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Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis > Calculus of variations

Simulation-Based Optimization - Parametric Optimization Techniques and Reinforcement Learning (Paperback, Softcover reprint of... Simulation-Based Optimization - Parametric Optimization Techniques and Reinforcement Learning (Paperback, Softcover reprint of hardcover 1st ed. 2003)
Abhijit Gosavi
R4,863 Discovery Miles 48 630 Out of stock

Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduces the evolving area of simulation-based optimization. Since it became possible to analyze random systems using computers, scientists and engineers have sought the means to optimize systems using simulation models. Only recently, however, has this objective had success in practice. Cutting-edge work in computational operations research, including non-linear programming (simultaneous perturbation), dynamic programming (reinforcement learning), and game theory (learning automata) has made it possible to use simulation in conjunction with optimization techniques. As a result, this research has given simulation added dimensions and power that it did not have in the recent past.

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. This book is written for students and researchers in the fields of engineering (electrical, industrial and computer), computer science, operations research, management science, and applied mathematics.

Student Solutions Manual for Larson/Edwards' Calculus of a Single  Variable:  Early Transcendental Functions, 2nd... Student Solutions Manual for Larson/Edwards' Calculus of a Single Variable: Early Transcendental Functions, 2nd (Paperback, 7th Revised edition)
R2,564 R2,300 Discovery Miles 23 000 Save R264 (10%) Special order

This manual contains worked-out solutions for all odd-numbered exercises in Larson/Edwards' CALCULUS OF A SINGLE VARIABLE: EARLY TRANSCENDENTAL FUNCTIONS, 7th Edition (Chapters 1-10 of CALCULUS: EARLY TRANSCENDENTAL FUNCTIONS, 7th Edition).

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