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An Introduction to Metaheuristics for Optimization

Gebonden Engels 2026 2e druk 9789819562152
€ 78,99
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Samenvatting

This book proposes an introduction to metaheuristics, combining a theoretical understanding with the practical skill to use and develop these methods. Optimization is central to most domains of science, whether academic or industrial. The solution to many real life problems rely on our ability to find the maximum or minimum of some quantity of interest. However, many of these problems are referred to as “hard optimization” problems, meaning that they quickly become numerically intractable and cannot be solved by traditional optimization techniques. Metaheuristics are methods, inspired by physical processes, Darwinian evolution, animal behaviors, and other phenomena observed in Nature, which usually find optimal values of satisfactory quality within acceptable computing resources. As such, they are an essential tool for the optimization community.

This textbook is suitable for advanced undergraduates in computer science and engineering, as well as for students and researchers from other disciplines looking for a concise and clear introduction to metaheuristic methods for optimization.

Specificaties

ISBN13:9789819562152
Taal:Engels
Bindwijze:Gebonden
Aantal pagina's:302
Uitgever:Springer International Publishing
Druk:2

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Inhoudsopgave

Problems, Algorithms, and Computational Complexity.- Search Space.- Statistical Features and Metrics of Search Spaces.- Tabu Search.- Simulated Annealing.- The Ant Colony Method.- Particle Swarm Optimization.- Fireflies, Cuckoos, and Lévy Flights.- Evolutionary Algorithms: Foundations.- Evolutionary Algorithms: structured populations.- Real Function Optimization: Evolution Strategies and Differential Evolution.- Genetic Programming.- Performance and Limitations of Metaheuristics.- Phase Transitions in Combinatorial Optimization Problems.- Adiabatic Quantum Computing and Quantum Annealing.

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€ 78,99
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          An Introduction to Metaheuristics for Optimization