2P method employs only a commercially available solid-phase printer and custom-made superhydrophobic films. The entire patterning process does not involve any thermal or chemical treatment. Moreover, the non-contact nature of droplet transferring and printing steps can be highly advantageous for sensitive biological uses. Using the P2P process, a minimal feature resolution of 229 ± 17 μm has been successfully demonstrated. In addition, this approach has been applied to form biological micropatterning on various substrates as well as multi-object co-patterns on the commonly used surfaces. Finally, the reusability of superhydrophobic substrates has also been illustrated.

  1. A vague-set-based fuzzy multi-objective decision making model for bidding purchase

    Institute of Scientific and Technical Information of China (English)

    WANG Zhou-jing; QIAN Edward Y.

    2007-01-01

    A vague-set-based fuzzy multi-objective decision making model is developed for evaluating bidding plans in a bidding purchase process. A group of decision-makers (DMs) first independently assess bidding plans according to their experience and preferences, and these assessments may be expressed as linguistic terms, which are then converted to fuzzy numbers. The resulting decision matrices are then transformed to objective membership grade matrices. The lower bound of satisfaction and upper bound of dissatisfaction are used to determine each bidding plan's supporting, opposing, and neutral objective sets, which together determine the vague value of a bidding plan. Finally, a score function is employed to rank all bidding plans. A new score function based on vague sets is introduced in the model and a novel method is presented for calculating the lower bound of satisfaction and upper bound of dissatisfaction. In a vague-set-based fuzzy multi-objective decision making model, different valuations for upper and lower bounds of satisfaction usually lead to distinct ranking results. Therefore, it is crucial to effectively contain DMs' arbitrariness and subjectivity when these values are determined.

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

    Science.gov (United States)

    Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

    2014-09-01

    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.

  3. Environmental multi-objective optimization of the use of biomass resources for energy.

    Science.gov (United States)

    Vadenbo, Carl; Tonini, Davide; Astrup, Thomas Fruergaard

    2017-02-17

    Bioenergy is often considered an important component, alongside other renewables, to mitigate global warming and to reduce fossil fuel dependency. Determining sustainable strategies for utilizing biomass resources, however, requires a holistic perspective to reflect a wider range of potential environmental consequences. To circumvent the limitations of scenario-based life cycle assessment (LCA), we develop a multi-objective optimization model to systematically identify the environmentally-optimal use of biomass for energy under given system constraints. Besides satisfying annual final energy demand, the model constraints comprise availability of biomass and arable land, technology- and system-specific capacities, and relevant policy targets. Efficiencies and environmental performances of bioenergy conversions are derived using biochemical process models combined with LCA data. The application of the optimization model is exemplified by a case aimed at determining the environmentally-optimal use of biomass in the Danish energy system in 2025. A multi-objective formulation based on fuzzy intervals for six environmental impact categories resulted in impact reductions of 13-43% compared to the baseline. The robustness of the optimal solution was analyzed with respect to parameter uncertainty and choice of environmental objectives.

  4. Multi-objective Extremum Seeking Control for Enhancement of Wind Turbine Power Capture with Load Reduction

    Science.gov (United States)

    Xiao, Yan; Li, Yaoyu; Rotea, Mario A.

    2016-09-01

    The primary objective in below rated wind speed (Region 2) is to maximize the turbine's energy capture. Due to uncertainty, variability of turbine characteristics and lack of inexpensive but precise wind measurements, model-free control strategies that do not use wind measurements such as Extremum Seeking Control (ESC) have received significant attention. Based on a dither-demodulation scheme, ESC can maximize the wind power capture in real time despite uncertainty, variabilities and lack of accurate wind measurements. The existing work on ESC based wind turbine control focuses on power capture only. In this paper, a multi-objective extremum seeking control strategy is proposed to achieve nearly optimum wind energy capture while decreasing structural fatigue loads. The performance index of the ESC combines the rotor power and penalty terms of the standard deviations of selected fatigue load variables. Simulation studies of the proposed multi-objective ESC demonstrate that the damage-equivalent loads of tower and/or blade loads can be reduced with slight compromise in energy capture.

  5. Multi-Objective Low-Carbon Economic Dispatch Considering Demand Response with Wind Power Integrated Systems

    Directory of Open Access Journals (Sweden)

    Liu Wenjuan

    2017-01-01

    Full Text Available The generation cost, carbon emissions and customers’ satisfaction are considered in this paper. On the basis of this, the multi-objective and low-carbon economic dispatch model with wind farm, this considers demand response, is established. The model user stochastic programming theory to describe the uncertainty of the wind power and converts it into an equivalent deterministic model by using distribution function of wind power output, optimizes demand side resources to adjust the next day load curve and to improve load rate and absorptive capacity of wind power, introduce customers’ satisfaction to ensure that the scheduling scheme satisfies customer and integrate the resources of source and load to unify coordination wind farm access to network and to meet the requirements of energy saving and emission reduction. The search process of artificial fish school algorithm introducing Tabu search and more targeted search mechanism, an multi-objective improved artificial fish school algorithm is proposed to solve this model. Using the technique for order preference by similarity to ideal solution (TOPSIS to sort the Pareto frontier, the optimal scheduling scheme is determined. Simulation results verify the rationality and validity of the proposed model and algorithm.

  6. A multi-objective optimisation model for a general polymer electrolyte membrane fuel cell system

    Science.gov (United States)

    Ang, Sheila Mae C.; Brett, Daniel J. L.; Fraga, Eric S.

    This paper presents an optimisation model for a general polymer electrolyte membrane (PEM) fuel cell system suitable for efficiency and size trade-offs investigation. Simulation of the model for a base case shows that for a given output power, a more efficient system is bigger and vice versa. Using the weighting method to perform a multi-objective optimisation, the Pareto sets were generated for different stack output powers. A Pareto set, presented as a plot of the optimal efficiency and area of the membrane electrode assembly (MEA), gives a quantitative description of the compromise between efficiency and size. Overall, our results indicate that, to make the most of the size-efficiency trade-off behaviour, the system must be operated at an efficiency of at least 40% but not more than 47%. Furthermore, the MEA area should be at least 3 cm 2 W -1 for the efficiency to be practically useful. Subject to the constraints imposed on the model, which are based on technical practicalities, a PEM fuel cell system such as the one presented in this work cannot operate at an efficiency above 54%. The results of this work, specifically the multi-objective model, will form a useful and practical basis for subsequent techno-economic studies for specific applications.

  7. Multi-objective Trajectory Planning of FFSM Carrying a Heavy Payload

    Directory of Open Access Journals (Sweden)

    Yong Liu

    2015-09-01

    Full Text Available Aiming at carrying a heavy payload to a desired pose (including position and orientation, a multi-objective optimization-based approach for maximum-payload trajectory planning of free-floating space manipulators (FFSM is proposed in this paper. The presented approach corresponds to two typical applications: (i the manipulator joints attain the desired states; (ii the inertial pose of the end-effector (pose with respect to the inertial frame attains the desired values, for which a novel two-stage method is presented. Firstly, for the purpose of reducing computational complexity, dynamics equations are derived using a spatial operator algebra (SOA method. Secondly, objective functions are defined according to the improvement of load-carrying capacity and pose requirements of the end-effector. Then, the joint trajectories are specified using sinusoidal polynomial functions. Finally, a multi objective particle optimization (MOPSO algorithm is employed to obtain a non-dominated solution set, during which process particles that do not satisfy the constraints are eliminated. Simulations are performed for a 7-DOF FFSM, considering three and five objectives for optimization in the two applications, respectively. The results demonstrate that the proposed approach can provide satisfactory joint trajectories and improve load-carrying capacity effectively.

  8. Modelling and Multi-Objective Optimal Control of Batch Processes Using Recurrent Neuro-fuzzy Networks

    Institute of Scientific and Technical Information of China (English)

    Jie Zhang

    2006-01-01

    In this paper, the modelling and multi-objective optimal control of batch processes, using a recurrent neuro-fuzzy network, are presented. The recurrent neuro-fuzzy network, forms a "global" nonlinear long-range prediction model through the fuzzy conjunction of a number of "local" linear dynamic models. Network output is fed back to network input through one or more time delay units, which ensure that predictions from the recurrent neuro-fuzzy network are long-range. In building a recurrent neural network model, process knowledge is used initially to partition the processes non-linear characteristics into several local operating regions, and to aid in the initialisation of corresponding network weights. Process operational data is then used to train the network. Membership functions of the local regimes are identified, and local models are discovered via network training. Based on a recurrent neuro-fuzzy network model, a multi-objective optimal control policy can be obtained. The proposed technique is applied to a fed-batch reactor.

