Solving fuzzy stochastic multi-objective programming problems based on a fuzzy inequality

被引:0
|
作者
Nabavi, S. S. [1 ]
Souzban, M. [2 ]
Safi, M. R. [3 ]
Sarmast, Z. [4 ]
机构
[1] Semnan Univ, Semnan, Iran
[2] Univ Damghan, Sch Math & Comp Sci, Dept Appl Math, Damghan, Iran
[3] Semnan Univ, Fac Math Stat & Comp Sci, Semnan, Iran
[4] Univ Houston, Fac Math Stat & Comp Sci, Houston, TX USA
来源
IRANIAN JOURNAL OF FUZZY SYSTEMS | 2020年 / 17卷 / 05期
关键词
Multi-objective programming; stochastic programming; fuzzy programming; interactive algorithm; SATISFICING METHOD; OPTIMIZATION; MAXIMIZATION; MODEL;
D O I
暂无
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Probabilistic or stochastic programming is a framework for modeling optimization problems that involve uncertainty. In this paper, we focus on multi-objective linear programming problems in which the coefficients of constraints and the right hand side vector are fuzzy random variables. There are several methods in the literature that convert this problem to a stochastic or fuzzy problem. By using a special type of fuzzy inequality, we transform the problem into a convenient stochastic problem. Then some known methods are applied to obtain the optimal solution. Finally, the equivalent multi-objective problem is solved by an interactive approach. A numerical example is provided to illustrate the procedure.
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页码:43 / 52
页数:10
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