A Two-Stage Multi-objective Programming Model to Improve the Reliability of Solution
Chenxia Jin, Fachao Li, Kaixin Feng, Yunfeng Guo · International Journal of Computational Intelligence Systems · 2020
Randomness is a common uncertainty encountered in practical multi-objectives decision-making.But it is always a challenge for decision-makers to process randomness in multi-objective programming problems.This paper takes the decision-making objectives as fuzzy events and aims to solve numerical multi-objective programming problems under random environment.We first analyze the effects of randomness on multi-objective decision-making results.With the expectation value and the probability of fuzzy events as quantitative index of randomness, we then establish a two-stage random multi-objective programming model based on reliability (i.e., TS-MOPM).Specifically, we give several probability calculation methods of fuzzy events with common distributions, and further present the corresponding calculation procedures for solving TS-MOPM.Finally, a case study is implemented to test the proposed model TS-MOPM.Theoretical analysis and case study indicate that our model has better interpretability and operability.The research results enrich the existing random multi-objective programming methods to some extent.