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Decomposing the user-preference in multiobjective optimization

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Abstract

Preference information (such as the reference point) of the decision maker (DM) is often used in multiobjective optimization; however, the location of the specified reference point has a detrimental effect on the performance of multiobjective evolutionary algorithms (MOEAs). Inspired by multiobjective evolutionary algorithm-based decomposition (MOEA/D), this paper proposes an MOEA to decompose the preference information of the reference point specified by the DM into a number of scalar optimization subproblems and deals with them simultaneously (called MOEA/D-PRE). This paper presents an approach of iterative weight to map the desired region of the DM, which makes the algorithm easily obtain the desired region. Experimental results have demonstrated that the proposed algorithm outperforms two popular preference-based approaches, g-dominance and r-dominance, on continuous multiobjective optimization problems (MOPs), especially on many-objective optimization problems. Moreover, this study develops distinct models to satisfy different needs of the DM, thus providing a new way to deal with preference-based multiobjective optimization. Additionally, in terms of the shortcoming of MOEA/D-PRE, an improved MOEA/D-PRE that dynamically adjusts the size of the preferred region is proposed and has better performance on some problems.

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Acknowledgments

This work was supported by the research Projects: the National Natural Science Foundation of China under Grant Nos. 61379062, 61372049, the Natural Science Foundation of Hunan Province under Grant No. 14JJ2072, the National Natural Science Foundation of China No. 61403326, the Science and Technology Project of Hunan Province under Grant No. 2013SK3136, the Graduate Innovation Foundation of Hunan Province of China under Grant No. CX2013A011, the Key Research Project of Education Department of Hunan Province under Grant No. 12A135, and the Science and Technology Plan of Hunan Province of China under Grant No. 2014GK3027.

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Authors and Affiliations

  1. Department of Information Engineering, Xiangtan University, Hunan, 411100, China

    Guo Yu, Jinhua Zheng, Ruimin Shen & Miqing Li

  2. Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex, UB8 3PH, UK

    Miqing Li

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  1. Guo Yu
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  2. Jinhua Zheng
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  3. Ruimin Shen
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  4. Miqing Li
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Correspondence to Jinhua Zheng.

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Communicated by V. Loia.

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Yu, G., Zheng, J., Shen, R. et al. Decomposing the user-preference in multiobjective optimization. Soft Comput 20, 4005–4021 (2016). https://doi.org/10.1007/s00500-015-1736-z

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