Optimum Population Size and Mutation Rate for a Simple Real Genetic Algorithm that Optimizes Array Factors

Authors

  • Randy L. Haupt Utah State University, Electrical and Computer Engineering 4120 Old Main Hill Logan

Keywords:

Optimum Population Size and Mutation Rate for a Simple Real Genetic Algorithm that Optimizes Array Factors

Abstract

The population size and mutation rate of a genetic algorithm have great influence upon the speed of convergence. Most genetic algorithm enthusiants use a large population size and low mutation rate due to the recommendations of several early studies. These studies were somewhat limited. This paper presents results that show a small population size and high mutation rate are actually better for many problems.

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Published

2022-07-09

How to Cite

[1]
R. L. Haupt, “Optimum Population Size and Mutation Rate for a Simple Real Genetic Algorithm that Optimizes Array Factors”, ACES Journal, vol. 15, no. 2, pp. 94–102, Jul. 2022.

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Section

General Submission