  9. Surrogate-based Multi-Objective Optimization and Uncertainty Quantification Methods for Large, Complex Geophysical Models

    Science.gov (United States)

    Gong, Wei; Duan, Qingyun

    2016-04-01

    Parameterization scheme has significant influence to the simulation ability of large, complex dynamic geophysical models, such as distributed hydrological models, land surface models, weather and climate models, etc. with the growing knowledge of physical processes, the dynamic geophysical models include more and more processes and producing more output variables. Consequently the parameter optimization / uncertainty quantification algorithms should also be multi-objective compatible. Although such algorithms have long been available, they usually require a large number of model runs and are therefore computationally expensive for large, complex dynamic models. In this research, we have developed surrogate-based multi-objective optimization method (MO-ASMO) and Markov Chain Monte Carlo method (MC-ASMO) for uncertainty quantification for these expensive dynamic models. The aim of MO-ASMO and MC-ASMO is to reduce the total number of model runs with appropriate adaptive sampling strategy assisted by surrogate modeling. Moreover, we also developed a method that can steer the search process with the help of prior parameterization scheme derived from the physical processes involved, so that all of the objectives can be improved simultaneously. The proposed algorithms have been evaluated with test problems and a land surface model - the Common Land Model (CoLM). The results demonstrated their effectiveness and efficiency.

  10. Design for sustainability of industrial symbiosis based on emergy and multi-objective particle swarm optimization.

    Science.gov (United States)

    Ren, Jingzheng; Liang, Hanwei; Dong, Liang; Sun, Lu; Gao, Zhiqiu

    2016-08-15

    Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex. Through incorporating the emergy theory, the model is formulated as a multi-objective approach that can optimize both the economic benefit and sustainable performance of the integrated industrial system. A set of emergy based evaluation index are designed. Multi-objective Particle Swarm Algorithm is proposed to solve the model, and the decision-makers are allowed to choose the suitable solutions form the Pareto solutions. An illustrative case has been studied by the proposed method, a few of compromises between high profitability and high sustainability can be obtained for the decision-makers/stakeholders to make decision. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Multi-objective portfolio optimization of mutual funds under downside risk measure using fuzzy theory

    Directory of Open Access Journals (Sweden)

    M. Amiri

    2012-10-01

    Full Text Available Mutual fund is one of the most popular techniques for many people to invest their funds where a professional fund manager invests people's funds based on some special predefined objectives; therefore, performance evaluation of mutual funds is an important problem. This paper proposes a multi-objective portfolio optimization to offer asset allocation. The proposed model clusters mutual funds with two methods based on six characteristics including rate of return, variance, semivariance, turnover rate, Treynor index and Sharpe index. Semivariance is used as a downside risk measure. The proposed model of this paper uses fuzzy variables for return rate and semivariance. A multi-objective fuzzy mean-semivariance portfolio optimization model is implemented and fuzzy programming technique is adopted to solve the resulted problem. The proposed model of this paper has gathered the information of mutual fund traded on Nasdaq from 2007 to 2009 and Pareto optimal solutions are obtained considering different weights for objective functions. The results of asset allocation, rate of return and risk of each cluster are also determined and they are compared with the results of two clustering methods.

  12. Multi-objective Genetic Algorithm for System Identification and Controller Optimization of Automated Guided Vehicle

    Directory of Open Access Journals (Sweden)

    Xing Wu

    2011-07-01

    Full Text Available This paper presents a multi-objective genetic algorithm (MOGA with Pareto optimality and elitist tactics for the control system design of automated guided vehicle (AGV. The MOGA is used to identify AGV driving system model and optimize its servo control system sequentially. In system identification, the model identified by least square method is adopted as an evolution tutor who selects the individuals having balanced performances in all objectives as elitists. In controller optimization, the velocity regulating capability required by AGV path tracking is employed as decision-making preferences which select Pareto optimal solutions as elitists. According to different objectives and elitist tactics, several sub-populations are constructed and they evolve concurrently by using independent reproduction, neighborhood mutation and heuristic crossover. The lossless finite precision method and the multi-objective normalized increment distance are proposed to keep the population diversity with a low computational complexity. Experiment results show that the cascaded MOGA have the capability to make the system model consistent with AGV driving system both in amplitude and phase, and to make its servo control system satisfy the requirements on dynamic performance and steady-state accuracy in AGV path tracking.

  13. A Multi-Objective Demand Side Management Considering ENS Cost in Smart Grids

    DEFF Research Database (Denmark)

    Yousefi Khanghah, Babak; Ghassemzadeh, Saeid; Hosseini, Seyed Hossein

    2017-01-01

    In this paper a new method is presented to achieve economic exploitation and proper usage of network capacity by exerting controlling actions over flexible loads and energy storage (ES) equipment. Multi-objective planning for demand response programs (DRP) and battery management policies is carri...... company (DisCo) modifies energy cost as a signal for DGO in order to coordinate with each other. So, behavior of DGO is based on modified energy price applied by upstream system considering ENS price....... out by considering energy not supplied (ENS). In order to achieve an optimal scheduling, charge/discharge control for batteries, demand response programs and dispatch of controllable distributed generations (DGs) are also considered. Then, the balanced cost and benefits of participants are evaluated....... As a whole, the main objective of this paper is to manage the load and energy storage options in a smart grid to reduce ENS, to minimize overall operation cost and to maximize DG operators’ (DGOs) profit. These goals are obtained by considering ENS cost in a multi-objective optimization problem. Distribution...

  14. Multi-Objective Random Search Algorithm for Simultaneously Optimizing Wind Farm Layout and Number of Turbines

    Science.gov (United States)

    Feng, Ju; Shen, Wen Zhong; Xu, Chang

    2016-09-01

    A new algorithm for multi-objective wind farm layout optimization is presented. It formulates the wind turbine locations as continuous variables and is capable of optimizing the number of turbines and their locations in the wind farm simultaneously. Two objectives are considered. One is to maximize the total power production, which is calculated by considering the wake effects using the Jensen wake model combined with the local wind distribution. The other is to minimize the total electrical cable length. This length is assumed to be the total length of the minimal spanning tree that connects all turbines and is calculated by using Prim's algorithm. Constraints on wind farm boundary and wind turbine proximity are also considered. An ideal test case shows the proposed algorithm largely outperforms a famous multi-objective genetic algorithm (NSGA-II). In the real test case based on the Horn Rev 1 wind farm, the algorithm also obtains useful Pareto frontiers and provides a wide range of Pareto optimal layouts with different numbers of turbines for a real-life wind farm developer.

  15. An inexact multi-objective programming approach for strategic environmental assessment on regional development plan

    Institute of Scientific and Technical Information of China (English)

    WANG Jihua; GUO Huaicheng; LIU Lei; HAO Mingjia; ZHANG Ming; LU Xiaojian; XING Kexia

    2004-01-01

    This paper presents the development of an inexact multi-objective programming (IMOP) model and its application to the strategic environmental assessment (SEA) for the regional development plan for the Hunnan New Zone (HNZ) in Shenyang City, China. Inexact programming and multi-objective programming methods are employed to effectively account for extensive uncertainties in the study system and to reflect various interests from different stakeholders, respectively. In the case study, balancing-economy-and-environment scenario and focusing-industry-development scenario are analyzed by the interactive solution process for addressing the preferences from local authorities and compromises among different objectives. Through interpreting the model solutions under both scenarios, analysis of industrial structure, waste water treatment plant(WWTP) expansion, water consumption and pollution generation and treatment are undertaken for providing a solid base to justify and evaluate the HNZ regional development plan. The study results show that the developed IMOP-SEA framework is feasible and applicable in carrying comprehensive environmental impact assessments for development plan in a more effective and efficient manner.

  16. Monte Carlo modelling of multi-object adaptive optics performance on the European Extremely Large Telescope

    Science.gov (United States)

    Basden, A. G.; Morris, T. J.

