基于新约束集成的差分进化算法

Differential Evolutionary Algorithm Based on New Ensemble of Constraint Handing Techniques

提出基于新约束集成的差分进化算法用于求解带约束的优化问题.在产生新个体的阶段,算法采用3种不同的突变策略.利用不同的约束处理技术对新个体进行选择,并通过引入局部搜索,增强算法局部寻优能力,避免算法陷入局部最优.该算法在CEC 2017的28个基准函数上进行数值实验,并且与其他较为先进的算法进行比较,实验结果显示,新算法在求解精度上表现较好.

In this paper,a differential evolutionary algorithm based on new ensemble of constraint handing techniques is proposed to solve optimization problems with constraints. At the stage of generating new individuals,the algorithm adopts three different mutation strategies. Different constraint handing techniques are used to select new individuals,and local search is introduced to enhance the local optimization ability and avoid the algorithm falling into local optimum. Numerical experiments are carried out on 28 benchmark functions from CEC 2017 and compared with other advanced algorithms. The results show that the new algorithm performs better in solution accuracy.