Improving the Performance of Heuristic Searches with Judicious Initial Point Selection

摘要：

In this paper we claim that local optimization can produce proper start point for genetic search. We completely test this claim on partitioning problem and on the performance of genetic search in a real problem that is finding aggregation tree in the sensor networks.The presented method (named Tendency algorithm) increases the performance of heuristic searches,and can be used in parallel with other tuning methods. The paper justifies the logic behind tendency algorithm by measuring the entropy of solution (in regard to optimal solution),and by numerous empirical tests.

作者: S.A.Tahaee A.H.Jahangir H.Habibi-Masouleh

作者单位: Computer Engineering Department Sharif University of Technology,Tehran,Iran

会议类型: 国际会议

会议名称: The Fifth IEEE International Symposium on Embedded Computing(SEC 2008)(第五届IEEE国际嵌入式系统计算会议)

会议地点: 北京

会议语种:英文

页码: 14-19

在线出版日期: 2008-10-06（万方平台首次上网日期，不代表论文的发表时间）