Planning and Planning (SP) plays a vital role in many fields. However, SP problems become more complex when they require to archive multi goals in decision-making processes that are more difficult to solve and push the decision-maker into a dilemma. This paper introduces an adaptive method based on the compromise programming approach to multi-objective optimization (MOP) in scheduling and planning (SP) problems. The proposed method gives an effective integration of mathematical programming with evolutionary algorithms (EA). Through the technique, decision-makers can validate the models as well as evaluate different decision alternatives. The method is in the development progress. However, we have obtained preliminary results by applying the method for solving some SP problems. These results show the feasibility of the proposed method. © 2021 ACM. Copyright held by the owner/author(s). Publication rights licensed to ACM.