Academic literature on the topic 'Global function optimization'
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Journal articles on the topic "Global function optimization"
Liu, Y., and K. L. Teo. "A bridging method for global optimization." Journal of the Australian Mathematical Society. Series B. Applied Mathematics 41, no. 1 (July 1999): 41–57. http://dx.doi.org/10.1017/s0334270000011024.
Full textZhu, Jinghao, Jiani Zhou, and David Gao. "Global optimization by canonical dual function." Journal of Computational and Applied Mathematics 234, no. 2 (May 2010): 538–44. http://dx.doi.org/10.1016/j.cam.2009.12.045.
Full textNorkin, Vladimir. "A Stochastic Smoothing Method for Nonsmooth Global Optimization." Cybernetics and Computer Technologies, no. 1 (March 31, 2020): 5–14. http://dx.doi.org/10.34229/2707-451x.20.1.1.
Full textSatapathy, Suresh Chandra. "Improved teaching learning based optimization for global function optimization." Decision Science Letters 2, no. 1 (January 1, 2013): 23–34. http://dx.doi.org/10.5267/j.dsl.2012.10.005.
Full textSatapathy, Suresh Chandra, Anima Naik, and K. Parvathi. "Weighted Teaching-Learning-Based Optimization for Global Function Optimization." Applied Mathematics 04, no. 03 (2013): 429–39. http://dx.doi.org/10.4236/am.2013.43064.
Full textWang, Wei, Xiaoshan Zhang, and Min Li. "A Filled Function Method Dominated by Filter for Nonlinearly Global Optimization." Journal of Applied Mathematics 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/245427.
Full textDJALIL, BOUDJEHEM, BOUDJEHEM BADREDDINE, and BOUKAACHE ABDENOUR. "REDUCING DIMENSION IN GLOBAL OPTIMIZATION." International Journal of Computational Methods 08, no. 03 (September 2011): 535–44. http://dx.doi.org/10.1142/s0219876211002460.
Full textXiao, Jin-ke, Wei-min Li, Wei Li, and Xin-rong Xiao. "Optimization on Black Box Function Optimization Problem." Mathematical Problems in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/647234.
Full textMou-Yan Zou and Xi Zou. "Global optimization: an auxiliary cost function approach." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 30, no. 3 (May 2000): 347–54. http://dx.doi.org/10.1109/3468.844358.
Full textHan, Qiaoming, and Jiye Han. "Revised filled function methods for global optimization." Applied Mathematics and Computation 119, no. 2-3 (April 2001): 217–28. http://dx.doi.org/10.1016/s0096-3003(99)00266-0.
Full textDissertations / Theses on the topic "Global function optimization"
Gutmann, H. M. "Radial basis function methods for global optimization." Thesis, University of Cambridge, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.599804.
Full textBastani, Spencer, and Olov Andersson. "Stochastic Optimization in Dynamic Environments : with applications in e-commerce." Thesis, Linköping University, Department of Mathematics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8509.
Full textIn this thesis we address the problem of how to construct an optimal algorithm for displaying banners (i.e advertisements shown on web sites). The optimization is based on the revenue each banner generates, with the aim of selecting those banners which maximize future total revenue. Banner optimality is of major importance in the e-commerce industry, in particular on web sites with heavy traffic. The 'micropayments' from showing banners add up to substantial profits due to the large volumes involved. We provide a broad, up-to-date and primarily theoretical treatment of this global optimization problem. Through a synthesis of mathematical modeling, statistical methodology and computer science we construct a stochastic 'planning algorithm'. The superiority of our algorithm is based on empirical analysis conducted by us on real internet-data at TradeDoubler AB, as well as test-results on a selection of stylized data-sets. The algorithm is flexible and adapts well to new environments.
Hatton, Marc. "Requirements specification for the optimisation function of an electric utility's energy flow simulator." Thesis, Stellenbosch : Stellenbosch University, 2015. http://hdl.handle.net/10019.1/96956.
