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M-PAES: a memetic algorithm for multiobjective optimization
Abstract
A memetic algorithm for tackling multiobjective optimization problems is presented. The algorithm employs the proven local search strategy used in the Pareto archived evolution strategy (PAES) and combines it with the use of a population and recombination. Verification of the new M-PAES (memetic PAES) algorithm is carried out by testing it on a set of multiobjective 0/1 knapsack problems. On each problem instance, a comparison is made between the new memetic algorithm, the (1+1)-PAES local searcher, and the strength Pareto evolutionary algorithm (SPEA) of E. Zitzler and L. Thiele (1998, 1999).
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Cited by
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Ishibuchi, H., Yoshida, T., & Murata, T. (2003) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2003.810752 · Cited by 773
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Metadata
- Authors
- Knowles, J. D., & Corne, D. W.
- Venue
- Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)
- Publisher
- IEEE
- Published
- 2002-11-07
- Volume
- 1
- Pages
- 325-332
- OpenAlex
- W1563728692
- Cited by
- 359
- References
- 0
- FWCI
- 15.03
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Knowles, J. D., & Corne, D. W. (2002). M-PAES: a memetic algorithm for multiobjective optimization. Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512). https://doi.org/10.1109/cec.2000.870313
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