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Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning (Operations Research/Computer Science Interfaces Series) - Softcover

Gosavi, Abhijit

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9781441953544: Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning (Operations Research/Computer Science Interfaces Series)

Synopsis

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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About the Author

Dr. Abhijit Gosavi has a Ph.D. in Industrial Engineering and an MS and a BS in Mechanical Engineering.  He currently teaches in the Department of Engineering Management and Systems Engineering in Missouri University of Science and Technology (formerly University of Missouri-Rolla).  He is a member of INFORMS, IIE, POMS, IEEE, and ASEE.  He has written numerous research articles on simulation-based optimization and Markov decision processes.

"About this title" may belong to another edition of this title.