Full textENGLISH ABSTRACT: Efficient and reliable energy generation capability is vital to any country's economic growth. Many strategic, tactical and operational decisions take place along the energy supply chain. Shortcomings in South Africa's electricity production industry have led to the development of an energy ow simulator. The energy ow simulator is claimed to incorporate all significant factors involved in the energy ow process from primary energy to end-use consumption. The energy ow simulator thus provides a decision support system for electric utility planners. The original aim of this study was to develop a global optimisation model and integrate it into the existing energy ow simulator. After gaining an understanding of the architecture of the energy ow simulator and scrutinising a large number of variables, it was concluded that global optimisation was infeasible. The energy ow simulator is made up of four modules and is operated on a module-by-module basis, with inputs and outputs owing between modules. One of the modules, namely the primary energy module, lends itself well to optimisation. The primary energy module simulates coal stockpile levels through Monte Carlo simulation. Classic inventory management policies were adapted to fit the structure of the primary energy module, which is treated as a black box. The coal stockpile management policies that are introduced provide a prescriptive means to deal with the stochastic nature of the coal stockpiles. As the planning horizon continuously changes and the entire energy ow simulator has to be re-run, an efficient algorithm is required to optimise stockpile management policies. Optimisation is achieved through the rapidly converging cross-entropy method. By integrating the simulation and optimisation model, a prescriptive capability is added to the primary energy module. Furthermore, this study shows that coal stockpile management policies can be improved. An integrated solution is developed by nesting the primary energy module within the optimisation model. Scalability is incorporated into the optimisation model through a coding approach that automatically adjusts to an everchanging planning horizon as well as the commission and decommission of power stations. As this study is the first of several research projects to come, it paves the way for future research on the energy ow simulator by proposing future areas of investigation.
AFRIKAANSE OPSOMMING: Effektiewe en betroubare energie-opwekkingsvermoë is van kardinale belang in enige land se ekonomiese groei. Baie strategiese, taktiese en operasionele besluite word deurgaans in die energie-verskaffingsketting geneem. Tekortkominge in Suid-Afrika se elektrisiteitsopwekkingsindustrie het tot die ontwikkeling van 'n energie-vloei-simuleerder gelei. Die energie-vloei-simuleerder vervat na bewering al die belangrike faktore wat op die energie-vloei-proses betrekking het van primêre energieverbruik tot eindgebruik. Die energie-vloei-simuleerder verskaf dus 'n ondersteuningstelsel aan elektrisiteitsdiensbeplanners vir die neem van besluite. Die oorspronklike doel van hierdie studie was om 'n globale optimeringsmodel te ontwikkel en te integreer in die bestaande energie-vloeisimuleerder. Na 'n begrip aangaande die argitektuur van die energievloei- simuleerder gevorm is en 'n groot aantal veranderlikes ondersoek is, is die slotsom bereik dat globale optimering nie lewensvatbaar is nie. Die energie-vloei-simuleerder bestaan uit vier eenhede en werk op 'n eenheid-tot-eenheid basis met insette en uitsette wat tussen eenhede vloei. Een van die eenhede, naamlik die primêre energiemodel, leen dit goed tot optimering. Die primêre energiemodel boots steenkoolreserwevlakke deur Monte Carlo-simulering na. Tradisionele voorraadbestuursbeleide is aangepas om die primêre energiemodel se struktuur wat as 'n swartboks hanteer word, te pas. Die steenkoolreserwebestuursbeleide wat ingestel is, verskaf 'n voorgeskrewe middel om met die stogastiese aard van die steenkoolreserwes te werk. Aangesien die beplanningshorison deurgaans verander en die hele energie-vloei-simulering weer met die energie-vloei-simuleerder uitgevoer moet word, word 'n effektiewe algoritme benodig om die re-serwebestuursbeleide te optimeer. Optimering word bereik deur die vinnige konvergerende kruis-entropie-metode. 'n Geïntegreerde oplossing is ontwikkel deur die primêre energiemodel en die optimering funksie saam te voeg. Skalering word ingesluit in die optimeringsmodel deur 'n koderingsbenadering wat outomaties aanpas tot 'n altyd-veranderende beplanningshorison asook die ingebruikneem en uitgebruikstel van kragstasies. Aangesien hierdie studie die eerste van verskeie navorsingsprojekte is, baan dit die weg vir toekomstige navorsing oor die energie-vloeisimuleerder deur ondersoekareas vir die toekoms voor te stel.
Al-Mharmah, Hisham. "Global optimization of stochastic functions." Diss., Georgia Institute of Technology, 1993. http://hdl.handle.net/1853/25665.
