Abstract
For decision making problems involving uncertainty, there exist two typical approaches: a stochastic programming based on the probability theory and a fuzzy programming based on the fuzzy set theory, and they have been developed in various ways. In this paper, we focus on multiobjective linear programming problems invoving random variable coefficients. After reformulating them based on the variance minimization model which aims to minimize variances of objective functions in view of risk avoidance under chance constrained conditions, we attempt to apply the interactive fuzzy satisficing method to the formulated problems. To be more specific, introducing fuzzy goals to consider the fuzziness of the decision maker's judgement for objective functions and applying the interactive fuzzy satisficing method to derive a satisficing solution for the decision maker through interaction, we propose a new decision making method as a hybrid of the stochastic programming and the fuzzy programming.
