A Novel Parallel Interval Ezclusion Algorithm

摘要：

The optimization algorithm based on interval analysis is a deterministic global optimization algorithm. However, Solving high-dimensional problems, traditional interval algorithm exposed lots of problems such as consumption of time and memory. In this paper, we give a parallel interval global optimization algorithm based on evolutionary computation. It combines the reliability of interval algorithm with the intelligence and nature scalability of mind evolution computation algorithm, effectively overcomes the shortcomings of TimeConsuming and Memory-Consuming of the traditional interval algorithm. Numerical experiments show that the algorithm has much high efficiency than the traditional interval algorithm.

作者: Yongmei Lei Shaojun Chen Yu Yan

作者单位: School of Computer Engineering and Science, Shanghai University, Shanghai 200072, China

会议类型: 国际会议

会议名称: The Second International Conference on High Performance Computing and Applications(第二届高性能计算及应用国际会议)

会议地点: 上海

会议语种:英文

页码: 218-223

在线出版日期: 2009-08-10（万方平台首次上网日期，不代表论文的发表时间）