    2016-12-01

    The performance of a wide-field adaptive optics (AO) system depends on input design parameters. Here we investigate the performance of a multi-object AO system design for the European Extremely Large Telescope, using an end-to-end Monte Carlo AO simulation tool, Durham adaptive optics simulation platform, with relevance for proposed instruments such as MOSAIC. We consider parameters such as the number of laser guide stars, sodium layer depth, wavefront sensor pixel scale, actuator pitch and natural guide star availability. We provide potential areas where costs savings can be made, and investigate trade-offs between performance and cost, and provide solutions that would enable such an instrument to be built with currently available technology. Our key recommendations include a trade-off for laser guide star wavefront sensor pixel scale of about 0.7 arcsec per pixel, and a field of view of at least 7 arcsec, that electron multiplying CCD technology should be used for natural guide star wavefront sensors even if reduced frame rate is necessary, and that sky coverage can be improved by a slight reduction in natural guide star sub-aperture count without significantly affecting tomographic performance. We find that AO correction can be maintained across a wide field of view, up to 7 arcmin in diameter. We also recommend the use of at least four laser guide stars, and include ground-layer and multi-object AO performance estimates.

  17. 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.

  18. Multi-Objective Sensitivity Analyses for Power Generation Mix: Malaysia Case Study

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    Siti Mariam Mohd Shokri

    2017-08-01

    Full Text Available 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 that Malaysia optimum generation mix in 2030 for, 1 economic case is 48% from coal, 41% from gas, 3% from hydro and 8% from RE, 2 environmental case is 19% from coal, 58% from gas, 11% from hydro and 12% from RE, 3 for reliability case is 64% from coal, 32% from gas, 3% from hydro and 1% from RE and 4 multi-objective case is 49% from coal, 41% from gas, 7% from hydro and 3% from RE. The findings of this paper are the optimum generation mix for Malaysia from 2013 to 2030 which is less expensive, substantially reduce carbon emission and that less risky.  

  19. Multi-objective Genetic Algorithm for Association Rule Mining Using a Homogeneous Dedicated Cluster of Workstations

    Directory of Open Access Journals (Sweden)

    S. Dehuri

    2006-01-01

    Full Text Available This study presents a fast and scalable multi-objective association rule mining technique using genetic algorithm from large database. The objective functions such as confidence factor, comprehensibility and interestingness can be thought of as different objectives of our association rule-mining problem and is treated as the basic input to the genetic algorithm. The outcomes of our algorithm are the set of non-dominated solutions. However, in data mining the quantity of data is growing rapidly both in size and dimensions. Furthermore, the multi-objective genetic algorithm (MOGA tends to be slow in comparison with most classical rule mining methods. Hence, to overcome these difficulties we propose a fast and scalability technique using the inherent parallel processing nature of genetic algorithm and a homogeneous dedicated network of workstations (NOWs. Our algorithm exploit both data and control parallelism by distributing the data being mined and the population of individuals across all available processors. The experimental result shows that the algorithm has been found suitable for large database with an encouraging speed up.

  20. Multi-objective optimisation and decision-making of space station logistics strategies

    Science.gov (United States)

    Zhu, Yue-he; Luo, Ya-zhong

    2016-10-01

    Space station logistics strategy optimisation is a complex engineering problem with multiple objectives. Finding a decision-maker-preferred compromise solution becomes more significant when solving such a problem. However, the designer-preferred solution is not easy to determine using the traditional method. Thus, a hybrid approach that combines the multi-objective evolutionary algorithm, physical programming, and differential evolution (DE) algorithm is proposed to deal with the optimisation and decision-making of space station logistics strategies. A multi-objective evolutionary algorithm is used to acquire a Pareto frontier and help determine the range parameters of the physical programming. Physical programming is employed to convert the four-objective problem into a single-objective problem, and a DE algorithm is applied to solve the resulting physical programming-based optimisation problem. Five kinds of objective preference are simulated and compared. The simulation results indicate that the proposed approach can produce good compromise solutions corresponding to different decision-makers' preferences.

  1. Multi-objective optimisation in carbon monoxide gas management at TRONOX KXN Sands

    Directory of Open Access Journals (Sweden)

    Stadler, Johan

    2014-08-01

    Full Text Available Carbon monoxide (CO is a by-product of the ilmenite smelting process from which titania slag and pig iron are produced. Prior to this project, the CO at Tronox KZN Sands in South Africa was burnt to get rid of it, producing carbon dioxide (CO2. At this plant, unprocessed materials are pre-heated using methane gas from an external supplier. The price of methane gas has increased significantly; and so this research considers the possibility of recycling CO gas and using it as an energy source to reduce methane gas demand. It is not possible to eliminate the methane gas consumption completely due to the energy demand fluctuation, and sub-plants have been assigned either CO gas or methane gas over time. Switching the gas supply between CO and methane gas involves production downtime to purge supply lines. Minimising the loss of production time while maximising the use of CO arose as a multi-objective optimisation problem (MOP with seven decision variables, and computer simulation was used to evaluate scenarios. We applied computer simulation and the multi-objective optimisation cross-entropy method (MOO CEM to find good solutions while evaluating the minimum number of scenarios. The proposals in this paper, which are in the process of being implemented, could save the company operational expenditure while reducing the carbon footprint of the smelter.

  2. Multi-objective H ∞ control for vehicle active suspension systems with random actuator delay

    Science.gov (United States)

    Li, Hongyi; Liu, Honghai; Hand, Steve; Hilton, Chris

    2012-12-01

    This article is concerned with the problem of multi-objective H ∞ control for vehicle active suspension systems with random actuator delay, which can be represented by signal probability distribution. First, the dynamical equations of a quarter-car suspension model are established for the control design purpose. Secondly, when taking into account vehicle performance requirements, namely, ride comfort, suspension deflection and the probability distributed actuator delay, we present the corresponding dynamic system, which will be transformed to the stochastic system for the problem of multi-objective H ∞ controller design. Third, based on the stochastic stability theory, the state feedback controller is proposed to render that the closed-loop system is exponentially stable in mean-square while simultaneously satisfying H ∞ performance and the output constraint requirement. The presented condition is expressed in the form of convex optimisation problems so that it can be efficiently solved via standard numerical software. Finally, a practical design example is given to demonstrate the effectiveness of the proposed method.

  3. Multi-Objective Dynamic Economic Dispatch of Microgrid Systems Including Vehicle-to-Grid

    Directory of Open Access Journals (Sweden)

    Haitao Liu

    2015-05-01

    Full Text Available Based on the characteristics of electric vehicles (EVs, this paper establishes the load models of EVs under the autonomous charging mode and the coordinated charging and discharging mode. Integrating the EVs into a microgrid system which includes wind turbines (WTs, photovoltaic arrays (PVs, diesel engines (DEs, fuel cells (FCs and a storage battery (BS, this paper establishes multi-objective economic dispatch models of a microgrid, including the lowest operating cost, the least carbon dioxide emissions, and the lowest pollutant treatment cost. After converting the multi-objective functions to a single objective function by using the judgment matrix method, we analyze the dynamic economic dispatch of the microgrid system including vehicle-to-grid (V2G with an improved particle swarm optimization algorithm under different operation control strategies. With the example system, the proposed models and strategies are verified and analyzed. Simulation results show that the microgrid system with EVs under the coordinated charging and discharging mode has better operation economics than the autonomous charging mode. Meanwhile, the greater the load fluctuation is, the higher the operating cost of the microgrid system is.

  4. Multi-objective behavioural mechanisms are adopted by foraging animals to achieve several optimality goals simultaneously.

    Science.gov (United States)

    Wajnberg, Eric

    2012-03-01

    1. Animals foraging for resources are under a variety of selective pressures, and separate optimality models have been developed predicting the optimal reproductive strategies they should adopt. 2. In most cases, the proximate behavioural mechanisms adopted to achieve such optimality goals have been identified. This is the case, for example, for optimal patch time and sex allocation in insect parasitoids. However, behaviours modelled within this framework have mainly been studied separately, even though real animals have to optimize some behaviours simultaneously. 3. For this reason, it would be better if proximate behavioural rules were designed to attain several goals simultaneously. Despite their importance, such multi-objective proximate rules remain to be discovered. 4. Based on experiments on insect parasitoids that simultaneously examine their optimal patch time and sex allocation strategies, it is shown here that animals can adopt multi-objective behavioural mechanisms that appear consistent with the two optimal goals simultaneously. 5. Results of computer simulations demonstrate that these behavioural mechanisms are indeed consistent with optimal reproductive strategies and have thus been most likely selected over the course of the evolutionary time.

