Hybrid Evolutionary Algorithms
Crina Grosan · Ajith Abraham · Hisao Ishibuchi
Aga 2007 · Studies in Computational Intelligence Ibhuku elingu-75 · Springer
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reportIzilinganiso nezibuyekezo aziqinisekisiwe Funda Kabanzi
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Hybridization of evolutionary algorithms is getting popular due to their capabilities in handling several real world problems involving complexity, noisy environment, imprecision, uncertainty and vagueness. This edited volume is targeted to present the latest state-of-the-art methodologies in “Hybrid Evolutionary Algorithms”. This book deals with the theoretical and methodological aspects, as well as various applications to many real world problems from science, technology, business or commerce. This volume comprises of 14 chapters including an introductory chapter giving the fundamental definitions and some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.
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