Ebook: Differential Evolution: A Handbook for Global Permutation-Based Combinatorial Optimization
- Tags: Appl.Mathematics/Computational Methods of Engineering, Artificial Intelligence (incl. Robotics), Applications of Mathematics
- Series: Studies in Computational Intelligence 175
- Year: 2009
- Publisher: Springer-Verlag Berlin Heidelberg
- Edition: 1
- Language: English
- pdf
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.
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.
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.
Content:
Front Matter....Pages I-XVII
Motivation for Differential Evolution for Permutative—Based Combinatorial Problems....Pages 1-11
Differential Evolution for Permutation—Based Combinatorial Problems....Pages 13-34
Forward Backward Transformation....Pages 35-80
Relative Position Indexing Approach....Pages 81-120
Smallest Position Value Approach....Pages 121-138
Discrete/Binary Approach....Pages 139-162
Discrete Set Handling....Pages 163-205
Back Matter....Pages 207-213
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.
Content:
Front Matter....Pages I-XVII
Motivation for Differential Evolution for Permutative—Based Combinatorial Problems....Pages 1-11
Differential Evolution for Permutation—Based Combinatorial Problems....Pages 13-34
Forward Backward Transformation....Pages 35-80
Relative Position Indexing Approach....Pages 81-120
Smallest Position Value Approach....Pages 121-138
Discrete/Binary Approach....Pages 139-162
Discrete Set Handling....Pages 163-205
Back Matter....Pages 207-213
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