针对非均匀问题的多目标进化算法

A Multi-Objective Evolutionary Algorithm for Non-uniform Problem

文章针对解集分布非均匀的问题,提出了一种新的多目标进化算法,称之为GNEA(带小生境的网格进化算法)。在算法中,针对分均匀问题的特点,采用了小生境技术来保持解集的局部非均匀分布,以及网格技术来保证整个解集的分布度。为了让GNEA运行效率更高,提出了用庄家法构造非支配集的方法。最后通过与其他算法进行比较,验证了算法具有较好的运行效率,且在解决非均匀问题上是一种有效的多目标进化算法。

In this paper,a grids technique based on niching evolutionary algorithm for multi-objective optimization （GNEA） is proposed,which aims to solve non-uniform problems,GNEA applies niche technique to keep the non-uniform distribution of local solutions,and grid division to maintain diversity of the globe solutions,To make GNEA more efficient,we propose to construct the non-dominated set with the Dealer＇s Principle, We compare our GNEA with two popular MOEAs,and it is validated by experiment that the algorithm has well-distributed set of Pareto-Optimal Solutions in a small computational time and it can be adapted to non-uniform problems.