A comparison of evolutionary programming and genetic algorithms on selected constrained optimization problems

A comparison of evolutionary programming and genetic algorithms on selected constrained optimization problems

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Article ID: iaor19952287
Country: United States
Volume: 64
Issue: 6
Start Page Number: 399
End Page Number: 406
Publication Date: Jun 1995
Journal: ACM SIGPLAN Notices
Authors:
Keywords: metaheuristics
Abstract:

Evolutionary programming and genetic algorithms are compared on two constrained optimization problems. The constrained problems are redesigned as related unconstrained problems by the appliction of penalty functions. The experiments indicate that evolutionary programming outperforms the genetic algorithm. The results are statistically significant under nonparametric hypothesis testing. The results also indicate potential difficulties in the design of suitable penalty functions for constrained optimization problems. A discussion is offered regarding the suitability of different methods of evolutionary computation for such problems.

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