Advances of Evolutionary Computation: Methods and Operators (Paperback)
Erik Cuevas
Sold by Grand Eagle Retail, Bensenville, IL, U.S.A.
AbeBooks Seller since 12 October 2005
New - Soft cover
Condition: New
Quantity: 1 available
Add to basketSold by Grand Eagle Retail, Bensenville, IL, U.S.A.
AbeBooks Seller since 12 October 2005
Condition: New
Quantity: 1 available
Add to basketPaperback. The goal of this book is topresent advances that discuss alternative Evolutionary Computation (EC) developmentsand non-conventional operators which have proved to be eective 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Seller Inventory # 9783319803661
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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