基于L支配的高维多目标人工蜂群算法

onsidering many objectives optimization problems can't be solved by Artificial Bee Colony Algorithm, a many objectives artificial bee colony algorithm based on pareto optimization and L-Optimality has been proposed in this paper. Many objectives optimization problems are transformed into single objective optimization problem by an improved fitness value evaluation method by L-Optimality. The results tested on the standard DTLZ function show that the proposed method can converge to the optimal non-dominated front, compared with the MDMOEA method, and have the less calculation and fast convergence speed. Many objectives optimization problems have been solved effectively.