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| Authors: | Marco Laumanns, Lothar Thiele, Kalyanmoy Deb, Eckart Zitzler |
| Group: | Computer Engineering |
| Type: | Inproceedings |
| Title: | Archiving with Guaranteed Convergence And Diversity in Multi-objective Optimization |
| Year: | 2002 |
| Month: | July |
| Pub-Key: | LTDZ2002a |
| Book Titel: | GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference |
| Pages: | 439-447 |
| Keywords: | EMO |
| Publisher: | Morgan Kaufmann Publishers |
| Abstract: | Over the past few years, the research on evolutionary algorithms has demonstrated their niche in solving multi-objective optimization problems, where the goal is to find a number of Pareto-optimal solutions in a single simulation run. However, none of the multi-objective evolutionary algorithms (MOEAs) has a proof of convergence to the true Pareto-optimal solutions with a wide diversity among the solutions. In this paper we discuss why a number of earlier MOEAs do not have such properties. A new archiving strategy is proposed that maintains a subset of the generated solutions. It guarantees convergence and diversity according to well-defined criteria, i.e. $e$-dominance and $e$-Pareto optimality. |
| Location: | New York, NY, USA |
| Resources: | [BibTeX] [Paper as PDF] |
