CAJ | 학술논문

为了提高引力搜索算法（gravitational search algorithm，GSA）在处理单目标优化问题上的综合能力，提出了一种基于混合改进策略的 GSA。依照种群个体自身的进化情况，提出个体进化率的进化策略，以提高算法的收敛速度；采取方向性的变异策略，较好地平衡了全局搜索能力和局部开采能力，最大限度地降低了种群陷入局部最优的可能。基于标准测试函数的仿真实验表明，基于混合策略的 GSA 算法可有效避免早熟收敛，在收敛精度和收敛速度上与标准的 GSA 算法以及相应的改进算法相比有显著提高。
위료제고인력수색산법（gravitational search algorithm，GSA）재처리단목표우화문제상적종합능력，제출료일충기우혼합개진책략적 GSA。의조충군개체자신적진화정황，제출개체진화솔적진화책략，이제고산법적수렴속도；채취방향성적변이책략，교호지평형료전국수색능력화국부개채능력，최대한도지강저료충군함입국부최우적가능。기우표준측시함수적방진실험표명，기우혼합책략적 GSA 산법가유효피면조숙수렴，재수렴정도화수렴속도상여표준적 GSA 산법이급상응적개진산법상비유현저제고。
In order to improve the performance of the gravitational search algorithm (GSA)in solving single objective optimization problems,a new GSA with mixed improved strategy is proposed.According to the evolu-tion situation,the individual evolution rate strategy is proposed which is applied to enhance the rate of conver-gence.And a kind of variation strategy is adopted to balance the ability of global searching and local exploiting which avoid the possibility that the population fall into local optimum.Simulation experimental results on benchmark functions show that the GSA with mixed strategy has a good performance in avoiding premature con-vergence.Compared with GSA and other improved GSA,the new algorithm has a good performance not only in convergence rate but also in convergence precision.