Preference-Based Multi-objective Optimization Algorithms Under the Union Mechanisms
摘要
Preference multi-objective optimization (PMOP) is hot problem in the field of current optimization. The searching objection of the PMOP which is local target pareto region according to preference information different from general multi-objective optimization. To improve the performance of the PMOP, a new Preference-based multi-objective optimization algorithms under the union mechanisms (UM-NSGAII) is proposed. Two strategies are proposed in UM-NSGAII. Firstly, initial population generated from limiting it to a certain range, which can reap a population dominated by preference information.Mutation individual is also come into being a certain range, which can reap progeny of populations closer to the pareto frontier corresponding to preference information. Secondly, Angle preference strategy is to identify the angle formed by a certain point with an arbitrary point and the origin as an angle preference region, where individuals in this region are selected in preference to individuals outside the region, this allows individuals evolving towards the target pareto region to be retained, facilitating rapid optimization searching.