Gotowa bibliografia na temat „Global Optimization”
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Artykuły w czasopismach na temat "Global Optimization"
Sahinidis, Nikolaos V. "Global optimization". Optimization Methods and Software 24, nr 4-5 (październik 2009): 479–82. http://dx.doi.org/10.1080/10556780903135287.
Pełny tekst źródłaHartke, Bernd. "Global optimization". Wiley Interdisciplinary Reviews: Computational Molecular Science 1, nr 6 (12.05.2011): 879–87. http://dx.doi.org/10.1002/wcms.70.
Pełny tekst źródłaStephens, C. P., i W. Baritompa. "Global Optimization Requires Global Information". Journal of Optimization Theory and Applications 96, nr 3 (marzec 1998): 575–88. http://dx.doi.org/10.1023/a:1022612511618.
Pełny tekst źródłaBlack, Fischer, i Robert Litterman. "Global Portfolio Optimization". Financial Analysts Journal 48, nr 5 (wrzesień 1992): 28–43. http://dx.doi.org/10.2469/faj.v48.n5.28.
Pełny tekst źródłaSellis, Timos K. "Global query optimization". ACM SIGMOD Record 15, nr 2 (15.06.1986): 191–205. http://dx.doi.org/10.1145/16856.16874.
Pełny tekst źródłaOdili, Julius Beneoluchi, i A. Noraziah. "African Buffalo Optimization for Global Optimization". Current Science 114, nr 03 (10.02.2018): 627. http://dx.doi.org/10.18520/cs/v114/i03/627-636.
Pełny tekst źródłaNg, Chi-Kong, Duan Li i Lian-Sheng Zhang. "Global Descent Method for Global Optimization". SIAM Journal on Optimization 20, nr 6 (styczeń 2010): 3161–84. http://dx.doi.org/10.1137/090749815.
Pełny tekst źródłaBeheshti, Zahra, Siti Mariyam Shamsuddin i Sarina Sulaiman. "Fusion Global-Local-Topology Particle Swarm Optimization for Global Optimization Problems". Mathematical Problems in Engineering 2014 (2014): 1–19. http://dx.doi.org/10.1155/2014/907386.
Pełny tekst źródłaOuyang, Hai-bin, Li-qun Gao, Xiang-yong Kong, De-xuan Zou i Steven Li. "Teaching-learning based optimization with global crossover for global optimization problems". Applied Mathematics and Computation 265 (sierpień 2015): 533–56. http://dx.doi.org/10.1016/j.amc.2015.05.012.
Pełny tekst źródłaKassoul, Khelil, Nicolas Zufferey, Naoufel Cheikhrouhou i Samir Brahim Belhaouari. "Exponential Particle Swarm Optimization for Global Optimization". IEEE Access 10 (2022): 78320–44. http://dx.doi.org/10.1109/access.2022.3193396.
Pełny tekst źródłaRozprawy doktorskie na temat "Global Optimization"
Singer, Adam B. "Global dynamic optimization". Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/28662.
Pełny tekst źródłaIncludes bibliographical references (p. 247-256).
(cont.) on a set composed of the Cartesian product between the parameter bounds and the state bounds. Furthermore, I show that the solution of the differential equations is affine in the parameters. Because the feasible set is convex pointwise in time, the standard result that a convex function composed with an affine function remains convex yields the desired result that the integrand is convex under composition. Additionally, methods are developed using interval arithmetic to derive the exact state bounds for the solution of a linear dynamic system. Given a nonzero tolerance, the method is rigorously shown to converge to the global solution in a finite time. An implementation is developed, and via a collection of case studies, the technique is shown to be very efficient in computing the global solutions. For problems with embedded nonlinear dynamic systems, the analysis requires a more sophisticated composition technique attributed to McCormick. McCormick's composition technique provides a method for computing a convex underestimator for for the integrand given an arbitrary nonlinear dynamic system provided that convex underestimators and concave overestimators can be given for the states. Because the states are known only implicitly via the solution of the nonlinear differential equations, deriving these convex underestimators and concave overestimators is a highly nontrivial task. Based on standard optimization results, outer approximation, the affine solution to linear dynamic systems, and differential inequalities, I present a novel method for constructing convex underestimators and concave overestimators for arbitrary nonlinear dynamic systems ...
