Development of STEM Decision-Making Technique using Simulation Approaches and Utility Function

Various techniques and approaches have been presented to solve multi-objective decision making problems under different assumptions. The STEM technique is also one of the most widely used techniques for dealing with this group of problems, especially for solving multi-objective linear programming (MOLP) models. In the current research, a new approach has been proposed as the development of the mentioned method. In this regard, the second phase of the method is integrated with the simulation process and the concept of utility function has been used in order to determine the probability of selecting targets. For each of the selected targets, several random adjustment rates are defined. Random selection of satisfactory functions based on their utility and using simulation tools, will "create diversity in the selected objectives for adjustment". Also, by considering different and random adjustment rates for selected functions, while facilitating the decision-making process and providing an analytical report to the decision-maker, it will be possible to apply "different levels of satisfaction" of the decision-maker. A three-objective problem with five constraints, is solved using the proposed method and its results are presented. The results indicate that applying the above changes will lead to solving some of the basic limitations of this method that have been mentioned in previous studies. Comparing the proposed technique with the basic method, shows the overall superiority of the proposed method, especially in the criteria related to interaction with the decision maker.