Handbook of simulation optimization [electronic resource]

• 其他作者：
  • Fu, Michael C.
  • SpringerLink (Online service)
• 其他題名：
  • International series in operations research & management science
• 出版： New York, NY : Springer New York :Imprint: Springer
• 叢書名： International series in operations research & management sciencev.216
• 主題： Simulation methods , Mathematical optimization , Stochastic processes , Operations research , Economics/Management Science. , Operation Research/Decision Theory. , Simulation and Modeling. , Operations Research, Management Science. , Game Theory/Mathematical Methods.
• ISBN： 9781493913848 (electronic bk.) 、 9781493913831 (paper)
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: Overview 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.
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• 摘要註: The 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.
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