An interactive preference-based evolutionary algorithm for multi-criteria satisficing optimization

An interactive preference-based evolutionary algorithm is proposed to solve multi-criteria satisfactory optimization problems. Using the proposed method, Decision Makers (DMs) can easily obtain the preferred parts of the actual Pareto front. Based on the satisfactory theory, the feasible region is constructed to evaluate the obtained candidates in terms of satisfactory degree. Furthermore, optimal weights are generated by minimizing the weighted l(p)-norm of the conflicting satisfactory and unsatisfying candidates, to form the evaluation function by which the next generation would evolve towards the preferred optimization solutions. The layout optimization of a retrievable satellite module is used to verify the effectiveness of proposed method.