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008 141113s2015 xxu| s |||| 0|eng d
020 _a9781493913848
_9978-1-4939-1384-8
024 7 _a10.1007/978-1-4939-1384-8
_2doi
050 4 _aHD30.23
072 7 _aKJT
_2bicssc
072 7 _aKJMD
_2bicssc
072 7 _aBUS049000
_2bisacsh
082 0 4 _a658.40301
_223
100 1 _aFu, Michael C.
_eeditor.
245 1 0 _aHandbook of Simulation Optimization
_h[electronic resource] /
_cedited by Michael C Fu.
260 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2015.
300 _aXVI, 387 p. 18 illus., 9 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aInternational Series in Operations Research & Management Science,
_x0884-8289 ;
_v216
505 0 _aOverview of the Handbook -- Discrete Optimization via Simulation -- Ranking and Selection: Efficient Simulation Budget Allocation -- Response Surface Methodology -- Stochastic Gradient Estimation -- An Overview of Stochastic Approximation -- Stochastic Approximation Methods and Their Finite-time Convergence Properties -- A Guide to Sample Average Approximation -- Stochastic Constraints and Variance Reduction Techniques -- A Review of Random Search Methods -- Stochastic Adaptive Search Methods: Theory and Implementation -- Model-Based Stochastic Search Methods -- Solving Markov Decision Processes via Simulation.
520 _aThe Handbook of Simulation Optimization presents an overview of the state of the art of simulation optimization, providing a survey of the most well-established approaches for optimizing stochastic simulation models and a sampling of recent research advances in theory and methodology.  Leading contributors cover such topics as discrete optimization via simulation, ranking and selection, efficient simulation budget allocation, random search methods, response surface methodology, stochastic gradient estimation, stochastic approximation, sample average approximation, stochastic constraints, variance reduction techniques, model-based stochastic search methods, and Markov decision processes. This single volume should serve as a reference for those already in the field and as a means for those new to the field for understanding and applying the main approaches. The intended audience includes researchers, practitioners, and graduate students in the business/engineering fields of operations research, management science, operations management, and stochastic control, as well as in economics/finance and computer science.
650 0 _aEconomics.
650 0 _aComputer simulation.
650 0 _aEconomics, Mathematical.
650 0 _aOperations research.
650 1 4 _aEconomics/Management Science.
650 2 4 _aOperation Research/Decision Theory.
650 2 4 _aSimulation and Modeling.
650 2 4 _aOperations Research, Management Science.
650 2 4 _aGame Theory/Mathematical Methods.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781493913831
830 0 _aInternational Series in Operations Research & Management Science,
_x0884-8289 ;
_v216
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4939-1384-8
912 _aZDB-2-SBE
942 _2ddc
_cEBOOK
999 _c2908
_d2908