  5. A Global Multi-Objective Optimization Tool for Design of Mechatronic Components using Generalized Differential Evolution

    DEFF Research Database (Denmark)

    Bech, Michael Møller; Nørgård, Christian; Roemer, Daniel Beck

    2016-01-01

    This paper illustrates how the relatively simple constrained multi-objective optimization algorithm Generalized Differential Evolution 3 (GDE3), can assist with the practical sizing of mechatronic components used in e.g. digital displacement fluid power machinery. The studied bi- and tri-objectiv...... different optimization control parameter settings and it is concluded that GDE3 is a reliable optimization tool that can assist mechatronic engineers in the design and decision making process.......This paper illustrates how the relatively simple constrained multi-objective optimization algorithm Generalized Differential Evolution 3 (GDE3), can assist with the practical sizing of mechatronic components used in e.g. digital displacement fluid power machinery. The studied bi- and tri......-objective problems having 10+ design variables are both highly constrained, nonlinear and non-smooth but nevertheless the algorithm converges to the Pareto-front within a hours of computation (20k function evaluations). Additionally, the robustness and convergence speed of the algorithm are investigated using...

  6. Capacitated Windy Rural Postman Problem with Several Vehicles: A Hybrid Multi-Objective Simulated Annealing Algorithm

    Directory of Open Access Journals (Sweden)

    Masoud Rabbani

    2016-02-01

    Full Text Available This paper presents the capacitated Windy Rural Postman Problem with several vehicles. For this problem, two objectives are considered. One of them is the minimization of the total cost of all vehicle routes expressed by the sum of the total traversing cost and another one is reduction of the maximum cost of vehicle route in order to find a set of equitable tours for the vehicles. Mathematical formulation is provided. The multi-objective simulated annealing (MOSA algorithm has been modified for solving this bi-objective NP-hard problem. To increase algorithm performance, Taguchi technique is applied to design experiments for tuning parameters of the algorithm. Numerical experiments are proposed to show efficiency of the model. Finally, the results of the MOSA have been compared with MOCS (multi-objective Cuckoo Search algorithm to validate the performance of the proposed algorithm. The experimental results indicate that the proposed algorithm provides good solutions and performs significantly better than the MOCS.

  7. A Pareto archive floating search procedure for solving multi-objective flexible job shop scheduling problem

    Directory of Open Access Journals (Sweden)

    J. S. Sadaghiani

    2014-04-01

    Full Text Available Flexible job shop scheduling problem is a key factor of using efficiently in production systems. This paper attempts to simultaneously optimize three objectives including minimization of the make span, total workload and maximum workload of jobs. Since the multi objective flexible job shop scheduling problem is strongly NP-Hard, an integrated heuristic approach has been used to solve it. The proposed approach was based on a floating search procedure that has used some heuristic algorithms. Within floating search procedure utilize local heuristic algorithms; it makes the considered problem into two sections including assigning and sequencing sub problem. First of all search is done upon assignment space achieving an acceptable solution and then search would continue on sequencing space based on a heuristic algorithm. This paper has used a multi-objective approach for producing Pareto solution. Thus proposed approach was adapted on NSGA II algorithm and evaluated Pareto-archives. The elements and parameters of the proposed algorithms were adjusted upon preliminary experiments. Finally, computational results were used to analyze efficiency of the proposed algorithm and this results showed that the proposed algorithm capable to produce efficient solutions.

  8. Stereomask lithography (SML): a universal multi-object micro-patterning technique for biological applications.

    Science.gov (United States)

    Zhao, Siwei; Chen, Arnold; Revzin, Alexander; Pan, Tingrui

    2011-01-21

    The advent of biological micro-patterning techniques has given new impetus to many areas of biological research, including quantitative biochemical analysis, tissue engineering, biosensing, and regenerative medicine. Derived from photolithography or soft lithography, current bio-patterning approaches have yet to completely address the needs of out-of-cleanroom, universal applicability, high feature resolution, as well as multi-object placement, though many have shown great promise to precisely pattern one specific biomaterial. In this paper, we present a novel versatile biological lithography technique to achieve integrated multi-object patterning with high feature resolution and high adaptability to various biomaterials, referred to as stereomask lithography (SML). Successive patterning of multiple objects is enabled by using unique three-dimensional masks (i.e., the stereomasks), which lay out current micropatterns while protecting pre-existing biological features on the substrate. Furthermore, high-precision reversible alignment among multiple bio-objects is achieved by adopting a peg-in-hole design between the substrate and stereomasks. We demonstrate that the SML technique is capable of constructing a complex biological microenvironment with various bio-functional components at the single-cell resolution, which to the best of our knowledge has not been realized before.

  9. 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.

  10. A multi-objective optimisation model for sewer rehabilitation considering critical risk of failure.

    Science.gov (United States)

    Ward, Ben; Savić, Dragan A

    2012-01-01

    A unique methodology for the optimal specification of sewer rehabilitation investment is presented in this paper. By accounting for the critical risk of asset failure, this methodology builds on previously successful work which explored the application of multi-objective optimisation tools to assist engineers with the specification of optimal rehabilitation strategies. The conventional sewerage rehabilitation specification process relies on the expertise of professional engineers to manually evaluate CCTV inspection information when determining the nature and extent of the rehabilitation solution. This process is not only tedious and subjective but it has no quantifiable means of identifying optimal solutions or possible combinations of optimal solutions in the delivery of catchment wide rehabilitation programmes. Therefore, the purely manual process of sewer rehabilitation design leaves a number of unanswered questions, such as: (1) Does the solution offer the greatest structural benefit to the network? (2) Is the solution the most cost-effective solution available? (3) Does the solution most greatly reduce the risk of critical asset failure? The application of a multi-objective genetic algorithm optimisation model, coupled with an enhanced critical risk methodology, has successfully answered these questions when applied to a case study data set provided by South West Water (UK).

  11. A Multi-Objective Fuzzy Linear Programming Model for Cash Flow Management

    Directory of Open Access Journals (Sweden)

    A. M. El-Kholy

    2014-08-01

    Full Text Available Although significant research work has been conducted on cash flow forecast, planning, and management, the objective is constantly the maximization of profit/final cash balance, or minimization of total project cost. This paper presents a multi-objective fuzzy linear programming model (FLP for resolving the optimization problem of three conflicting objectives: final cash balance, cost of money, and initial cash balance. The proposed model depends on Jiang et al. (2011 Model. In the new formulation, both the advanced payment and delay of owner's progress payment one period were considered. Literature concerned with cash flow studies and models for construction projects was reviewed. Fuzzy linear programming applications in literature was presented and it's concept was then described. Jiang et al. (2011 Model is presented. The proposed model development was then presented. The proposed model was validated using an example project. An optimization of each individual objective was performed with a linear programming (LP software (Lindo that gave the upper and lower bounds for the multi-objective analysis. Fuzzy linear programming was then applied to optimize the solution. Four cases are considered: considering advanced payment and delay of owner's progress payment one period simultaneously, then separately, and neglecting advanced payment and delay of owner's progress payment. Penalty of delayed payment have been also considered. Analysis of the results revealed that the model is an effective decision making tool to be used by industry practitioners with reasonable accuracy.

  12. Multi-Objective Combinatorial Optimization of Trigeneration Plants Based on Metaheuristics

    Directory of Open Access Journals (Sweden)

    Mirko M. Stojiljković

    2014-12-01

    Full Text Available In this paper, a methodology for multi-objective optimization of trigeneration plants is presented. It is primarily applicable to the systems for buildings’ energy supply characterized by high load variations on daily, weekly and annual bases, as well as the components applicable for flexible operation. The idea is that this approach should enable high accuracy and flexibility in mathematical modeling, while remaining efficient enough. The optimization problem is structurally decomposed into two new problems. The main problem of synthesis and design optimization is combinatorial and solved with different metaheuristic methods. For each examined combination of the synthesis and design variables, when calculating the values of the objective functions, the inner, mixed integer linear programming operation optimization problem is solved with the branch-and-cut method. The applicability of the exploited metaheuristic methods is demonstrated. This approach is compared with the alternative, superstructure-based approach. The potential for combining them is also examined. The methodology is applied for multi-objective optimization of a trigeneration plant that could be used for the energy supply of a real residential settlement in Niš, Serbia. Here, two objectives are considered: annual total costs and primary energy consumption. Results are obtained in the form of a Pareto chart using the epsilon-constraint method.