My thesis focuses on global optimization of nonconvex integral objective functions subject to parameter dependent ordinary differential equations. In particular, efficient, deterministic algorithms are developed for solving problems with both linear and nonlinear dynamics embedded. The techniques utilized for each problem classification are unified by an underlying composition principle transferring the nonconvexity of the embedded dynamics into the integral objective function. This composition, in conjunction with control parameterization, effectively transforms the problem into a finite dimensional optimization problem where the objective function is given implicitly via the solution of a dynamic system. A standard branch-and-bound algorithm is employed to converge to the global solution by systematically eliminating portions of the feasible space by solving an upper bounding problem and convex lower bounding problem at each node. The novel contributions of this work lie in the derivation and solution of these convex lower bounding relaxations. Separate algorithms exist for deriving convex relaxations for problems with linear dynamic systems embedded and problems with nonlinear dynamic systems embedded. However, the two techniques are unified by the method for relaxing the integral in the objective function. I show that integrating a pointwise in time convex relaxation of the original integrand yields a convex underestimator for the integral. Separate composition techniques, however, are required to derive relaxations for the integrand depending upon the nature of the embedded dynamics; each case is addressed separately. For problems with embedded linear dynamic systems, the nonconvex integrand is relaxed pointwise in time
by Adam Benjamin Singer.
Ph.D.
Ruan, Ning. "Global optimization for nonconvex optimization problems". Thesis, Curtin University, 2012. http://hdl.handle.net/20.500.11937/1936.
Pełny tekst źródłaMoore, Roxanne Adele. "Value-based global optimization". Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44750.
Pełny tekst źródłaBirbil, Sevket Ilker. "Stochastic Global Optimization Techniques". NCSU, 2002. http://www.lib.ncsu.edu/theses/available/etd-20020403-171452.
Pełny tekst źródłaIn this research, a novel population-based global optimization method has been studied. The method is called Electromagnetism-like Mechanism or in short EM. The proposed method mimicks the behavior of electrically charged particles. In other words, a set of points is sampled from the feasible region and these points imitate the role of the charged particles in basic electromagnetism. The underlying idea of the method is directing sample points toward local optimizers, which point out attractive regions of the feasible space.The proposed method has been applied to different test problems from the literature. Moreover, the viability of the method has been tested by comparing its results with other reported results from the literature. Without using the higher order information, EM has converged rapidly (in terms of the number of function evaluations) to the global optimum and produced highly efficient results for problems of varying degree of difficulty.After a systematic study of the underlying stochastic process, the proof of convergence to the global optimum has been given for the proposed method. The thrust of the proof has been to show that in the limit, at least one of the points in the population moves to the neighborhood of the global optimum with probability one.The structure of the proposed method is very flexible permitting the easy development of variations. Capitalizing on this, several variants of the proposed method has been developed and compared with the other methods from the literature. These variants of EM have been able to provide accurate answers to selected problems and in many cases have been able to outperform other well-known methods.
Gattupalli, Rajeswar R. "Advances in global optimization /". View online ; access limited to URI, 2008. http://0-digitalcommons.uri.edu.helin.uri.edu/dissertations/AAI3314454.
Pełny tekst źródłaZehnder, Nino. "Global optimization of laminated structures /". Zürich : ETH, 2008. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=17573.
Pełny tekst źródłaQuttineh, Nils-Hassan. "Algorithms for Costly Global Optimization". Licentiate thesis, Mälardalen University, School of Education, Culture and Communication, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-5970.
Pełny tekst źródłaThere exists many applications with so-called costly problems, which means that the objective function you want to maximize or minimize cannot be described using standard functions and expressions. Instead one considers these objective functions as ``black box'' where the parameter values are sent in and a function value is returned. This implies in particular that no derivative information is available.The reason for describing these problems as expensive is that it may take a long time to calculate a single function value. The black box could, for example, solve a large system of differential equations or carrying out a heavy simulation, which can take anywhere from several minutes to several hours!These very special conditions therefore requires customized algorithms. Common optimization algorithms are based on calculating function values every now and then, which usually can be done instantly. But with an expensive problem, it may take several hours to compute a single function value. Our main objective is therefore to create algorithms that exploit all available information to the limit before a new function value is calculated. Or in other words, we want to find the optimal solution using as few function evaluations as possible.A good example of real life applications comes from the automotive industry, where on the development of new engines utilize advanced models that are governed by a dozen key parameters. The goal is to optimize the model by changing the parameters in such a way that the engine becomes as energy efficient as possible, but still meets all sorts of demands on strength and external constraints.
Schonlau, Matthias. "Computer experiments and global optimization". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq22234.pdf.
Pełny tekst źródłaAl-Mharmah, Hisham. "Global optimization of stochastic functions". Diss., Georgia Institute of Technology, 1993. http://hdl.handle.net/1853/25665.
Pełny tekst źródłaOulmane, Mourad. "On-Chip global interconnect optimization". Thesis, McGill University, 2001. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=33985.
