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Solving Bi-objective Unconstrained Binary Quadratic Programming Problem with Multi-objective Backbone Guided Search Algorithm

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Intelligent Computing Theories and Application (ICIC 2016)

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Abstract

This paper presents a multi-objective backbone guided search algorithm in order to optimize a bi-objective unconstrained binary quadratic programming problem. Our proposed algorithm consists of two main procedures which are hypervolume-based local search and backbone guided search. When the hypervolume-based local search procedure can not improve the Pareto approximation set any more, the backbone guided search procedure is applied for further improvements. Experimental results show that the proposed algorithm is very effective compared with the original multi-objective optimization algorithms.

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Notes

  1. 1.

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Acknowledgment

The work in this paper was supported by the Fundamental Research Funds for the Central Universities (Grant No. A0920502051408-25), supported by the Research Foundation for International Young Scientists of China (Grant No. 61450110443), supported by the Scientific Research Foundation for the Returned Overseas Chinese Scholars (Grant Nos. 2015S03007), supported by National Natural Science Foundation of China (Grant No. 61370150, 61433014 and 71501157) and supported by West Light Foundation of Chinese Academy of Science (Grant No: Y4C0011001). The authors would like to thank the anonymous referees for their valuable comments and suggestions.

Author information

Authors and Affiliations

  1. School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, Sichuan, People’s Republic of China

    Li-Yuan Xue

  2. School of Mathematics, Southwest Jiaotong University, Chengdu, 610031, Sichuan, People’s Republic of China

    Rong-Qiang Zeng

  3. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, Sichuan, People’s Republic of China

    Rong-Qiang Zeng

  4. School of Management, Northwestern Polytechnical University, Xi’an, 710072, Shanxi, People’s Republic of China

    Yang Wang

  5. Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, 400714, People’s Republic of China

    Ming-Sheng Shang

Authors
  1. Li-Yuan Xue
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  2. Rong-Qiang Zeng
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  3. Yang Wang
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  4. Ming-Sheng Shang
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Corresponding author

Correspondence to Rong-Qiang Zeng .

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Editors and Affiliations

  1. Tongji University , Shanghai, China

    De-Shuang Huang

  2. University of Ulsan , Ulsan, Korea (Republic of)

    Kang-Hyun Jo

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Xue, LY., Zeng, RQ., Wang, Y., Shang, MS. (2016). Solving Bi-objective Unconstrained Binary Quadratic Programming Problem with Multi-objective Backbone Guided Search Algorithm. In: Huang, DS., Jo, KH. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science(), vol 9772. Springer, Cham. https://doi.org/10.1007/978-3-319-42294-7_66

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  • DOI: https://doi.org/10.1007/978-3-319-42294-7_66

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42293-0

  • Online ISBN: 978-3-319-42294-7

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