Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)
In this paper, we focus on hierarchical multiobjective linear programming problems with random variable coefficients where multiple decision makers in a hierarchical organization have their own multiple objective linear functions together with common linear constraints. In order to deal with objective linear functions and linear constraints with random variable coefficients, p-Pareto optimality concept is introduced. After each decision maker specifies his/her own decision power and reference probabilistic values, the corresponding candidate of the satisfactory solution is obtained among from p-Pareto optimal solution set on the basis of linear programming. Each decision maker updates his/her own decision power and/or reference probabilistic values according to the two rules, until the satisfactory solution is obtained. An interactive processes are demonstrated by means of an illustrative numerical example.