  13. Long Series Multi-objectives Optimal Operation of Water And Sediment Regulation

    Science.gov (United States)

    Bai, T.; Jin, W.

    2015-12-01

    Secondary suspended river in Inner Mongolia reaches have formed and the security of reach and ecological health of the river are threatened. Therefore, researches on water-sediment regulation by cascade reservoirs are urgent and necessary. Under this emergency background, multi-objectives water and sediment regulation are studied in this paper. Firstly, multi-objective optimal operation models of Longyangxia and Liujiaxia cascade reservoirs are established. Secondly, based on constraints handling and feasible search space techniques, the Non-dominated Sorting Genetic Algorithm (NSGA-II) is greatly improved to solve the model. Thirdly, four different scenarios are set. It is demonstrated that: (1) scatter diagrams of perato front are obtained to show optimal solutions of power generation maximization, sediment maximization and the global equilibrium solutions between the two; (2) the potentiality of water-sediment regulation by Longyangxia and Liujiaxia cascade reservoirs are analyzed; (3) with the increasing water supply in future, conflict between water supply and water-sediment regulation occurred, and the sustainability of water and sediment regulation will confront with negative influences for decreasing transferable water in cascade reservoirs; (4) the transfer project has less benefit for water-sediment regulation. The research results have an important practical significance and application on water-sediment regulation by cascade reservoirs in the Upper Yellow River, to construct water and sediment control system in the whole Yellow River basin.

  14. Applying multi-objective genetic algorithms in green building design optimization

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Weimin; Zmeureanu, Radu [Department of Building, Civil and Environmental Engineering, Centre for Building Studies, Concordia University, Montreal (Canada); Rivard, Hugues [Department of Construction Engineering, Ecole de Technologie Superieure, Montreal (Canada)

    2005-11-01

    Since buildings have considerable impacts on the environment, it has become necessary to pay more attention to environmental performance in building design. However, it is a difficult task to find better design alternatives satisfying several conflicting criteria, especially, economical and environmental performance. This paper presents a multi-objective optimization model that could assist designers in green building design. Variables in the model include those parameters that are usually determined at the conceptual design stage and that have critical influence on building performance. Life cycle analysis methodology is employed to evaluate design alternatives for both economical and environmental criteria. Life cycle environmental impacts are evaluated in terms of expanded cumulative exergy consumption, which is the sum of exergy consumption due to resource inputs and abatement exergy required to recover the negative impacts due to waste emissions. A multi-objective genetic algorithm is employed to find optimal solutions. A case study is presented and the effectiveness of the approach is demonstrated for identifying a number of Pareto optimal solutions for green building design. (author)

  15. An Improved Artificial Bee Colony Algorithm and Its Application to Multi-Objective Optimal Power Flow

    Directory of Open Access Journals (Sweden)

    Xuanhu He

    2015-03-01

    Full Text Available Optimal power flow (OPF objective functions involve minimization of the total fuel costs of generating units, minimization of atmospheric pollutant emissions, minimization of active power losses and minimization of voltage deviations. In this paper, a fuzzy multi-objective OPF model is established by the fuzzy membership functions and the fuzzy satisfaction-maximizing method. The improved artificial bee colony (IABC algorithm is applied to solve the model. In the IABC algorithm, the mutation and crossover operations of a differential evolution algorithm are utilized to generate new solutions to improve exploitation capacity; tent chaos mapping is utilized to generate initial swarms, reference mutation solutions and the reference dimensions of crossover operations to improve swarm diversity. The proposed method is applied to multi-objective OPF problems in IEEE 30-bus, IEEE 57-bus and IEEE 300-bus test systems. The results are compared with those obtained by other algorithms, which demonstrates the effectiveness and superiority of the IABC algorithm, and how the optimal scheme obtained by the proposed model can make systems more economical and stable.

  16. An effective docking strategy for virtual screening based on multi-objective optimization algorithm

    Directory of Open Access Journals (Sweden)

    Kang Ling

    2009-02-01

    Full Text Available Abstract Background Development of a fast and accurate scoring function in virtual screening remains a hot issue in current computer-aided drug research. Different scoring functions focus on diverse aspects of ligand binding, and no single scoring can satisfy the peculiarities of each target system. Therefore, the idea of a consensus score strategy was put forward. Integrating several scoring functions, consensus score re-assesses the docked conformations using a primary scoring function. However, it is not really robust and efficient from the perspective of optimization. Furthermore, to date, the majority of available methods are still based on single objective optimization design. Results In this paper, two multi-objective optimization methods, called MOSFOM, were developed for virtual screening, which simultaneously consider both the energy score and the contact score. Results suggest that MOSFOM can effectively enhance enrichment and performance compared with a single score. For three different kinds of binding sites, MOSFOM displays an excellent ability to differentiate active compounds through energy and shape complementarity. EFMOGA performed particularly well in the top 2% of database for all three cases, whereas MOEA_Nrg and MOEA_Cnt performed better than the corresponding individual scoring functions if the appropriate type of binding site was selected. Conclusion The multi-objective optimization method was successfully applied in virtual screening with two different scoring functions that can yield reasonable binding poses and can furthermore, be ranked with the potentially compromised conformations of each compound, abandoning those conformations that can not satisfy overall objective functions.

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

    Science.gov (United States)

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

    2017-08-10

    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.

  18. Autonomous robot navigation based on the evolutionary multi-objective optimization of potential fields

    Science.gov (United States)

    Herrera Ortiz, Juan Arturo; Rodríguez-Vázquez, Katya; Padilla Castañeda, Miguel A.; Arámbula Cosío, Fernando

    2013-01-01

    This article presents the application of a new multi-objective evolutionary algorithm called RankMOEA to determine the optimal parameters of an artificial potential field for autonomous navigation of a mobile robot. Autonomous robot navigation is posed as a multi-objective optimization problem with three objectives: minimization of the distance to the goal, maximization of the distance between the robot and the nearest obstacle, and maximization of the distance travelled on each field configuration. Two decision makers were implemented using objective reduction and discrimination in performance trade-off. The performance of RankMOEA is compared with NSGA-II and SPEA2, including both decision makers. Simulation experiments using three different obstacle configurations and 10 different routes were performed using the proposed methodology. RankMOEA clearly outperformed NSGA-II and SPEA2. The robustness of this approach was evaluated with the simulation of different sensor masks and sensor noise. The scheme reported was also combined with the wavefront-propagation algorithm for global path planning.

  19. Multi Objective Optimization of Yarn Quality and Fibre Quality Using Evolutionary Algorithm

    Science.gov (United States)

    Ghosh, Anindya; Das, Subhasis; Banerjee, Debamalya

    2013-03-01

    The quality and cost of resulting yarn play a significant role to determine its end application. The challenging task of any spinner lies in producing a good quality yarn with added cost benefit. The present work does a multi-objective optimization on two objectives, viz. maximization of cotton yarn strength and minimization of raw material quality. The first objective function has been formulated based on the artificial neural network input-output relation between cotton fibre properties and yarn strength. The second objective function is formulated with the well known regression equation of spinning consistency index. It is obvious that these two objectives are conflicting in nature i.e. not a single combination of cotton fibre parameters does exist which produce maximum yarn strength and minimum cotton fibre quality simultaneously. Therefore, it has several optimal solutions from which a trade-off is needed depending upon the requirement of user. In this work, the optimal solutions are obtained with an elitist multi-objective evolutionary algorithm based on Non-dominated Sorting Genetic Algorithm II (NSGA-II). These optimum solutions may lead to the efficient exploitation of raw materials to produce better quality yarns at low costs.

  20. Optimal design of multichannel fiber Bragg grating filters using Pareto multi-objective optimization algorithm

    Science.gov (United States)

    Chen, Jing; Liu, Tundong; Jiang, Hao

    2016-01-01

    A Pareto-based multi-objective optimization approach is proposed to design multichannel FBG filters. Instead of defining a single optimal objective, the proposed method establishes the multi-objective model by taking two design objectives into account, which are minimizing the maximum index modulation and minimizing the mean dispersion error. To address this optimization problem, we develop a two-stage evolutionary computation approach integrating an elitist non-dominated sorting genetic algorithm (NSGA-II) and technique for order preference by similarity to ideal solution (TOPSIS). NSGA-II is utilized to search for the candidate solutions in terms of both objectives. The obtained results are provided as Pareto front. Subsequently, the best compromise solution is determined by the TOPSIS method from the Pareto front according to the decision maker's preference. The design results show that the proposed approach yields a remarkable reduction of the maximum index modulation and the performance of dispersion spectra of the designed filter can be optimized simultaneously.

