| 梯级水库发电优化调度的改进细菌觅食算法研究 |
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| 引用本文： | 陈志强.梯级水库发电优化调度的改进细菌觅食算法研究[J].大众科技,2014(7):47-50. |
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| 作者姓名： | 陈志强 |
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| 作者单位： | 广东省水文局阳江测报中心,广东江门509030 |
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| 摘 要： | 细菌觅食算法在求解水库优化调度问题时,以固定的步长进行趋向操作,同时以固定概率对细菌个体进行随机驱散操作,虽然可以一定程度上增加种群多样性,但是在进化后期容易使优秀的个体流失,影响算法的寻优质量。针对该问题,文章提出步长自适应调整和驱散概率自适应调整两项改进策略,根据算法进化程度和细菌个体的能量值动态调整趋向操作的步长和驱散操作的概率,使算法进化过程中尽量保证种群多样性的基础上,提高细菌个体的觅食能力,进一步促进算法达到局部搜索和全局优化之间的平衡。将改进的细菌觅食算法应用于乌江梯级水库群的联合优化调度问题,模拟结果表明:改进细菌觅食算法具有较强的全局寻优能力,适合求解梯级水库联合优化调度问题。
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| 关 键 词： | 优化问题 细菌觅食算法 自适应 |
Self-adaptive bacterial foraging algorithm and its application to optimization problems |
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| Abstract: | The search procedure is performed in a fixed step length and the random dispersal is processed in a fixed frequency when applying bacterial foraging algorithm in optimization problems. Diversity of population can be increased through the traditional algorithm; however, efficiency of the algorithm is compromised for possible loss of samples in later period. Two improvements, including the self-adaption of the search step length and dispersal probabihty according to the evolution level and the energy value of bacteria, are proposed in this study. The improvements are mainly aimed at enhancing the balance between local search and global optimization while keeping the diversity of populations. The proposed algorithm has been applied on the standard test function and TSP problem, and the results indicate that the algorithm is suited for complex high dimensional optimization problems with better global search capabihty. |
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| Keywords: | Optimization problems bacterial foraging algorithm self-adaptive |
| 本文献已被 CNKI 维普 等数据库收录！ |
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