Interactive MOEA/D for multi-objective decision making

Authors:
Maoguo Gong;Fang Liu;Wei Zhang;Licheng Jiao;Qingfu Zhang
Affiliations:
Xidian University, Xi'an, China;Xidian University, Xi'an, China;Xidian University, Xi'an, China;Xidian University, Xi'an, China;Xidian University, Xi'an, China
Venue:
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Year:
2011

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Abstract

In this paper, an interactive version of the decomposition based multiobjective evolutionary algorithm (iMOEA/D) is proposed for interaction between the decision maker (DM) and the algorithm. In MOEA/D, a multi-objective problem (MOP) can be decomposed into several single-objective sub-problems. Thus, the preference incorporation mechanism in our algorithm is implemented by selecting the preferred sub-problems rather than the preferred region in the objective space. At each interaction, iMOEA/D offers a set of current solutions and asks the DM to choose the most preferred one. Then, the search will be guided to the neighborhood of the selected. iMOEA/D is tested on some benchmark problems, and various utility functions are used to simulate the DM's responses. The experimental studies show that iMOEA/D can handle the preference information very well and successfully converge to the expected preferred regions.