  1. Multi-objective optimisation of wastewater treatment plant control to reduce greenhouse gas emissions.

    Science.gov (United States)

    Sweetapple, Christine; Fu, Guangtao; Butler, David

    2014-05-15

    This study investigates the potential of control strategy optimisation for the reduction of operational greenhouse gas emissions from wastewater treatment in a cost-effective manner, and demonstrates that significant improvements can be realised. A multi-objective evolutionary algorithm, NSGA-II, is used to derive sets of Pareto optimal operational and control parameter values for an activated sludge wastewater treatment plant, with objectives including minimisation of greenhouse gas emissions, operational costs and effluent pollutant concentrations, subject to legislative compliance. Different problem formulations are explored, to identify the most effective approach to emissions reduction, and the sets of optimal solutions enable identification of trade-offs between conflicting objectives. It is found that multi-objective optimisation can facilitate a significant reduction in greenhouse gas emissions without the need for plant redesign or modification of the control strategy layout, but there are trade-offs to consider: most importantly, if operational costs are not to be increased, reduction of greenhouse gas emissions is likely to incur an increase in effluent ammonia and total nitrogen concentrations. Design of control strategies for a high effluent quality and low costs alone is likely to result in an inadvertent increase in greenhouse gas emissions, so it is of key importance that effects on emissions are considered in control strategy development and optimisation.

  2. Multi-objective Optimization of Biochemical System Production Using an Improve Newton Competitive Differential Evolution Method

    Directory of Open Access Journals (Sweden)

    Mohd Arfian Ismail

    2017-09-01

    Full Text Available In this paper, an improve method of multi-objective optimization for biochemical system production is presented and discussed in detail. The optimization process of biochemical system production become hard and difficult when involved a large biochemical system that contain with many components. In addition, the multi-objective problem also need to be considered. Due to that, this study proposed and improve method that comprises with Newton method, differential evolution algorithm (DE and competitive co-evolutionary algorithm(ComCA. The aim of the proposed method is to maximize the production and simultaneously minimize the total amount of chemical concentrations involves. The operation of the proposed method starts with Newton method by dealing with biochemical system production as a nonlinear equations system. Then DE and ComCA are used to represent the variables in nonlinear equation system and tune the variables in order to find the best solution. The used of DE is to maximize the production while ComCA is to minimize the total amount of chemical concentrations involves. The effectiveness of the proposed method is evaluated using two benchmark biochemical systems and the experimental results show that the proposed method perform well compared to other works.

  3. A Cognitive Skill Classification Based on Multi Objective Optimization Using Learning Vector Quantization for Serious Games

    Directory of Open Access Journals (Sweden)

    Moh. Aries Syufagi

    2013-09-01

    Full Text Available Nowadays, serious games and game technology are poised to transform the way of educating and training students at all levels. However, pedagogical value in games do not help novice students learn, too many memorizing and reduce learning process due to no information of player’s ability. To asses the cognitive level of player ability, we propose a Cognitive Skill Game (CSG. CSG improves this cognitive concept to monitor how players interact with the game. This game employs Learning Vector Quantization (LVQ for optimizing the cognitive skill input classification of the player. CSG is using teacher’s data to obtain the neuron vector of cognitive skill pattern supervise. Three clusters multi objective XE "multi objective"  target will be classified as; trial and error, carefully and, expert cognitive skill. In the game play experiments employ 33 respondent players demonstrates that 61% of players have high trial and error, 21% have high carefully, and 18% have high expert cognitive skill. CSG may provide information to game engine when a player needs help or when wanting a formidable challenge. The game engine will provide the appropriate tasks according to players’ ability. CSG will help balance the emotions of players, so players do not get bored and frustrated. 

  4. Job-shop Scheduling with Multi-objectives Based on Genetic Algorithms

    Institute of Scientific and Technical Information of China (English)

    周亚勤; 李蓓智; 陈革

    2003-01-01

    The technology of production planning and scheduling is one of the critical technologies that decide whether the automated manufacturing systems can get the expected economy. Job shop scheduling belongs to the special class of NP-hard problems. Most of the algorithms used to optimize this class of problems have an exponential time; that is, the computation time increases exponentially with problem size. In scheduling study, makespan is often considered as the main objective. In this paper, makespan, the due date request of the key jobs, the availability of the key machine, the average wait-time of the jobs, and the similarities between the jobs and so on are taken into accotmt based on the application of mechanical engineering. The job shop scheduling problem with multi-objectives is analyzed and studied by using genetic algorithms based on the mechanics of genetics and natural selection. In this research, the tactics of the coding and decoding and the design of the genetic operators, along with the description of the mathematic model of the multi-objective functions,are presented. Finally an illu-strative example is given to testify the validity of this algorithm.

  5. FMRFamide-like immunoreactivity in the nervous system of Hydra

    DEFF Research Database (Denmark)

    Grimmelikhuijzen, C J; Dockray, G J; Schot, L P

    1982-01-01

    FMRFamide-like immunoreactivity has been localized in different parts of the hydra nervous system. Immunoreactivity occurs in nerve perikarya and processes in the ectoderm of the lower peduncle region near the basal disk, in the ectoderm of the hypostome and in the ectoderm of the tentacles...

  6. HydraPower out to make a big bang

    CERN Multimedia

    Revill, John

    2006-01-01

    "An engineering company has provided equipment for a £1.3 billion international project to recreate the conditions of the 'Big Bang". Garry Williams, technical director of hydraPower dynamics, has been asked to return to Switzerland by CERN."

  7. The Origin of Mucosal Immunity: Lessons from the Holobiont Hydra

    Directory of Open Access Journals (Sweden)

    Katja Schroder

    2016-11-01

    Full Text Available Historically, mucosal immunity—i.e., the portion of the immune system that protects an organism’s various mucous membranes from invasion by potentially pathogenic microbes—has been studied in single-cell epithelia in the gastrointestinal and upper respiratory tracts of vertebrates. Phylogenetically, mucosal surfaces appeared for the first time about 560 million years ago in members of the phylum Cnidaria. There are remarkable similarities and shared functions of mucosal immunity in vertebrates and innate immunity in cnidarians, such as Hydra species. Here, we propose a common origin for both systems and review observations that indicate that the ultimately simple holobiont Hydra provides both a new perspective on the relationship between bacteria and animal cells and a new prism for viewing the emergence and evolution of epithelial tissue-based innate immunity. In addition, recent breakthroughs in our understanding of immune responses in Hydra polyps reared under defined short-term gnotobiotic conditions open up the potential of Hydra as an animal research model for the study of common mucosal disorders.

  8. Performance of AAOmega: the AAT multi-purpose fibre-fed spectrograph

    CERN Document Server

    Sharp, R; Smith, G; Churilov, V; Correll, D; Dawson, J; Farrel, T; Frost, G; Haynes, R; Heald, R; Lankshear, A; Mayfield, D; Waller, L; Whittard, D

    2006-01-01

    AAOmega is the new spectrograph for the 2dF fibre-positioning system on the Anglo-Australian Telescope. It is a bench-mounted, double-beamed design, using volume phase holographic (VPH) gratings and articulating cameras. It is fed by 392 fibres from either of the two 2dF field plates, or by the 512 fibre SPIRAL integral field unit (IFU) at Cassegrain focus. Wavelength coverage is 370 to 950nm and spectral resolution 1,000-8,000 in multi-Object mode, or 1,500-10,000 in IFU mode. Multi-object mode was commissioned in January 2006 and the IFU system will be commissioned in June 2006. The spectrograph is located off the telescope in a thermally isolated room and the 2dF fibres have been replaced by new 38m broadband fibres. Despite the increased fibre length, we have achieved a large increase in throughput by use of VPH gratings, more efficient coatings and new detectors - amounting to a factor of at least 2 in the red. The number of spectral resolution elements and the maximum resolution are both more than doubl...

