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

Shuya Zhong, Yizeng Chen, Jian Zhou, Yuanyuan Liu

Research output: Contribution to journalArticlepeer-review

13 Citations (SciVal)


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), 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.

Original languageEnglish
Pages (from-to)535-547
Number of pages13
JournalJournal of Intelligent Manufacturing
Issue number3
Publication statusPublished - 1 Mar 2017

Bibliographical note

Funding Information:
This work was supported by Grants from the National Social Science Foundation of China (No. 13CGL057), the National Natural Science Foundation of China (No. 71272177), and the Innovation Program of Shanghai Municipal Education Commission (No. 13ZS065).


  • Interactive satisficing approach
  • Multi-objective optimization
  • Multi-objective programming
  • Uncertain programming
  • Uncertain variable

ASJC Scopus subject areas

  • Software
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence


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