Robust goal programming for multi-objective portfolio selection problem

This paper proposes a robust optimization model for the portfolio selection problem that uses a goal programming (GP) approach. In GP, decision makers can achieve more than one objective function. Some uncertain coefficients exist in both single and multi-objective models of the portfolio selection problem, which affects the feasibility and optimality of solutions. Robust optimization is an approach that deals with the uncertainty parameters in mathematical models, and guarantees the feasibility of the solutions. This paper tries to address the uncertainty parameters with robust optimization approach. This paper presents GP for the portfolio selection problem and addresses the uncertainty of the parameters by use of robust optimization approach. The approach is illustrated by a numerical example.