کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
496250 | 862854 | 2008 | 9 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: A hybrid genetic algorithm and particle swarm optimization for multimodal functions A hybrid genetic algorithm and particle swarm optimization for multimodal functions](/preview/png/496250.png)
Heuristic optimization provides a robust and efficient approach for solving complex real-world problems. The focus of this research is on a hybrid method combining two heuristic optimization techniques, genetic algorithms (GA) and particle swarm optimization (PSO), for the global optimization of multimodal functions. Denoted as GA-PSO, this hybrid technique incorporates concepts from GA and PSO and creates individuals in a new generation not only by crossover and mutation operations as found in GA but also by mechanisms of PSO. The results of various experimental studies using a suite of 17 multimodal test functions taken from the literature have demonstrated the superiority of the hybrid GA-PSO approach over the other four search techniques in terms of solution quality and convergence rates.
Journal: Applied Soft Computing - Volume 8, Issue 2, March 2008, Pages 849–857