A Multi-objective Genetic Algorithm Based on Nearest Neighbor Method

Aiming at the practical engineering problems, when the multi-objective problem known a few of the optimization solutions, often need to be in a region search the relatively dense Pareto solution set for problems. This paper puts forward a multi-objective genetic algorithm based on the nearest neighbor method, the optimal solution of the known information added to the initial sample space, use the nearest neighbor method to identify individual belongs evolution Pareto dominant set, guide evolution direction. Simulation results show that the algorithm in the particular area showed very good local search ability, and can search for a scattered distribution of Pareto optimal solution subset.