Iterative Solution Process for Multiple Objective Stochastic Linear Programming Problems Under Fuzzy Environment. Issue 4 (2nd October 2018)

• Record Type: Journal Article
• Authors: Garai, Arindam; Mandal, Palash; Roy, Tapan Kumar
• Is Part Of: Fuzzy information and engineering. Volume 10:Issue 4(2018)
• Page Start: 435
• Page End: 451
• Publication Date: 2018-10-02
• Subjects: Main objective function -- trade-off ratio -- chance-constrained programming -- expectation model -- fuzzy multi-objective optimisation -- stochastic optimisation; Fuzzy systems -- Periodicals; Intelligent control systems -- Periodicals; 629.89
• DOI: 10.1080/16168658.2020.1750871
• Languages: English
• ISSNs: 1616-8658

Abstract

Abstract : This article presents one interactive algorithm, and thereby determines the Pareto optimal solution to multi-objective stochastic linear programming (MOSLP) problems in real-life oriented fuzzy environment. Among the various objective functions, there always exists one objective function, referred to as the main objective function in this article, to multi-objective models, whose optimal value is most vital to decision-makers. When the optimal value to main objective function meets the pre-determined aspiration level, and the corresponding values to other objective functions are satisfactory in nature, that Pareto optimal solution is acceptable to decision-makers. Again, in several existing interactive fuzzy optimisation methods to MOSLP models, all reference membership levels of expectations to objective functions are considered as a unity. However, this seems to be less rational that the expectation of each conflicting objective function simultaneously attains the individual goal. So, the present article proposes to employ the trade-off ratios of membership functions to analytically determine reference membership levels in a fuzzy environment. Numerical applications further illustrate this algorithm. Finally, conclusions are drawn.