[1]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,2014,16(07):47-50.
　Self-adaptive bacterial foraging algorithm and its application to optimization problems[J].Popular Science & Technology,2014,16(07):47-50.
点击复制

梯级水库发电优化调度的改进细菌觅食算法研究()
分享到：

《大众科技》[ISSN:1008-1151/CN:45-1235/N]

卷:
第16卷
期数:
2014年07期
页码:
47-50
栏目:
资源与环境
出版日期:
2014-12-27

文章信息/Info

Title:
Self-adaptive bacterial foraging algorithm and its application to optimization problems
文章编号:
1008-1151(2014)07-0047-04
作者:
陈志强
广东省水文局阳江测报中心，广东 江门 509030
关键词:
优化问题; 细菌觅食算法; 自适应
Keywords:
Optimization problems;  bacterial foraging algorithm;  self-adaptive
分类号:
P33
文献标志码:
A
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。
Abstract:
The search procedure is performed in a fixed step length and the random dispersal is processed in a fixed frequency whenapplying 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 theself-adaption of the search step length and dispersal probability according to the evolution level and the energy value of bacteria, areproposed in this study. The improvements are mainly aimed at enhancing the balance between local search and global optimization whilekeeping the diversity of populations. The proposed algorithm has been applied on the standard test function and TSP problem, and theresults indicate that the algorithm is suited for complex high dimensional optimization problems with better global search capability

参考文献/References:

[1] 梅亚东,熊莹,陈立华.梯级水库综合利用调度的动态规划方法研究[J].水力发电学报,2007,26(2):1-4.[2] 李崇浩,纪昌明,缪益平.基于微粒群算法的梯级水电厂短期优化调度研究[J].水力发电学报,2006,25(2):94-98.[3] 马光文,王黎.遗传算法在水电站优化调度中的应用[J].水科学进展,1997,8(3):275-280.[4] 郑慧涛,梅亚东,胡挺,等. 双层交互混合差分进化算法在水库群优化调度中的应用[J].水力发电学报,2013,2(1):54-62.[5] Dong Hwa Kim,Ajith Abraham,Jae Hoon Cho. A hybridgenetic algorithm and bacterial foraging approach for globaloptimization[J]. Information Sciences,2007,177: 3918-3937.[6] Swagatam Das,Arijit Biswas,Sambarta Dasgupta. BacterialForaging optimization algorithm: theoretical foundations,analysis,and applications[J].Foundations of Computer,2009,3:23-55.[7] 王雪松,程玉虎,郝名林.基于细菌觅食行为的分布估计算法在预测控制中的应用[J].电子学报,2010,(2):333-339.[8] 马溪原,吴耀文,方华亮,孙元章.采用改进细菌觅食算法的风/光/储混合微电网电源优化配置[J].中国电机工程学报,2011,31(25):17-25.[9] 李丹,唐普英.基于细菌觅食的盲源分离算法研究[J].通信技术,2011,44(12):150-152.[10] 崔静静,孙延明,车兰秀.改进细菌觅食算法求解车间作业调度问题[J].计算机应用研究,2011,28(9):3324-3326.[11] 李珺,党建武,卜锋.自适应步长的细菌觅食优化算法研究[J].兰州交通大学学报,2013,32(6):10-14.

备注/Memo

备注/Memo:
【收稿日期】2014-06-13【作者简介】陈志强（1963－），男，广东江门人，广东省水文局阳江测报中心工程师，从事水文计算分析、水资源勘测评价等工作。
更新日期/Last Update: 2016-02-29