Solving stochastic multi-objective programming in multi-attribute portfolio selection through the goal programming model

The aim of this paper is to present an approach for solving the Stochastic Multi-Objective Programming (SMOP) and formulate a Stochastic Goal Programming model that will be applied to multi-attribute portfolio selection problem. The concept of satisfaction function will be utilized to incorporate explicitly the financial decision-maker’s preferences for selecting the best financial portfolio based on several conflicting objectives. The proposed approach will be illustrated through numerical examples from the Tunisian stock exchange market