Multi-objective Optimization Algorithm Embedded by User Preference Region
Aiming at the problem of the existing multi-objective optimization methodologies in actual application, this paper proposes a multi-objective optimization algorithm based on user preference region, which only finds a preferred and smaller set of Pareto-optimal solutions, instead of the entire Pareto frontier, so that the number of solutions is reduced and the convergence rate is improved. The algorithm adopts the elitist non-dominated sorting strategy, takes the distance between individual and the user preference region as a factor affecting individuals fitness, and applies the crowding strategy to maintain the diversity of solution. Simulation results show that the proposed algorithm is effective.