×

zbMATH — the first resource for mathematics

Towards a quick computation of well-spread Pareto-optimal solutions. (English) Zbl 1036.90525
Fonseca, Carlos M. (ed.) et al., Evolutionary multi-criterion optimization. Second international conference, EMO 2003, Faro, Portugal, April 8–11, 2003. Proceedings. Berlin: Springer (ISBN 3-540-01869-7/pbk). Lect. Notes Comput. Sci. 2632, 222-236 (2003).
Summary: The trade-off between obtaining a good distribution of Pareto-optimal solutions and obtaining them in a small computational time is an important issue in evolutionary multi-objective optimization (EMO). It has been well established in the EMO literature that although SPEA produces a better distribution compared to NSGA-II, the computational time needed to run SPEA is much larger. In this paper, we suggest a clustered NSGA-II which uses an identical clustering technique to that used in SPEA for obtaining a better distribution. Moreover, we propose a steady-state MOEA based on \(\epsilon\)-dominance concept and efficient parent and archive update strategies. Based on a comparative study on a number of two and three objective test problems, it is observed that the steady-state MOEA achieves a comparable distribution to the clustered NSGA-II with a much less computational time.
For the entire collection see [Zbl 1018.00013].

MSC:
90C29 Multi-objective and goal programming
68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
90C59 Approximation methods and heuristics in mathematical programming
PDF BibTeX XML Cite
Full Text: Link