Margarita Arimatea Díaz Cortés - Böcker

The goal of this book is topresent advances that discuss alternative Evolutionary Computation (EC) developmentsand non-conventional operators which have proved to be effective 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.

This book bridges the gap between Soft Computing techniques and their applications to complex engineering problems. In each chapter we endeavor to explain the basic ideas behind the proposed applications in an accessible format for readers who may not possess a background in some of the fields. Therefore, engineers or practitioners who are not familiar with Soft Computing methods will appreciate that the techniques discussed go beyond simple theoretical tools, since they have been adapted to solve significant problems that commonly arise in such areas. At the same time, the book will show members of the Soft Computing community how engineering problems are now being solved and handled with the help of intelligent approaches.Highlighting new applications and implementations of Soft Computing approaches in various engineering contexts, the book is divided into 12 chapters. Further, it has been structured so that each chapter can be read independently of the others.

The goal of this book is topresent advances that discuss alternative Evolutionary Computation (EC) developmentsand non-conventional operators which have proved to be effective 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.