DocumentCode :
2728831
Title :
Comparing algorithms, representations and operators for the multi-objective knapsack problem
Author :
Colombo, Gualtiero ; Mumford, Christine L.
Author_Institution :
Sch. of Comput. Sci., Cardiff Univ., UK
Volume :
2
fYear :
2005
fDate :
2-5 Sept. 2005
Firstpage :
1268
Abstract :
This paper compares the performance of three evolutionary multi-objective algorithms on the multi-objective knapsack problem. The three algorithms are SPEA2 (strength Pareto evolutionary algorithm, version 2), MOGLS (multi-objective genetic local search) and SEAMO2 (simple evolutionary algorithm for multi-objective optimization, version 2). For each algorithm, we try two representations: bit-string and order-based. Our results suggest that a bit-string representation works best for MOGLS, but that SPEA2 and SEAMO2 perform better with an order-based approach. Although MOGLS outperforms the other algorithms in terms of solution quality, SEAMO2 runs much faster than its competitors and produces results of a similar standard to SPEA2.
Keywords :
Pareto optimisation; genetic algorithms; knapsack problems; mathematical operators; search problems; algorithm comparison; bit-string representation; evolutionary multiobjective algorithm; multibjective knapsack problem; multiobjective genetic local search; multiobjective optimization; operator comparison; order-based representation; strength Pareto evolutionary algorithm; Biological cells; Computer science; Decoding; Evolutionary computation; Genetics; Pareto optimization; Standards development; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Print_ISBN :
0-7803-9363-5
Type :
conf
DOI :
10.1109/CEC.2005.1554836
Filename :
1554836
Link To Document :
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