Full textSharikov, Evgenii. "Conditions for global minimum through abstract convexity." Thesis, University of Ballarat, 2008. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/45930.
Full textDoctor of Philosophy
Andramonov, Mikhail. "Global minimization of some classes of generalized convex functions." Thesis, Federation University Australia, 2001. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/164850.
Full textFowkes, Jaroslav Mrazek. "Bayesian numerical analysis : global optimization and other applications." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:ab268fe7-f757-459e-b1fe-a4a9083c1cba.
Full textSelassie, Abebe Geletu W. "A coarse solution of generalized semi-infinite optimization problems via robust analysis of marginal functions and global optimization." [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=974862304.
Full textSultanova, Nargiz. "A class of Increasing Positively Homogeneous functions for which global optimization problem is NP-hard." Thesis, University of Ballarat, 2009. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/44036.
Full textMaster of Mathematical Sciences (Research)
Sultanova, Nargiz. "A class of Increasing Positively Homogeneous functions for which global optimization problem is NP-hard." University of Ballarat, 2009. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/16160.
Full textMaster of Mathematical Sciences (Research)
Books on the topic "Global function optimization"
Hoang, Tuy. Convex analysis and global optimization. Dordrecht: Kluwer Academic Publishers, 1998.
Find full text1873-1950, Carathéodory Constantin, Hadjisavvas Nicolas 1953-, and Pardalos P. M. 1954-, eds. Advances in convex analysis and global optimization: Honoring the memory of C. Caratheodory (1873-1950). Dordrecht: Kluwer Academic Publishers, 2001.
Find full textDontchev, A. L. Implicit functions and solution mappings: A view from variational analysis. Dordrecht: Springer, 2009.
Find full textVirginia, Torczon, and Langley Research Center, eds. A globally convergent augmented Lagrangian pattern search algorithm for optimization with general constraints and simple bounds. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.
Find full textVirginia, Torczon, and Langley Research Center, eds. A globally convergent augmented Lagrangian pattern search algorithm for optimization with general constraints and simple bounds. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.
Find full textPenot, Jean-Paul. Calculus Without Derivatives. New York, NY: Springer New York, 2013.
Find full textBoţ, Radu Ioan. Conjugate Duality in Convex Optimization. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.
Find full textScholtes, Stefan. Introduction to Piecewise Differentiable Equations. New York, NY: Springer New York, 2012.
Find full textÇınlar, E. Real and Convex Analysis. Boston, MA: Springer US, 2013.
Find full textDrábek, Pavel. Methods of Nonlinear Analysis: Applications to Differential Equations. 2nd ed. Basel: Springer Basel, 2013.
Find full textBook chapters on the topic "Global function optimization"
Khamisov, Oleg V. "Objective Function Decomposition in Global Optimization." In Lecture Notes in Computer Science, 338–44. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69404-7_28.
Full textVerma, Anand, Shikha Agrawal, Jitendra Agrawal, and Sanjeev Sharma. "Advance Teaching–Learning Based Optimization for Global Function Optimization." In Proceedings of 3rd International Conference on Advanced Computing, Networking and Informatics, 573–80. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2538-6_59.
Full textShang, You-Lin, Zhen-Yang Sun, and Xiang-Yi Jiang. "Modified Filled Function Method for Global Discrete Optimization." In Springer Proceedings in Mathematics & Statistics, 57–68. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08377-3_7.
Full textLocatelli, Marco. "Function Landscapes and the Difficulty of Global Optimization." In Computational Intelligence in Aerospace Sciences, 47–62. Reston, VA: American Institute of Aeronautics and Astronautics, Inc., 2014. http://dx.doi.org/10.2514/5.9781624102714.0047.0062.
Full textGergel, Victor, and Alexander Sysoyev. "Global Optimization Method with Numerically Calculated Function Derivatives." In Communications in Computer and Information Science, 3–14. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65739-0_1.
Full textLi, Sun, and Wang Yuncheng. "A Modified Cut-Peak Function Method for Global Optimization." In Springer Proceedings in Mathematics & Statistics, 51–56. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08377-3_6.
Full textZheng, Fangying, and Liansheng Zhang. "Constrained Global Optimization Using a New Exact Penalty Function." In Springer Proceedings in Mathematics & Statistics, 69–76. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08377-3_8.
