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Fuzzy programming for mixed-integer optimization problems

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Abstract

Mixed-integer optimization problems belong to the group of NP-hard combinatorial problems. Therefore, they are difficult to search for global optimal solutions. Mixed-integer optimization problems are always described by precise mathematical programming models. However, many practical mixed-integer optimization problems have inherited a more or less imprecise nature. Under these circumstances, if we take into account the flexibility of the constraints and the fuzziness of the objectives, the original mixed-integer optimization problems can be formulated as fuzzy mixed-integer optimization problems. Mixed-integer hybrid differential evolution (MIHDE) is an evolutionary search algorithm which has been successfully applied to many complex mixed-integer optimization problems. In this article, a fuzzy mixed-integer mathematical programming model is developed to formulate the fuzzy mixed-integer optimization problem. In addition the MIHDE is introduced to solve the fuzzy mixed-integer programming problem. Finally, the illustrative example shows that satisfactory results can be obtained by the proposed method. This demonstrates that MIHDE can effectively handle fuzzy mixed-integer optimization problems.

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Authors and Affiliations

  1. Graduate School of Engineering Science and Technology, National Yunlin University of Science and Technology, Yunlin, Taiwan, ROC

    Yung-Chin Lin

  2. Department of Electrical Engineering, WuFeng University, Minhsiung, Chiayi County, Taiwan, ROC

    Yung-Chien Lin & Tsing-Hua Chen

  3. Department of Electrical Engineering, National Yunlin University of Science and Technology, Douliou, Yunlin, 64002, Taiwan, ROC

    Kuo-Lan Su

  4. Department of Electrical Engineering, I-Shou University, Dashu District, Kaohsiung City, Taiwan, ROC

    Wei-Cheng Lin

Authors
  1. Yung-Chin Lin
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  2. Yung-Chien Lin
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  3. Kuo-Lan Su
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  4. Wei-Cheng Lin
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  5. Tsing-Hua Chen
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Corresponding author

Correspondence to Yung-Chien Lin.

Additional information

This work was presented in part at the 16th International Symposium on Artificial Life and Robotics, Oita, Japan, January 27–29, 2011

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Lin, YC., Lin, YC., Su, KL. et al. Fuzzy programming for mixed-integer optimization problems. Artif Life Robotics 16, 174–177 (2011). https://doi.org/10.1007/s10015-011-0909-9

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  • DOI: https://doi.org/10.1007/s10015-011-0909-9

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