| 基于混沌的生物地理分布优化算法 |
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| 引用本文： | 张萍,魏平,于鸿洋,费春.基于混沌的生物地理分布优化算法[J].电子科技大学学报（自然科学版）,2012,41(1):65-69. |
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| 作者姓名： | 张萍 魏平 于鸿洋 费春 |
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| 作者单位： | 1.电子科技大学电子工程学院 成都 611731; |
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| 基金项目： | 中央高校基本科研业务费(ZYGX2009J024) |
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| 摘 要： | 生物地理分布优化算法(BBO)是一种新型的智能优化算法,其寻优能力优于以往的智能优化算法,但同样存在早熟收敛的缺陷。针对该问题,提出了基于混沌的生物地理分布优化算法(CSBBO)。该算法首先利用分段混沌映射产生初始种群,再根据BBO算法进行全局搜索得到当前最优解,最后以该解为基础进行混沌搜索得到全局最优解。仿真测试表明,该算法的收敛速度和寻优精度均优于BBO算法和以往智能优化算法。
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| 关 键 词： | 生物地理分布优化 全局优化 智能计算 分段混沌映射 |
| 收稿时间： | 2010-12-14 |
Biogeography-Based Optimization Algorithm by Using Chaotic Search |
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| Affiliation: | 1.School of Electronic Engineer,University of Electronic Science and Technology of China Chengdu 611731;2.School of Computer Science & Engineering,University of Electronic Science and Technology of China Chengdu 611731 |
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| Abstract: | Biogeography-based optimization (BBO) is a new intelligent optimization algorithm, which has better search efficiency than the previous intelligent optimization algorithms, but it also has premature convergence. To solve this problem, biogeography-based optimization algorithm by suing chaotic search (CSBBO) is proposed. Firstly initial populations are generated based on piecewise chaotic map, then BBO global search algorithm is used to get the current optimal solution, finally the global optimum is obtained by using chaotic search. Simulation results show that CSBBO outperforms BBO and previous intelligent optimization algorithms in terms of convergence rate and search precision. |
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