A methodology for solving multi-objective simulation-optimization problems

For many practical and industrial optimization problems where some or all of the system components are stochastic, the objective functions cannot be represented analytically. Due to the difficulties involved in the analytical expression, simulation may be the most effective means of studying these complex systems. Furthermore, many of these problems are characterized by the presence of multiple and confiicting objectives. The goal of this paper is to introduce a new methodology through an interactive algorithm for solving this multi-objective simulation optimization problem.