A note on the performance of genetic algorithms on zero-one knapsack problems

Abstract

For small zero-one knapsack problems, simple branch-and-bound and depth-first methods generate solutions much faster than our genetic algorithms. For large problems, branch-and-bound and depth-first methods outperform the genetic algorithms both for finding optimal solutions and for finding approximate solutions quickly. The simple methods perform much better than genetic algorithms on this class of problem in spite of the existence of a genetic encoding scheme which exploits useful local information. The results highlight the need for a betler understanding of which problems are suitable for genetic algorithms and which problems are not.

DOI: 10.1145/326619.326696

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Cite this paper

@inproceedings{Gordon1994ANO, title={A note on the performance of genetic algorithms on zero-one knapsack problems}, author={V. Scott Gordon and A. P. Wim B{\"{o}hm and L. Darrell Whitley}, booktitle={SAC}, year={1994} }