Home // ICCGI 2012, The Seventh International Multi-Conference on Computing in the Global Information Technology // View article

Multi-modal Optimization using a Simple Artificial Immune Algorithm

Authors:
Tad Gonsalves
Yu Aiso

Keywords: evolutionary computation; multi-modal optimization; artificial immune algorithm

Abstract:
Evolutionary Algorithms have an inherent parallelism that should enable them to locate several optima of a multi-modal function. However, in practice they are found to converge to a single (global) optimum. This has led to the research in the design of highly specialized evolutionary algorithms to obtain the maximum number of global and local optima of multi-modal functions. However, this is an over-kill, since in most cases the management needs no more than a handful of optima to make decisions. We demonstrate that the ordinary CLONALG algorithm, without any special modification to handle multi-modal optimization, is powerful enough to obtain several global and local optima to support the decision-making process.

Pages: 183 to 188

Copyright: Copyright (c) IARIA, 2012

Publication date: June 24, 2012

Published in: conference

ISSN: 2308-4529

ISBN: 978-1-61208-202-8

Location: Venice, Italy

Dates: from June 24, 2012 to June 29, 2012