Advances of Evolutionary Computation: Methods and Operators
Erik Cuevas
Sold by buchversandmimpf2000, Emtmannsberg, BAYE, Germany
AbeBooks Seller since January 23, 2017
New - Hardcover
Condition: New
Quantity: 2 available
Add to basketSold by buchversandmimpf2000, Emtmannsberg, BAYE, Germany
AbeBooks Seller since January 23, 2017
Condition: New
Quantity: 2 available
Add to basketNeuware -The goal of this book is topresent advances that discuss alternative Evolutionary Computation (EC) developmentsand non-conventional operators which have proved to be e¿ective in the solutionof several complex problems. The book has been structured so that each chaptercan be read independently from the others. The book contains nine chapters withthe following themes: 1) Introduction, 2) the Social Spider Optimization (SSO)3) the States of Matter Search (SMS), 4) the collective animal behavior (CAB)algorithm, 5) the Allostatic Optimization (AO) method, 6) the Locust Search(LS) algorithm, 7) the Adaptive Population with Reduced Evaluations (APRE)method, 8) the multimodal CAB, 9) the constrained SSO method.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 216 pp. Englisch.
Seller Inventory # 9783319285023
The goal of this book is to present advances that discuss alternative Evolutionary Computation (EC) developments and non-conventional operators which have proved to be effective in the solution of several complex problems. The book has been structured so that each chapter can be read independently from the others. The book contains nine chapters with the following themes: 1) Introduction, 2) the Social Spider Optimization (SSO), 3) the States of Matter Search (SMS), 4) the collective animal behavior (CAB) algorithm, 5) the Allostatic Optimization (AO) method, 6) the Locust Search (LS) algorithm, 7) the Adaptive Population with Reduced Evaluations (APRE) method, 8) the multimodal CAB, 9) the constrained SSO method.
The goal of this book is to present advances that discuss alternative Evolutionary Computation (EC) developments and non-conventional operators which have proved to be effective in the solution of several complex problems. The book has been structured so that each chapter can be read independently from the others. The book contains nine chapters with the following themes: 1) Introduction, 2) the Social Spider Optimization (SSO), 3) the States of Matter Search (SMS), 4) the collective animal behavior (CAB) algorithm, 5) the Allostatic Optimization (AO) method, 6) the Locust Search (LS) algorithm, 7) the Adaptive Population with Reduced Evaluations (APRE) method, 8) the multimodal CAB, 9) the constrained SSO method.
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