Genetic algorithms in computer aided design |
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Authors: | Gábor Renner [Author Vitae] Anikó Ekárt [Author Vitae] |
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Affiliation: | a Computer and Automation Research Institute, Hungarian Academy of Sciences, P.O. Box 63, 1518 Budapest, Hungary b School of Computer Science, The University of Birmingham, Birmingham B15 2TT, UK |
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Abstract: | Design is a complex engineering activity, in which computers are more and more involved. The design task can often be seen as an optimization problem in which the parameters or the structure describing the best quality design are sought.Genetic algorithms constitute a class of search algorithms especially suited to solving complex optimization problems. In addition to parameter optimization, genetic algorithms are also suggested for solving problems in creative design, such as combining components in a novel, creative way.Genetic algorithms transpose the notions of evolution in Nature to computers and imitate natural evolution. Basically, they find solution(s) to a problem by maintaining a population of possible solutions according to the ‘survival of the fittest’ principle. We present here the main features of genetic algorithms and several ways in which they can solve difficult design problems. We briefly introduce the basic notions of genetic algorithms, namely, representation, genetic operators, fitness evaluation, and selection. We discuss several advanced genetic algorithms that have proved to be efficient in solving difficult design problems. We then give an overview of applications of genetic algorithms to different domains of engineering design. |
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Keywords: | CAD Genetic algorithms Optimization Geometric design Conceptual design Mechanism design |
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