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Interactive Evolutionary Algorithms with Decision-Maker’s Preferences for Solving Interval Multi-objective Optimization Problems

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Emerging Intelligent Computing Technology and Applications (ICIC 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 304))

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Abstract

Multi-objective optimization problems (MOPs) with interval parameters are considerably popular and important in real-world applications. A novel evolutionary algorithm incorporating with a decision-maker (DM)’s preferences is presented to obtain their Pareto subsets which meet the DM’s preferences in this study. The proposed algorithm is applied to four MOPs with interval parameters and compared with other two algorithms. The experimental results confirm the advantages of the proposed algorithm.

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References

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Author information

Authors and Affiliations

  1. School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, China

    Dunwei Gong, Xinfang Ji, Jing Sun & Xiaoyan Sun

Authors
  1. Dunwei Gong
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  2. Xinfang Ji
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  3. Jing Sun
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  4. Xiaoyan Sun
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Editor information

Editors and Affiliations

  1. Machine Learning and Systems Biology Laboratory, School of Electronics and Information Engineering, Tongji University, Shanghai, China

    De-Shuang Huang

  2. Department of Computer Science and Engineering, Indian Institute of Technology Kanpur, 208016, Kanpur, India

    Phalguni Gupta

  3. Department of Chemistry, University of Louisville, 2320 South Brook Street, 40292, Louisville, Kentucky, USA

    Xiang Zhang

  4. School of Electrical, Computer & Telecommunications Engineering, The University of Wollongong,, 2522, North Wollongong, NSW, Australia

    Prashan Premaratne

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© 2012 Springer-Verlag Berlin Heidelberg

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Gong, D., Ji, X., Sun, J., Sun, X. (2012). Interactive Evolutionary Algorithms with Decision-Maker’s Preferences for Solving Interval Multi-objective Optimization Problems. In: Huang, DS., Gupta, P., Zhang, X., Premaratne, P. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2012. Communications in Computer and Information Science, vol 304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31837-5_4

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  • DOI: https://doi.org/10.1007/978-3-642-31837-5_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31836-8

  • Online ISBN: 978-3-642-31837-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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