An analysis of an embedded crossover scheme on a GA-hard problem

A. R. Venkatachalam

doi:10.1016/0305-0548(93)E0025-O

An analysis of an embedded crossover scheme on a GA-hard problem

A. R. Venkatachalam

CM - Dean's Office

University of New Hampshire

Research output: Contribution to journal › Article › peer-review

Abstract

This paper analyzes the effect of an embedded crossover scheme on the performance of a genetic algorithm in solving a GA-hard problem. Embedded crossover schemes have been found to be efficient in achieving convergence in a variety of numerical problems in the past. This analysis confirms these findings through a minimal deceptive problem (with severe deceptive conditions), which would cause a simple GA to diverge from the best solution.

Original language	English
Pages (from-to)	149-157
Number of pages	9
Journal	Computers and Operations Research
Volume	22
Issue number	1
DOIs	https://doi.org/10.1016/0305-0548(93)E0025-O
State	Published - Jan 1995

ASJC Scopus Subject Areas

General Computer Science
Modeling and Simulation
Management Science and Operations Research

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10.1016/0305-0548(93)E0025-O

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An analysis of an embedded crossover scheme on a GA-hard problem

Abstract

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