Title :
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
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;
Conference_Titel :
Evolutionary Computation, 2000. Proceedings of the 2000 Congress on
Conference_Location :
La Jolla, CA
Print_ISBN :
0-7803-6375-2
DOI :
10.1109/CEC.2000.870313
