CAJ | 학술논문

针对基本粒子群优化算法易陷入局部极值的缺陷，提出了一种细菌觅食机制粒子群优化算法。其基本思想是在粒子群优化算法中引入细菌觅食行为机制，提高PSO算法跳出局部极值的能力，借以改善PSO算法的寻优性能。采用标准测试函数的实验结果表明，该算法在收敛速度和求解精度方面均有显著改进。
침대기본입자군우화산법역함입국부겁치적결함，제출료일충세균멱식궤제입자군우화산법。기기본사상시재입자군우화산법중인입세균멱식행위궤제，제고PSO산법도출국부겁치적능력，차이개선PSO산법적심우성능。채용표준측시함수적실험결과표명，해산법재수렴속도화구해정도방면균유현저개진。
A novel particle swarm optimization algorithm based on bacterial foraging mechanism ( PSOBF ) is proposed for conventional particle swarm optimization algorithms ( PSO) often trapped in local optima.The basic idea is to introduce the bacterial foraging mechanism into particle swarm optimization algorithm to improve the ability of PSO algorithm.The experimental results of six benchmark functions demonstrate the efficacy of the present algorithm.