| 摘要: |
| 利用混合细菌觅食算法(PO-BFA)求解整数规划问题,并与量子粒子群算法(QPSO)的求解结果进行对比。经过适当的参数设置混合细菌觅食算法可以有效地解决整数规划问题,在搜索过程中没有出现早熟现象,而且PO-BFA在求解整数规划问题上的整体性能比QPSO更优。 |
| 关键词: 细菌觅食算法 量子粒子群算法 整数规划 |
| DOI： |
| 投稿时间：2012-02-27修订日期：2012-07-20 |
| 基金项目:科学计算与智能信息处理广西高校重点实验室项目(GXSCIIP201204);广西教育厅科研基金项目(201106LX310,201204LX216)资助。 |
|
| Research of Hybrid Bacterial Foraging Algorithm for Integer Programming |
|
MAI Xiong-fa1,2, LI Ling3
|
| (1.School of Mathematical Sciences, Guangxi Teachers Education University, Nanning, Guangxi, 530023, China;2.Key Lab of Scientific Computing & Intelligent Information Processing in Universities of Guangxi, Nanning, Guangxi, 530023, China;3.School of Continuing Education, Guangxi Teachers Education University, Nanning, Guangxi, 530001, China) |
| Abstract: |
| The performance of the bacterial foraging algorithm combined with particle swarm optimization and opposition-based learning(PO-BFA) for integer programming was investigated. With the proper setting, the experimental results indicated that PO-BFA efficiently solved the problems of integer programming and converged faster than the QPSO algorithm in most cases. |
| Key words: bacterial foraging algorithm quantum-behaved particle swarm optimization integer programming |
