A novel method for maintaining the diversity in evolutionary multiobjective optimization
一种新的分布性保持方法

Maintaining the diversity of solutions is a crucial part in multi-objective optimization. However, there has to be a trade-off between the diversity and the execution time. A method for maintaining the diversity using a minimum spanning tree is proposed. By estimating the individual density based on the degree and edge of the minimum spanning tree, we preserve the low-degree boundary individuals and the longer-edge-low-density individuals. Moreover, by this onetime selection, the adjustment of individual density after removing each individual can be avoided. Through the extensive comparison study with three other classical methods on four performance metrics in five test problems, it is observed that the proposed method has a good performance in diversity and execution time.