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An interactive satisficing approach for multi-objective optimization with uncertain parameters

Author

Listed:
  • Shuya Zhong

    (Shanghai University)

  • Yizeng Chen

    (Shanghai University)

  • Jian Zhou

    (Shanghai University)

  • Yuanyuan Liu

    (Shanghai University)

Abstract

Uncertain variables are used to describe the phenomenon where uncertainty appears in a complex system. For modeling the multi-objective decision-making problems with uncertain parameters, a class of uncertain optimization is suggested for the decision systems in Liu and Chen (2013), http://orsc.edu.cn/online/131020 which is called the uncertain multi-objective programming. In order to solve the proposed uncertain multi-objective programming, an interactive uncertain satisficing approach involving the decision-maker’s flexible demands is proposed in this paper. It makes an improvement in contrast to the noninteractive methods. Finally, a numerical example about the capital budget problem is given to illustrate the effectiveness of the proposed model and the relevant solving approach.

Suggested Citation

  • Shuya Zhong & Yizeng Chen & Jian Zhou & Yuanyuan Liu, 2017. "An interactive satisficing approach for multi-objective optimization with uncertain parameters," Journal of Intelligent Manufacturing, Springer, vol. 28(3), pages 535-547, March.
    • Handle: RePEc:spr:joinma:v:28:y:2017:i:3:d:10.1007_s10845-014-0998-0
    DOI: 10.1007/s10845-014-0998-0
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    References listed on IDEAS

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    1. Niknam, Taher & Meymand, Hamed Zeinoddini & Mojarrad, Hasan Doagou, 2011. "An efficient algorithm for multi-objective optimal operation management of distribution network considering fuel cell power plants," Energy, Elsevier, vol. 36(1), pages 119-132.
    2. Tzeng, Gwo-Hshiung & Cheng, Hsin-Jung & Huang, Tsung Dow, 2007. "Multi-objective optimal planning for designing relief delivery systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 673-686, November.
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    Cited by:

    1. Jian Zhou & Yujiao Jiang & Athanasios A. Pantelous & Weiwen Dai, 2023. "A systematic review of uncertainty theory with the use of scientometrical method," Fuzzy Optimization and Decision Making, Springer, vol. 22(3), pages 463-518, September.
    2. Mingxuan Zhao & Yuhan Liu & Dan A. Ralescu & Jian Zhou, 2018. "The covariance of uncertain variables: definition and calculation formulae," Fuzzy Optimization and Decision Making, Springer, vol. 17(2), pages 211-232, June.

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