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Incorporating Distance Domination in Multiobjective Evolutionary Algorithm

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2005) 3776 LNCS 684-689
DOI: 10.1007/11590316_110
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Abstract

In this article we propose a novel distance domination parameter and describe a multiobjective evolutionary concept called distance domination based multiobjective evolutionary algorithm (DBMEA). The distance parameter drives the algorithm faster in approximating the Pareto optimal front. To ensure proper diversity in the solutions of the non-dominating set, a new method for incorporating diversity is explained. The DBMEA has been compared with the NSGA-II algorithm on different test functions using different performance measures. © Springer-Verlag Berlin Heidelberg 2005.

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APA

Tripathi, P. K., Bandyopadhyay, S., & Pal, S. K. (2005). Incorporating Distance Domination in Multiobjective Evolutionary Algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3776 LNCS, pp. 684–689). https://doi.org/10.1007/11590316_110

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