Applying genetic algorithms to selected topics commonly encountered in engineering practice

A carefully selected group of optimization problems is addressed to advocate application of genetic algorithms in various engi-neering optimization domains. Each topic introduced in the present paper serves as a representative of a larger class of interesting problems that arise frequently in many applications such as design tasks, functional optimization associated with various variational formulations, or a number of problems linked to image evaluation. No particular preferences are given to any version of genetic algorithms, but rather lessons learnt up-to-date are eectively combined to show the power of the genetic algorithm in eective search for the desired solution over a broad class of optimization problems discussed herein. Ó 2000 Elsevier Science B.V. All rights reserved