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Genetic algorithm attributes for component selection

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Abstract

This paper uses a genetic algorithm for component selection given a user-defined system layout, a database of components, and a defined set of design specifications. A genetic algorithm is a search method based on the principles of natural selection. An introduction to genetic algorithms is presented, and genetic algorithm attributes that are useful for component selection are explored. A comparison of these attributes is performed using two industrial design problems. A set of genetic algorithm attributes including integer coding, uniform crossover, anti-incest mating, variable mating and mutation rates, retention of population members from generation to generation, and an attention shifted penalty function are suggested for a more efficient search in component selection problems.

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Authors and Affiliations

  1. Department of Mechanical, Aerospace, and Nuclear Engineering, Thornton Hall, University of Virginia, McCormick Road, 22903-2442, Charlottesville, VA, USA

    Susan E. Carlson

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  1. Susan E. Carlson
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Correspondence to Susan E. Carlson.

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Carlson, S.E. Genetic algorithm attributes for component selection. Research in Engineering Design 8, 33–51 (1996). https://doi.org/10.1007/BF01616555

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