Fractile criterion iterative-interactive optimization process for multi-objective stochastic linear programming problems in fuzzy environment

Abstract

Present article focuses on one general fractile criterion iterative-interactive optimisation process in order to obtain the preferable Pareto optimal solution, subject to specified main objective function to multi-objective stochastic linear programming problems in fuzzy environment. This asks the managers to identify the main objective function among all objective functions without specifying any weights or utility functions. Unlike existing articles, the reference membership levels to conflicting objective functions are analytically determined by employing the trade-off ratios among objective functions in this process. Moreover, the necessity of only very few interactions with decision-makers saves the precious time and money of organisations. Numerical applications demonstrate the efficiency of proposed process. Finally, conclusions are drawn.