Author	Gosavi, Abhijit. author
Title	Simulation-Based Optimization [electronic resource] : Parametric Optimization Techniques and Reinforcement Learning / by Abhijit Gosavi
Imprint	Boston, MA : Springer US : Imprint: Springer, 2003
Connect to	http://dx.doi.org/10.1007/978-1-4757-3766-0
Descript	XXVII, 554 p. online resource

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

1. Background -- 2. Notation -- 3. Probability Theory: A Refresher -- 4. Basic Concepts Underlying Simulation -- 5. Simulation Optimization: An Overview -- 6. Response Surfaces and Neural Nets -- 7. Parametric Optimization -- 8. Dynamic Programming -- 9. Reinforcement Learning -- 10. Markov Chain Automata Theory -- 11. Convergence: Background Material -- 12. Convergence: Parametric Optimization -- 13. Convergence: Control Optimization -- 14. Case Studies -- 15. Codes -- 16. Concluding Remarks -- References

1. Mathematics
2. Operations research
3. Decision making
4. System theory
5. Mathematical optimization
6. Calculus of variations
7. Mathematics
8. Systems Theory
9. Control
10. Calculus of Variations and Optimal Control; Optimization
11. Operation Research/Decision Theory
12. Optimization