改进交叉算子的自适应人工蜂群黏菌算法

Adaptive Artificial Bee Colony Slime Mold Algorithm with Improved Crossover Operator

针对黏菌算法存在的收敛速度慢,易陷入局部最小值的问题,提出了一种改进交叉算子的自适应人工蜂群黏菌算法(ISMA).为了提高算法收敛速度,引入自适应可调节的反馈因子和改进的交叉算子;考虑到人工蜂群算法强大的搜索能力,引入改进的人工蜂群搜索策略,提高算法跳出局部最小值的能力.利用8个标准测试函数以及部分CEC2014测试函数对改进算法进行寻优性能测试,并加入基准测试函数的Wilcoxon秩和统计检测,仿真结果表明,改进的算法具有很好的鲁棒性.

In order to solve the problems of slow convergence speed and easy to fall into local minimum value,an adaptive artificial bee colony slime mold algorithm(ISMA)with improved crossover operator was proposed.In order to improve the convergence speed of the algorithm,an adaptive and adjustable feedback factor and an improved crossover operator are introduced.Considering the strong searching ability of artificial bee colony algorithm,an improved artificial bee colony searching strategy is introduced to improve the ability of the algorithm to jump out of the local minimum value.Eight standard test functions and some CEC2014 test functions were used to test the optimization performance of the improved algorithm,and Wilcoxon rank sum of the benchmark function was added to test the performance.The simulation results show that the improved algorithm has good robustness.