Pełny tekst źródłaAccurate moment matching techniques for computing the RC delays and transition times are used in addition to an accurate CMOS inverter/repeater delay model that takes into account short channel effects that are prevalent in deep submicron (DSM) technologies. In particular, a new delay metric, based on the first two moments of the impulse response of the interconnect RC circuit, is derived. Also, a new empirical ramp approximation that takes into account the inherent asymmetry of signals in signal distribution networks in DSM technologies is presented.
Książki na temat "Global Optimization"
Horst, Reiner, i Hoang Tuy. Global Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-662-02947-3.
Pełny tekst źródłaHorst, Reiner, i Hoang Tuy. Global Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-662-03199-5.
Pełny tekst źródłaHorst, Reiner, i Hoang Tuy. Global Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-662-02598-7.
Pełny tekst źródłaTörn, Aimo, i Antanas Žilinskas, red. Global Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/3-540-50871-6.
Pełny tekst źródłaPintér, János D., red. Global Optimization. Boston, MA: Springer US, 2006. http://dx.doi.org/10.1007/0-387-30927-6.
Pełny tekst źródłaLiberti, Leo, i Nelson Maculan, red. Global Optimization. Boston, MA: Springer US, 2006. http://dx.doi.org/10.1007/0-387-30528-9.
Pełny tekst źródłaSchäffler, Stefan. Global Optimization. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-3927-1.
Pełny tekst źródłaA, Zhilinskas, red. Global optimization. Berlin: Springer-Verlag, 1989.
Znajdź pełny tekst źródłaFloudas, Christodoulos A. Deterministic Global Optimization. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4757-4949-6.
Pełny tekst źródłaChew, Soo Hong, i Quan Zheng. Integral Global Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-46623-6.
Pełny tekst źródłaCzęści książek na temat "Global Optimization"
Tuy, Hoang, Steffen Rebennack i Panos M. Pardalos. "Global Optimization". W Encyclopedia of Operations Research and Management Science, 650–58. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-1-4419-1153-7_1142.
Pełny tekst źródłaKulisch, Ulrich, Rolf Hammer, Matthias Hocks i Dietmar Ratz. "Global Optimization". W C++ Toolbox for Verified Computing I, 312–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-79651-7_14.
Pełny tekst źródłaKulisch, Ulrich, Rolf Hammer, Matthias Hocks i Dietmar Ratz. "Global Optimization". W C++ Toolbox for Verified Computing I, 113–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-79651-7_7.
Pełny tekst źródłaForst, Wilhelm, i Dieter Hoffmann. "Global Optimization". W Optimization—Theory and Practice, 341–63. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-0-387-78977-4_8.
Pełny tekst źródłaHeitzinger, Clemens. "Global Optimization". W Algorithms with JULIA, 307–28. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-16560-3_11.
Pełny tekst źródłaKulisch, Ulrich, Rolf Hammer, Dietmar Ratz i Matthias Hocks. "Global Optimization". W Springer Series in Computational Mathematics, 282–311. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78423-1_14.
Pełny tekst źródłaKulisch, Ulrich, Rolf Hammer, Dietmar Ratz i Matthias Hocks. "Global Optimization". W Springer Series in Computational Mathematics, 105–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78423-1_7.
Pełny tekst źródłaSchäffler, Stefan. "Unconstrained Global Optimization". W Global Optimization, 21–55. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-3927-1_3.
Pełny tekst źródłaSchäffler, Stefan. "Constrained Global Optimization". W Global Optimization, 75–103. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-3927-1_5.
Pełny tekst źródłaSchäffler, Stefan. "Vector Optimization". W Global Optimization, 105–17. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-3927-1_6.
Pełny tekst źródłaStreszczenia konferencji na temat "Global Optimization"
Sellis, Timos K. "Global query optimization". W the 1986 ACM SIGMOD international conference. New York, New York, USA: ACM Press, 1986. http://dx.doi.org/10.1145/16894.16874.
Pełny tekst źródłaNAN, Marin Silviu. "EXACT GLOBAL OPTIMIZATION". W 17th International Multidisciplinary Scientific GeoConference SGEM2017. Stef92 Technology, 2017. http://dx.doi.org/10.5593/sgem2017/21/s07.039.
Pełny tekst źródłaDaboul, Siad, Stephan Held, Bento Natura i Daniel Rotter. "Global Interconnect Optimization". W 2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD). IEEE, 2019. http://dx.doi.org/10.1109/iccad45719.2019.8942155.
