Title: Introduction to Stochastic Search and Optimization
Description: A unique interdisciplinary foundation for real-world problem solving   Stochastic search and optimization techniques are used in a vast number of areas, including aerospace, medicine, transportation, and finance, to name but a few. Whether the goal is refining the design of a missile or aircraft, determining the effectiveness of a new drug, developing the most efficient timing strategies for traffic signals, or making investment decisions in order to increase profits, stochastic algorithms can help researchers and practitioners devise optimal solutions to countless real-world problems.   Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control is a graduate-level introduction to the principles, algorithms, and practical aspects of stochastic optimization, including applications drawn from engineering, statistics, and computer science. The treatment is both rigorous and broadly accessible, distinguishing this text from much of the current literature and providing students, researchers, and practitioners with a strong foundation for the often-daunting task of solving real-world problems.   The text covers a broad range of today's most widely used stochastic algorithms, including:    Random search  Recursive linear estimation  Stochastic approximation  Simulated annealing  Genetic and evolutionary methods  Machine (reinforcement) learning  Model selection  Simulation-based optimization  Markov chain Monte Carlo  Optimal experimental design     The book includes over 130 examples, Web links to software and data sets, more than 250 exercises for the reader, and an extensive list of references. These features help make the text an invaluable resource for those interested in the theory or practice of stochastic search and optimization.
Subjects: Mathematical optimization, Mathematics, Nonfiction, Search theory, Stochastic processes, Processus stochastiques, Décision, Théorie de la, Optimisation mathématique, Stochastische processen, Optimaliseren