Multi-objective Evolutionary Algorithm Based on Neighborhood List

To balance the performance of algorithm and running time,this paper proposes a multi-objective evolutionary algorithm based on neighborhood list whose structure is similar with that of adjacent list in graph theory.Considering the crowding degree and distance,this measure assigns diversity fitness by the neighboring relation of solutions,and adjusts the list by fitness to select the environment efficient.By examining three performance metrics on seven test problems,the new algorithm can converge to the true Pareto front fast,and has a good distribution at the same time.