Pełny tekst źródłaBánhelyi, Balázs, Tibor Csendes, Balázs Lévai, Dániel Zombori i László Pál. "Improved versions of the GLOBAL optimization algorithm and the globalJ modularized toolbox". W PROCEEDINGS LEGO – 14TH INTERNATIONAL GLOBAL OPTIMIZATION WORKSHOP. Author(s), 2019. http://dx.doi.org/10.1063/1.5089989.
Pełny tekst źródłaCalvin, James M., Craig J. Gotsman i Cuicui Zheng. "Global optimization for image registration". W PROCEEDINGS LEGO – 14TH INTERNATIONAL GLOBAL OPTIMIZATION WORKSHOP. Author(s), 2019. http://dx.doi.org/10.1063/1.5089975.
Pełny tekst źródłaKosolap, Anatolii. "Quadratic regularization for global optimization". W PROCEEDINGS LEGO – 14TH INTERNATIONAL GLOBAL OPTIMIZATION WORKSHOP. Author(s), 2019. http://dx.doi.org/10.1063/1.5090001.
Pełny tekst źródłaBOGDAN, Constantin. "NUMERICAL NONLINEAR GLOBAL OPTIMIZATION". W 17th International Multidisciplinary Scientific GeoConference SGEM2017. Stef92 Technology, 2017. http://dx.doi.org/10.5593/sgem2017/21/s07.061.
Pełny tekst źródłaBilbro, Griff L. "Fast stochastic global optimization". W SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, redaktor Su-Shing Chen. SPIE, 1993. http://dx.doi.org/10.1117/12.162050.
Pełny tekst źródłaRogers, John. "Global optimization and desensitization". W SPIE Optifab, redaktorzy Julie L. Bentley i Sebastian Stoebenau. SPIE, 2015. http://dx.doi.org/10.1117/12.2196010.
Pełny tekst źródłaJagadish, H. V., Hui Jin, Beng Chin Ooi i Kian-Lee Tan. "Global optimization of histograms". W the 2001 ACM SIGMOD international conference. New York, New York, USA: ACM Press, 2001. http://dx.doi.org/10.1145/375663.375687.
Pełny tekst źródłaRaporty organizacyjne na temat "Global Optimization"
Dunlavy, Daniel M., i Dianne P. O'Leary. Homotopy optimization methods for global optimization. Office of Scientific and Technical Information (OSTI), grudzień 2005. http://dx.doi.org/10.2172/876373.
Pełny tekst źródłaHaftka, Raphael T. Theory and Algorithms for Global/Local Design Optimization. Fort Belvoir, VA: Defense Technical Information Center, grudzień 2004. http://dx.doi.org/10.21236/ada437353.
Pełny tekst źródłaMalony, Allen D., i Sameer S. Shende. MOGO: Model-Oriented Global Optimization of Petascale Applications. Office of Scientific and Technical Information (OSTI), wrzesień 2012. http://dx.doi.org/10.2172/1096588.
Pełny tekst źródłaEskow, Elizabeth, i Robert B. Schnabel. Mathematical Modeling of a Parallel Global Optimization Algorithm. Fort Belvoir, VA: Defense Technical Information Center, kwiecień 1988. http://dx.doi.org/10.21236/ada446514.
Pełny tekst źródłaGlover, Fred. Probabilistic Methods for Global Optimization in Continuous Variables. Fort Belvoir, VA: Defense Technical Information Center, listopad 1995. http://dx.doi.org/10.21236/ada304297.
Pełny tekst źródłaGlover, Fred. Probabilistic Methods or Global Optimization in Continuous Variables. Fort Belvoir, VA: Defense Technical Information Center, listopad 1995. http://dx.doi.org/10.21236/ada311405.
Pełny tekst źródłaMarcus, Steven I., Michael C. Fu i Jiaqiao Hu. Simulation-Based Methodologies for Global Optimization and Planning. Fort Belvoir, VA: Defense Technical Information Center, październik 2013. http://dx.doi.org/10.21236/ada591505.
Pełny tekst źródłaOblow, E. M. STP: A Stochastic Tunneling Algorithm for Global Optimization. Office of Scientific and Technical Information (OSTI), maj 1999. http://dx.doi.org/10.2172/814395.
Pełny tekst źródłaHART, WILLIAM E. LDRD Final Report: Global Optimization for Engineering Science Problems. Office of Scientific and Technical Information (OSTI), grudzień 1999. http://dx.doi.org/10.2172/15153.
Pełny tekst źródłaAnderson, P. B., D. W. Norton i M. A. Young. CM-5 Kernel Optimization of a Global Weather Model. Fort Belvoir, VA: Defense Technical Information Center, lipiec 1995. http://dx.doi.org/10.21236/ada295796.
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