With a comparison to the random selection approach used in the weight-based multiobjective immune algorithm (WBMOIA), this paper proposes a new selection approach based on the truncation algorithm with similar individuals (TASI). Then the effect of the proposed selection approach is examined on the performance of WBMOIA. On one hand, the performance is compared between WBMOIA with the random selection approach and WBMOIA with the proposed selection approach. On the other hand, simulation results on a number of problems are presented to investigate if there exists any value of the reduction rate where WBMOIA performs well. Experiment results show that the performance of WBMOIA can be improved by the proposed selection approach and a better reduction rate can be obtained for each test problem. © Springer-Verlag 2009.
CITATION STYLE
Gao, J., Fang, Z., & Fang, L. (2009). Effects of similarity-based selection on WBMOIA: A weight-based multiobjective immune algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5821 LNCS, pp. 191–200). https://doi.org/10.1007/978-3-642-04843-2_21
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