The Evolutionary Multi-Objective Optimization Algorithm with Maximization of Personal Preference

For the problem that how to combine personal preference with the multi-objective optimization during the search procedure,an evolutionary multi-objective optimization algorithm which determines the search direction based on the maximization of personal preference is proposed.In the proposed algorithm,multi-objective problem is converted into a single objective problem by using the weighted-sum approach at first.After the conversion,genetic algorithm(GA) is used to search the feasible solution globally.Under the constraint of personal preference,the objective weights which make the synthetical finesses of the population own the biggest variance are calculated by solving a constraint optimization problem(COP).With maximization of personal preference,the optimal individual is selected exactly to execute the genetic operations.According to different preferences,the proposed algorithm is able to achieve the global optimal solution under the preference constraint.