An Improved Hybrid Genetic Algorithms Using Simulated Annealing

摘要：

It is well known that simulated annealing (SA) and genetic algorithm (GA) are two global methods and can then be used to determine the optimal solution of NP-hard problem. In this paper, due to difficulty of obtaining the optimal solution in medium and large-scaled problems, a hybrid genetic algorithm (HGA) was also developed. The proposed HGA incorporates simulated annealing into a basic genetic algorithm that enables the algorithm to perform genetic search over the subspace of local optima. The two proposed solution methods were compared on Rosenbrock function global optimal problems, and computational results suggest that the HGA algorithm have good ability of solving the problem and the performance of HGA is very promising because it is able to find an optimal or near-optimal solution for the test problems.

关键词： Hybrid Genetic Algorithms Simulated Annealing global optimal

作者: Shi Huawang

作者单位: School of Civil Engineering Hebei University of Engineering Handan, P.R.China

会议类型: 国际会议

会议名称: Second International Symposium on Electronic Commerce and Security(第二届电子商务与安全国际研究大会)(ISECS 2009)

会议地点: 南昌

会议语种:英文

页码: 462-465

在线出版日期: 2009-05-22（万方平台首次上网日期，不代表论文的发表时间）