J4

• 计算机科学 • 上一篇    下一篇

噪声环境下函数优化问题的混合优化算法

岳 娜, 欧阳丹彤, 张长胜, 刘玉玺   

  1. 吉林大学 计算机科学与技术学院, 长春 130012; 吉林大学 符号计算与知识工程教育部重点实验室, 长春 130012
  • 收稿日期:2008-01-17 修回日期:1900-01-01 出版日期:2008-09-26 发布日期:2008-09-26
  • 通讯作者: 欧阳丹彤

A Hybrid Optimization Algorithm for Function Optimizationin Noisy Environment

YUE Na, OUYANG Dantong, ZHANG Changsheng, LIU Yuxi   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012, China; Key Laboratory of Symbol Computation and Knowledge Engineer of Ministry of Education, Jilin University, Changchun 130012, China
  • Received:2008-01-17 Revised:1900-01-01 Online:2008-09-26 Published:2008-09-26
  • Contact: OUYANG Dantong

摘要: 针对噪声环境下的函数优化问题提出一种混合粒子群优化算法UPSOOHT, 并考察了最优计算量分配(OCBA)和噪声幅度对算法性能的影响. 该算法将粒子群优化算法与假设检验及OCBA有效地结合, 具有很好的全局搜索能力和局部精化能力. 与其他优化算法比较的测试结果表明, UPSOOHT算法的性能和抗噪声能力都具有明显的优势.

关键词: 粒子群优化算法, 噪声环境, 函数优化, 混合优化算法

Abstract: A hybrid algorithm was proposed to solve function optimization problems in noisy environment which combined the Unified Particle Swarm Optimization Scheme, hypothesis test and optimal computing budget allocation technique together. The algorithm has good abilities of exploration and exploitation. Numerical simulations based on several representative benchmark problems were carried out in noisy environment and a comparison was made between UPSOOHT and several popular algorithms. Additionally, the influences of OCBA and noise magnitude were studied. The results show that UPSOOHT has a better performance.

Key words: unified particle swarm optimization, noisy environment, function optimization, hybrid optimization algorithm

中图分类号: 

  • TP18