Hybrid metaheuristics: an emerging approach to optimization

By:

Blum, Christian

Material type: Text

TextSeries: Studies in computational intelligence, 1860-949X ; v. 114Publication details: 2008 Springer-Verlag Berlin HeidelbergDescription: viii, 289 pISBN:

9783540782940

Subject(s):

DDC classification:

511.6 B5H9

Summary: Optimization problems are of great importance in many fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. Examples of metaheuristics are simulated annealing, tabu search, evolutionary computation, iterated local search, variable neighborhood search, and ant colony optimization. In recent years it has become evident that a skilled combination of a metaheuristic with other optimization techniques, a so called hybrid metaheuristic, can provide a more efficient behavior and a higher flexibility. This is because hybrid metaheuristics combine their advantages with the complementary strengths of, for example, more classical optimization techniques such as branch and bound or dynamic programming. (http://www.springer.com/engineering/computational+intelligence+and+complexity/book/978-3-540-78294-0)

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Item type	Current library	Call number	Status	Date due	Barcode	Item holds
Book	Ahmedabad	511.6 B5H9 (Browse shelf(Opens below))	Available		174608

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Optimization problems are of great importance in many fields. They can be tackled, for example, by approximate algorithms such as metaheuristics. Examples of metaheuristics are simulated annealing, tabu search, evolutionary computation, iterated local search, variable neighborhood search, and ant colony optimization. In recent years it has become evident that a skilled combination of a metaheuristic with other optimization techniques, a so called hybrid metaheuristic, can provide a more efficient behavior and a higher flexibility. This is because hybrid metaheuristics combine their advantages with the complementary strengths of, for example, more classical optimization techniques such as branch and bound or dynamic programming. (http://www.springer.com/engineering/computational+intelligence+and+complexity/book/978-3-540-78294-0)

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