M-PAES: a memetic algorithm for multiobjective optimization

M-PAES: a memetic algorithm for multiobjective optimization

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 PAE...

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Hauptverfasser: Knowles, J.D., Corne, D.W.
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Computer science
Convergence
Cybernetics
Decision making
Evolutionary computation
Genetic algorithms
Operations research
Simulated annealing
Testing
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Corne, D.W.
description 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).
doi_str_mv 10.1109/CEC.2000.870313
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subjects Aggregates
Computer science
Convergence
Cybernetics
Decision making
Evolutionary computation
Genetic algorithms
Operations research
Simulated annealing
Testing
title M-PAES: a memetic algorithm for multiobjective optimization
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