Full textZiyi, Chen, and Kang Lishan. "Population Climbing Evolutionary Algorithm for Multimodal Function Global Optimization." In Lecture Notes in Computer Science, 553–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11903697_70.
Full textChen, Ziyi, and Lishan Kang. "Steady-State Evolutionary Algorithm for Multimodal Function Global Optimization." In Computational Intelligence and Security, 200–207. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11596448_29.
Full textZhu, Wenxing. "A Dynamic Convexized Function with the Same Global Minimizers for Global Optimization." In Lecture Notes in Computer Science, 939–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11881070_124.
Full textConference papers on the topic "Global function optimization"
Isshiki, Masaki. "Global optimization with escape function." In International Optical Design Conference, edited by Leo R. Gardner and Kevin P. Thompson. SPIE, 1998. http://dx.doi.org/10.1117/12.321984.
Full textIsshiki, Masaki. "Global optimization with escape function." In International Optical Design Conference. Washington, D.C.: Optica Publishing Group, 1998. http://dx.doi.org/10.1364/iodc.1998.lmc.1.
Full textChen, Zhong, Cai-Yun Liu, and Yi-Bing Lv. "Global Minimum of Measure Function and Quasi-convex Function." In 2010 Third International Joint Conference on Computational Science and Optimization. IEEE, 2010. http://dx.doi.org/10.1109/cso.2010.47.
Full textHuang, Zhiyong, Youlin Shang, and Fengye Wang. "Transformation Function Method for Unconstrained Global Optimization." In 2012 Fifth International Joint Conference on Computational Sciences and Optimization (CSO). IEEE, 2012. http://dx.doi.org/10.1109/cso.2012.75.
Full textYanxia, Niu, and Zhao Hengjun. "Generalized Filled Function for Global Continuous Optimization Problems." In 2012 Fifth International Joint Conference on Computational Sciences and Optimization (CSO). IEEE, 2012. http://dx.doi.org/10.1109/cso.2012.87.
Full textKou, Jiaxun, Teng Long, Zhu Wang, Yonglu Wen, and Li Liu. "A Deterministic Constrained Global Optimization Algorithm Without Penalty Function." In 17th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2016. http://dx.doi.org/10.2514/6.2016-4296.
Full textHendrix, E. M. T., J. M. G. Salmerón, and L. G. Casado. "On function monotonicity in simplicial branch and bound." In PROCEEDINGS LEGO – 14TH INTERNATIONAL GLOBAL OPTIMIZATION WORKSHOP. Author(s), 2019. http://dx.doi.org/10.1063/1.5089974.
Full textSakalauskas, Leonidas, and Jurgis Susinskas. "On bayes approach to univariate global optimization." In International Workshop of "Stochastic Programming for Implementation and Advanced Applications". The Association of Lithuanian Serials, 2012. http://dx.doi.org/10.5200/stoprog.2012.18.
Full textYang, Yongjian, and Yuelin Gao. "A new filled function method for global optimization." In 2015 IEEE International Conference on Digital Signal Processing (DSP). IEEE, 2015. http://dx.doi.org/10.1109/icdsp.2015.7251329.
Full textZhang, L. S. "Advances in Global Optimization: Novel Function Transformation Approaches." In APCCAS 2006 - 2006 IEEE Asia Pacific Conference on Circuits and Systems. IEEE, 2006. http://dx.doi.org/10.1109/apccas.2006.342064.
Full textReports on the topic "Global function optimization"
AL-Khayyal, Fais A., Reiner Horst, and Panos M. Pardalos. Global Optimization of Concave Functions Subject to Separable Quadratic Constraints and of All-Quadratic Separable Problems. Fort Belvoir, VA: Defense Technical Information Center, April 1988. http://dx.doi.org/10.21236/ada197747.
Full textMcElwain, Terry, Eugene Pipano, Guy Palmer, Varda Shkap, Stephen Hines, and Douglas Jasmer. Protection of Cattle Against Babesiosis: Immunization with Recombinant DNA Derived Apical Complex Antigens of Babesia bovis. United States Department of Agriculture, June 1995. http://dx.doi.org/10.32747/1995.7612835.bard.
Full textRémy, Elisabeth, Romain Escudier, and Alexandre Mignot. Access impact of observations. EuroSea, 2023. http://dx.doi.org/10.3289/eurosea_d4.8.
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