M-PAES: a memetic algorithm for multiobjective optimization

Author

Knowles, Joshua D. ; Corne, David W.

Author_Institution

Sch. of Comput. Sci., Cybern. & Electron. Eng., Reading Univ., UK

Volume

1

fYear

2000

fDate

2000

Firstpage

325

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)

Keywords

Pareto distribution; evolutionary computation; integer programming; knapsack problems; operations research; search problems; (1+1)-PAES local searcher; M-PAES algorithm; Pareto archived evolution strategy; algorithm verification; local search strategy; memetic algorithm; multiobjective 0/1 knapsack problems; multiobjective optimization problems; population; recombination; strength Pareto evolutionary algorithm; Aggregates; Computer science; Convergence; Cybernetics; Decision making; Evolutionary computation; Genetic algorithms; Operations research; Simulated annealing; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2000. Proceedings of the 2000 Congress on

Conference_Location

La Jolla, CA

Print_ISBN

0-7803-6375-2

Type

conf

DOI

10.1109/CEC.2000.870313

Filename

870313