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Computer Science - Artificial Intelligence | Stochastic Optimization

Stochastic Optimization

Schneider, Johannes, Kirkpatrick, Scott

2006, XVI, 568 p.

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The search for optimal solutions pervades our daily lives. From the scientific point of view, optimization procedures play an eminent role whenever exact solutions to a given problem are not at hand or a compromise has to be sought, e.g. to obtain a sufficiently accurate solution within a given amount of time. This book addresses stochastic optimization procedures in a broad manner, giving an overview of the most relevant optimization philosophies in the first part. The second part deals with benchmark problems in depth, by applying in sequence a selection of optimization procedures to them. While having primarily scientists and students from the physical and engineering sciences in mind, this book addresses the larger community of all those wishing to learn about stochastic optimization techniques and how to use them.

Content Level » Research

Keywords » Constraint Satisfaction - Markov - Monte Carlo - Random Numbers - Simulated Annealing - Stochastic Optimization - Tabu Search - Traveling Salesman Problem - algorithm - algorithms - construction - genetic algorithms - optimization

Related subjects » Artificial Intelligence - Computational Intelligence and Complexity - Computational Science & Engineering - Mathematics - Probability Theory and Stochastic Processes - Theoretical, Mathematical & Computational Physics

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