  9. Astrometry and orbits of Nix, Kerberos, AND Hydra

    Energy Technology Data Exchange (ETDEWEB)

    Buie, Marc W. [Southwest Research Institute, 1050 Walnut Street, Suite 300, Boulder, CO 80302 (United States); Grundy, William M. [Lowell Observatory, 1400 West Mars Hill Road, Flagstaff, AZ 86001 (United States); Tholen, David J., E-mail: buie@boulder.swri.edu, E-mail: grundy@lowell.edu, E-mail: tholen@ifa.hawaii.edu [Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States)

    2013-12-01

    We present new Hubble Space Telescope observations of three of Pluto's outer moons, Nix, Kerberos, and Hydra. This work revises previously published astrometry of Nix and Hydra from 2002 to 2003. New data from a four-month span during 2007 include observations designed to better measure the positions of Nix and Hydra. A third data set from 2010 also includes data on Nix and Hydra as well as some pre-discovery observations of Kerberos. The data were fitted using numerical point-spread function (PSF) fitting techniques to get accurate positions but also to remove the extended wings of the Pluto and Charon PSFs when working on these faint satellites. The resulting astrometric data were fitted with two-body Keplerian orbits that are useful for short-term predictions of the future positions of these satellites for stellar occultation and for guiding encounter planning for the upcoming New Horizons flyby of the Pluto system. The mutual inclinations of the satellites are all within 0.°2 of the plane of Charon's orbit. The periods for all continue to show that their orbits are near but distinct from integer period ratios relative to Charon. Based on our results, the period ratios are Hydra:Charon = 5.98094 ± 0.00001, Kerberos:Charon = 5.0392 ± 0.0003, and Nix:Charon = 3.89135 ± 0.00001. Based on period ratios alone, there is a trend of increased distance from an integer period ratio with decreasing distance from Charon. Our analysis shows that orbital uncertainties for Nix and Hydra are now low enough to permit useful stellar occultation predictions and for New Horizons encounter planning. In 2015 July, our orbits predict a position error of 60 km for Nix and 38 km for Hydra, well below other limiting errors that affect targeting. The orbit for Kerberos, however, still needs a lot of work as its uncertainty in 2015 is quite large at 22,000 km based on these data.

  10. Using the Multi-Object Adaptive Optics demonstrator RAVEN to observe metal-poor stars in and towards the Galactic Centre

    CERN Document Server

    Lamb, Masen; Andersen, David; Oya, Shin; Shetrone, Matthew; Fattahi, Azadeh; Howes, Louise; Asplund, Martin; Lardiere, Olivier; Akiyama, Masayuki; Ono, Yoshito; Terada, Hiroshi; Hayano, Yutaka; Suzuki, Genki; Blain, Celia; Jackson, Kathryn; Correia, Carlos; Youakim, Kris; Bradley, Colin

    2016-01-01

    The chemical abundances for five metal-poor stars in and towards the Galactic bulge have been determined from H-band infrared spectroscopy taken with the RAVEN multi-object adaptive optics science demonstrator and the IRCS spectrograph at the Subaru 8.2-m telescope. Three of these stars are in the Galactic bulge and have metallicities between -2.1 < [Fe/H] < -1.5, and high [alpha/Fe] ~+0.3, typical of Galactic disk and bulge stars in this metallicity range; [Al/Fe] and [N/Fe] are also high, whereas [C/Fe] < +0.3. An examination of their orbits suggests that two of these stars may be confined to the Galactic bulge and one is a halo trespasser, though proper motion values used to calculate orbits are quite uncertain. An additional two stars in the globular cluster M22 show [Fe/H] values consistent to within 1 sigma, although one of these two stars has [Fe/H] = -2.01 +/- 0.09, which is on the low end for this cluster. The [alpha/Fe] and [Ni/Fe] values differ by 2 sigma, with the most metal-poor star sho...

  11. Fibre assignment in next-generation wide-field spectrographs

    Science.gov (United States)

    Morales, Isaac; Montero-Dorta, Antonio D.; Azzaro, Marco; Prada, Francisco; Sánchez, Justo; Becerril, Santiago

    2012-01-01

    We present an optimized algorithm for assigning fibres to targets in next-generation fibre-fed multi-object spectrographs. The method, which we have called the draining algorithm, ensures that the maximum number of targets in a given target field is observed in the first few tiles. Using randomly distributed targets and mock galaxy catalogues, we have estimated that the gain provided by the draining algorithm, compared to a random assignment, can be as much as 2 per cent for the first tiles. For a survey such as the Baryon Oscillation Spectroscopic Survey (BigBOSS), this would imply saving for observation several hundred thousand objects or, alternatively, reducing the covered area in ˜350 deg2. An important advantage of this method is that the fibre collision problem can be solved easily and in an optimal way. We also discuss the additional optimizations of the fibre-positioning process. In particular, we show that if we allow for the rotation of the focal plane, we can improve the efficiency of the process by ˜3.5-4.5 per cent, even if only small adjustments are permitted (up to 2°). For instruments that allow large rotations of the focal plane, the expected gain increases to ˜5-6 per cent. Therefore, these results strongly support the use of focal plane rotation in future spectrographs, as far as the efficiency of the fibre-positioning process is concerned. Finally, we discuss the implications of our optimizations and provide some basic hints for an optimal survey strategy, based on the number of targets per positioner.

  12. MEGARA: a new generation optical spectrograph for GTC

    Science.gov (United States)

    Gil de Paz, A.; Gallego, J.; Carrasco, E.; Iglesias-Páramo, J.; Cedazo, R.; Vílchez, J. M.; García-Vargas, M. L.; Arrillaga, X.; Carrera, M. A.; Castillo-Morales, A.; Castillo-Domínguez, E.; Eliche-Moral, M. C.; Ferrusca, D.; González-Guardia, E.; Lefort, B.; Maldonado, M.; Marino, R. A.; Martínez-Delgado, I.; Morales Durán, I.; Mujica, E.; Páez, G.; Pascual, S.; Pérez-Calpena, A.; Sánchez-Penim, A.; Sánchez-Blanco, E.; Tulloch, S.; Velázquez, M.; Zamorano, J.; Aguerri, A. L.; Barrado y Naváscues, D.; Bertone, E.; Cardiel, N.; Cava, A.; Cenarro, J.; Chávez, M.; García, M.; Guichard, J.; Gúzman, R.; Herrero, A.; Huélamo, N.; Hughes, D.; Jiménez-Vicente, J.; Kehrig, C.; Márquez, I.; Masegosa, J.; Mayya, Y. D.; Méndez-Abreu, J.; Mollá, M.; Muñoz-Tuñón, C.; Peimbert, M.; Pérez-González, P. G.; Pérez Montero, E.; Rodríguez, M.; Rodríguez-Espinosa, J. M.; Rodríguez-Merino, L.; Rosa-González, D.; Sánchez-Almeida, J.; Sánchez Contreras, C.; Sánchez-Blázquez, P.; Sánchez Moreno, F. M.; Sánchez, S. F.; Sarajedini, A.; Serena, F.; Silich, S.; Simón-Díaz, S.; Tenorio-Tagle, G.; Terlevich, E.; Terlevich, R.; Torres-Peimbert, S.; Trujillo, I.; Tsamis, Y.; Vega, O.; Villar, V.

    2014-07-01

    MEGARA (Multi-Espectrógrafo en GTC de Alta Resolución para Astronomía) is an optical Integral-Field Unit (IFU) and Multi-Object Spectrograph (MOS) designed for the GTC 10.4m telescope in La Palma. MEGARA offers two IFU fiber bundles, one covering 12.5x11.3 arcsec2 with a spaxel size of 0.62 arcsec (Large Compact Bundle; LCB) and another one covering 8.5x6.7 arcsec2 with a spaxel size of 0.42 arcsec (Small Compact Bundle; SCB). The MEGARA MOS mode will allow observing up to 100 objects in a region of 3.5x3.5 arcmin2 around the two IFU bundles. Both the LCB IFU and MOS capabilities of MEGARA will provide intermediate-to-high spectral resolutions (RFWHM~6,000, 12,000 and 18,700, respectively for the low-, mid- and high-resolution Volume Phase Holographic gratings) in the range 3650-9700ÅÅ. These values become RFWHM~7,000, 13,500, and 21,500 when the SCB is used. A mechanism placed at the pseudo-slit position allows exchanging the three observing modes and also acts as focusing mechanism. The spectrograph is a collimator-camera system that has a total of 11 VPHs simultaneously available (out of the 18 VPHs designed and being built) that are placed in the pupil by means of a wheel and an insertion mechanism. The custom-made cryostat hosts an E2V231-84 4kx4k CCD. The UCM (Spain) leads the MEGARA Consortium that also includes INAOE (Mexico), IAA-CSIC (Spain), and UPM (Spain). MEGARA is being developed under a contract between GRANTECAN and UCM. The detailed design, construction and AIV phases are now funded and the instrument should be delivered to GTC before the end of 2016.

