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Evolutionary Optimization pp 57–86Cite as

Evolutionary Algorithms and Constrained Optimization

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Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 48))

Abstract

Evolutionary computation techniques have received a lot of attention regarding their potential as optimization techniques for complex numerical functions. However, they have not produced a significant breakthrough in the area of nonlinear programming due to the fact that they have not addressed the issue of constraints in a systematic way. Only during the last decade several methods have been proposed for handling nonlinear constraints by evolutionary algorithms for numerical optimization problems; however, these methods give different performance on different test cases.

In this chapter we (1) present some issues which should be addressed while solving the general nonlinear programming problem, (2) survey several approaches which have emerged in the evolutionary computation community, and (3) discuss briefly a methodology, which may serve as a handy reference for future methods.

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Authors
  1. Zbigniew Michalewicz
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  2. Martin Schmidt
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© 2003 Kluwer Academic Publishers

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Michalewicz, Z., Schmidt, M. (2003). Evolutionary Algorithms and Constrained Optimization. In: Evolutionary Optimization. International Series in Operations Research & Management Science, vol 48. Springer, Boston, MA. https://doi.org/10.1007/0-306-48041-7_3

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  • DOI: https://doi.org/10.1007/0-306-48041-7_3

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-7923-7654-5

  • Online ISBN: 978-0-306-48041-6

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