Interactive Evolutionary Multi-Objective Optimization and Decision-Making using Reference Direction Method

In this paper, we borrow the concept of reference direction approach from the multi-criterion decision-making literature and combine it with all EMO procedure to develop an algorithm for finding a single preferred solution ill a multi-objective optimization scenario efficiently. EMO methodologies are adequately used to find a set of representative efficient, solutions over Hie past decade. This study is timely in addressing the issue Of optimizing and choosing a single solution using certain preference information. In this approach, the user supplies one or more reference directions in the objective, space. The population approach of EMO methodologies is exploited to find a Set of efficient, solutions corresponding to a number of representative points along the reference, direction. By using a utility function, a single solution is chosen for further analysis. This procedure is continued till no further improvement is possible. The, working of the procedure is demonstrated oil a set of test problems having two to tell Objectives and oil an engineering design problem. Results are verified with theoretically exact solutions oil two-objective test, problems.