  13. [Multi-objectives optimization on life cycle pollutants emission of cassava-based ethanol blended gasoline fuels].

    Science.gov (United States)

    Pu, Geng-qiang; Hu, Zhi-yuan; Wang, Cheng-tao

    2004-09-01

    An optimization model on life cycle pollutants emission of cassava-based ethanol blended gasoline fuels, including single and multi-objectives, was carried out in this paper. And, the single and multi-objectives optimization of cassava-based ethanol blended gasoline fuels were done, using the life cycle CO, NOx, PM, HC, SOx, CO2 emissions as objectives. Moreover, sensitivity analysis of design variables was done. The multi-objectives results shown that the blend ratio between cassava-based ethanol and gasoline was 63%. Compare with the initial value, multi-objective optimization of cassava-based ethanol blended gasoline fuels achieved a little more life cycle CO, NOx and PM emissions, about 1%, 15% and 19% respectively, and reduced life cycle HC, SOx and CO2 emissions, 8%, 50%, and 21% respectively.

  14. Strength Pareto Evolutionary Algorithm based Multi-Objective Optimization for Shortest Path Routing Problem in Computer Networks

    Directory of Open Access Journals (Sweden)

    Subbaraj Potti

    2011-01-01

    Full Text Available Problem statement: A new multi-objective approach, Strength Pareto Evolutionary Algorithm (SPEA, is presented in this paper to solve the shortest path routing problem. The routing problem is formulated as a multi-objective mathematical programming problem which attempts to minimize both cost and delay objectives simultaneously. Approach: SPEA handles the shortest path routing problem as a true multi-objective optimization problem with competing and noncommensurable objectives. Results: SPEA combines several features of previous multi-objective evolutionary algorithms in a unique manner. SPEA stores nondominated solutions externally in another continuously-updated population and uses a hierarchical clustering algorithm to provide the decision maker with a manageable pareto-optimal set. SPEA is applied to a 20 node network as well as to large size networks ranging from 50-200 nodes. Conclusion: The results demonstrate the capabilities of the proposed approach to generate true and well distributed pareto-optimal nondominated solutions.

  15. Optimization of externalities using DTM measures: a Pareto optimal multi objective optimization using the evolutionary algorithm SPEA2+

    NARCIS (Netherlands)

    Wismans, Luc; Berkum, van Eric; Bliemer, Michiel; Allkim, T.P.; Arem, van B.

    2748-01-01

    Multi objective optimization of externalities of traffic is performed solving a network design problem in which Dynamic Traffic Management measures are used. The resulting Pareto optimal set is determined by employing the SPEA2+ evolutionary algorithm.

  16. Multi-objective based on parallel vector evaluated particle swarm optimization for optimal steady-state performance of power systems

    DEFF Research Database (Denmark)

    Vlachogiannis, Ioannis (John); Lee, K Y

    2009-01-01

    In this paper the state-of-the-art extended particle swarm optimization (PSO) methods for solving multi-objective optimization problems are represented. We emphasize in those, the co-evolution technique of the parallel vector evaluated PSO (VEPSO), analysed and applied in a multi-objective problem...... of steady-state of power systems. Specifically, reactive power control is formulated as a multi-objective optimization problem and solved using the parallel VEPSO algorithm. The results on the IEEE 30-bus test system are compared with those given by another multi-objective evolutionary technique...... demonstrating the advantage of parallel VEPSO. The parallel VEPSO is also tested on a larger power system this with 136 busses. (C) 2009 Elsevier Ltd. All rights reserved....

  17. Near Ultraviolet Spectrograph for Cubesats

    Science.gov (United States)

    Aickara Gopinathan, Sreejith; Mathew, Joice; Sarpotdar, Mayuresh; Suresh, Ambily; Kaippacheri, Nirmal; Safonova, Margarita; Murthy, Jayant

    2017-01-01

    We have designed a near ultraviolet (200 - 400 nm) spectrograph to fit into a 2U CubeSat and planned for flight in mid-2017 with a scientific goal of obtaining NUV spectra of bright sources (procurement delays and cost. Our baseline optical design consists of a collecting mirror with a 70 mm diameter which reflects light onto a concave reflection grating with a spacing of 1200 lines per mm. The grating focuses the light onto a linear array back-thinned FFT CCD with a pixel size of 14-μm × 14-μm.We will present the design of the payload and the choices forced on us by the restrictive CubeSat environment and the short lead times. This payload is a part of our program to build payloads that will address limited scientific goals but making full use of the opportunities that are arising for CubeSat class missions.

  18. A Comparative Study of Multi-Objective Optimization Algorithms for Automatic Calibration

    Science.gov (United States)

    Asadzadeh, M.; Tolson, B.; Maclean, A.

    2009-12-01

    Hydrologic model calibration is often a computationally expensive problem that aims to find a set of parameters that simulates observations. It has been shown that no single metric can comprehensively evaluate the effectiveness of the calibration. Moreover, many of the proposed metrics are conflicting (e.g., the set of parameters that achieves accurate high flow predictions is different from the set of parameters that achieves accurate low flow predictions). Conflict is even more likely when objectives are based on different fluxes and/or state variables (e.g., streamflow versus Snow Water Equivalent (SWE)). The goal of solving a multi-objective optimization problem is to approximate the tradeoff between objectives (also called the Pareto front) that represents the attained level of each metric in comparison with other metrics and hence helps to decide on the acceptable set of parameters. In this study, a variety of algorithms are applied to solve a multi-objective (MO) model calibration problem and the performance of these algorithms is compared. The calibration case study is the MESH model (a combined land surface and hydrologic model under development by Environment Canada) applied to the Reynolds Creek Experimental Watershed. MESH is calibrated against two objectives to adequately simulate the measured streamflow and SWE. The MO algorithms applied to this calibration problem include NSGAII, SPEA2 and AMALGAM. In addition, a new MO algorithm called the Pareto Archived Dynamically Dimensioned Search (PA-DDS) is also applied. PA-DDS uses DDS as a search engine and archives all the non-dominated solutions during the search. It inherits the parsimonious characteristic of DDS, so it has only one algorithm parameter which does not need tuning. This characteristic makes PA-DDS very suitable for solving multi-objective hydrologic model calibrations, since tuning the algorithm parameters in computationally intensive models is a very time consuming process. Preliminary

  19. Field Raman spectrograph for environmental analysis

    Energy Technology Data Exchange (ETDEWEB)

    Haas, J.W. III; Forney, R.W.; Carrabba, M.M. [EIC Labs, Norwood, MA (United States)] [and others

    1995-10-01

    This project entails the development of a compact raman spectrograph for field screening and monitoring of a wide variety of wastes, pollutants, and corrosion products in tanks, and environmental materials. The design of a fiber optic probe for use with the spectrograph is also discussed.

  20. Interactive Multi-objective Optimization Design for the Pylon Structure of an Airplane

    Institute of Scientific and Technical Information of China (English)

    An Weigang; Li Weiji

    2007-01-01

    The pylon structure of an airplane is very complex, and its high-fidelity analysis is quite time-consuming. If posterior preference optimization algorithm is used to solve this problem, the huge time consumption will be unacceptable in engineering practice due to the large amount of evaluation needed for the algorithm. So, a new interactive optimization algorithm-interactive multi-objective particle swarm optimization (IMOPSO) is presented. IMOPSO is efficient, simple and operable. The decision-maker can expediently determine the accurate preference in IMOPSO. IMOPSO is used to perform the pylon structure optimization design of an airplane, and a satisfactory design is achieved after only 12 generations of IMOPSO evolutions. Compared with original design, the maximum displacement of the satisfactory design is reduced, and the mass of the satisfactory design is decreased for 22%.