Full Description
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.
Contents
Introduction.- A Swarm Global Optimization Algorithm Inspired in the Behavior of the Social-spider.-A States of
Matter Algorithm for Global Optimization.- An Algorithm for Global Optimization Inspired
by Collective Animal Behavior.- A Bio-inspired Evolutionary Algorithm: Allostatic
Optimization.- Optimization Based on the Behavior of Locust Swarms.
