Knowledge-based nonuniform crossover

Harpal Maini, Kishan Mehrotra, Chilukuri K Mohan, Sanjay Ranka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

One-point, two-point and k-point crossover can be viewed as special cases of uniform crossover, where genetic material is chosen each locus of either parent with equal probability. This paper generalizes uniform crossover to `non-uniform crossover' using `mask' vectors whose elements are real numbers qq[0,1], representing problem-specific knowledge that improves performance by biasing the selection of alleles from either parent. This knowledge based non-uniform crossover (KNUX) is applied to two NP optimization problems: graph partitioning and soft-decision decoding of linear block codes. Simulation results show orders of magnitude improvement of this operator over two-point and uniform crossover. An appropriate schema theorem is also developed.

Original languageEnglish (US)
Title of host publicationIEEE Conference on Evolutionary Computation - Proceedings
PublisherIEEE Computer Society
Pages22-27
Number of pages6
Volume1
StatePublished - 1994
EventProceedings of the 1st IEEE Conference on Evolutionary Computation. Part 1 (of 2) - Orlando, FL, USA
Duration: Jun 27 1994Jun 29 1994

Other

OtherProceedings of the 1st IEEE Conference on Evolutionary Computation. Part 1 (of 2)
CityOrlando, FL, USA
Period6/27/946/29/94

ASJC Scopus subject areas

  • Engineering(all)

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    Maini, H., Mehrotra, K., Mohan, C. K., & Ranka, S. (1994). Knowledge-based nonuniform crossover. In IEEE Conference on Evolutionary Computation - Proceedings (Vol. 1, pp. 22-27). IEEE Computer Society.