Differential Evolution A Handbook for Global Permutation Based Combinatorial Optimization

This book PDF is perfect for those who love Computers genre, written by Godfrey C. Onwubolu and published by Springer Science & Business Media which was released on 13 January 2009 with total hardcover pages 226. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Differential Evolution A Handbook for Global Permutation Based Combinatorial Optimization books below.

Differential Evolution  A Handbook for Global Permutation Based Combinatorial Optimization
Author : Godfrey C. Onwubolu
File Size : 46,7 Mb
Publisher : Springer Science & Business Media
Language : English
Release Date : 13 January 2009
ISBN : 9783540921509
Pages : 226 pages
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Differential Evolution A Handbook for Global Permutation Based Combinatorial Optimization by Godfrey C. Onwubolu Book PDF Summary

This is the first book devoted entirely to Differential Evolution (DE) for global permutative-based combinatorial optimization. Since its original development, DE has mainly been applied to solving problems characterized by continuous parameters. This means that only a subset of real-world problems could be solved by the original, classical DE algorithm. This book presents in detail the various permutative-based combinatorial DE formulations by their initiators in an easy-to-follow manner, through extensive illustrations and computer code. It is a valuable resource for professionals and students interested in DE in order to have full potentials of DE at their disposal as a proven optimizer. All source programs in C and Mathematica programming languages are downloadable from the website of Springer.

Differential Evolution  A Handbook for Global Permutation Based Combinatorial Optimization

This is the first book devoted entirely to Differential Evolution (DE) for global permutative-based combinatorial optimization. Since its original development, DE has mainly been applied to solving problems characterized by continuous parameters. This means that only a subset of real-world problems could be solved by the original, classical DE algorithm.

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