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A Multi-direction Prediction Approach for Dynamic Multi-objective Optimization

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Intelligent Computing Methodologies (ICIC 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9773))

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Abstract

In the real word, many multi-objective optimization problems are subject to dynamic changing conditions, which may occur in objectives, constraints and parameters. This paper provides a prediction strategy, called multi-direction prediction strategy (MDP), to enhance the performance of multi-objective evolutionary optimization algorithms in dealing with dynamic environments. Besides, the proposed prediction method makes use of multiple directions determined by several representative individuals. Our experimental results indicate that MDP can well tackle dynamic multi-objective problems.

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Acknowledgement

This research was supported by the National Natural Science Funds of China (No. 61473299), the Natural Science Foundation of Jiangsu province (No. BK20130207),and the China Postdoctoral Science Foundation funded project (No. 2014T70557, 2012M521142).

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Authors and Affiliations

  1. School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, 221116, China

    Miao Rong, Dun-wei Gong & Yong Zhang

  2. School of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou, 730050, China

    Dun-wei Gong

Authors
  1. Miao Rong
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  2. Dun-wei Gong
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  3. Yong Zhang
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Corresponding author

Correspondence to Miao Rong .

Editor information

Editors and Affiliations

  1. Tongji University , Shanghai, China

    De-Shuang Huang

  2. Inha University , Incheon, Korea (Republic of)

    Kyungsook Han

  3. Liverpool John Moores University , Liverpool, United Kingdom

    Abir Hussain

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Rong, M., Gong, Dw., Zhang, Y. (2016). A Multi-direction Prediction Approach for Dynamic Multi-objective Optimization. In: Huang, DS., Han, K., Hussain, A. (eds) Intelligent Computing Methodologies. ICIC 2016. Lecture Notes in Computer Science(), vol 9773. Springer, Cham. https://doi.org/10.1007/978-3-319-42297-8_58

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  • DOI: https://doi.org/10.1007/978-3-319-42297-8_58

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42296-1

  • Online ISBN: 978-3-319-42297-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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