Abstract
In this article, we present an agent-based method associated with a local research inspired by strategies of evolution to solve multiobjective problems. In comparison with GA-based methods this method uses few parameters. Moreover a decision maker can easily understand the influence of these parameters on the result. The conception of this method led us to represent the Pareto optimal set with zones and not with points. This representation gives additional information which allows to choose between two non-dominated solutions. © Springer-Verlag Berlin Heidelberg 2004.
Cite
CITATION STYLE
Beiro, A., & Sanchez, S. (2004). Autonomous agent for multi-objective optimization. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3102, 251–252. https://doi.org/10.1007/978-3-540-24854-5_22
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