Simulation-Based Optimization
Subtitle: Parametric Optimization Techniques and Reinforcement Learning
By: by Abhijit Gosavi
Series: Operations Research/Computer Science Interfaces Series -- 25; Operations research/computer science interfaces series -- 25.
Publisher: Springer US
Published: 2003
Place of publication: Boston, MA
Language: eng
Format: [electronic resource] :
Number of pages: 554
ISBN-13: 9781441953544; 9781475737660
Subjects: Mathematics; Mathematical optimization; Operations research; Systems theory
Description: Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduces the evolving area of simulation-based optimization. The book's objective is two-fold: (1) It examines the mathematical governing principles of simulation-based optimization, thereby providing the reader with the ability to model relevant real-life problems using these techniques. (2) It outlines the computational technology underlying these methods. Taken together these two aspects demonstrate that the mathematical and computational methods discussed in this book do work. Broadly speaking, the book has two parts: (1) parametric (static) optimization and (2) control (dynamic) optimization. Some of the book's special features are: *An accessible introduction to reinforcement learning and parametric-optimization techniques. *A step-by-step description of several algorithms of simulation-based optimization. *A clear and simple introduction to the methodology of neural networks. *A gentle introduction to convergence analysis of some of the methods enumerated above. *Computer programs for many algorithms of simulation-based optimization.
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