针对混合蛙跳算法在寻优过程中出现的早熟收敛问题,利用混沌技术的遍历性优势对子群最优个体进行变异操作,形成局部精细搜索策略;根据蛙群相对多样性参数来判断算法是否陷入局部最优,进而对蛙群最优个体进行扰动以提高全局寻优能力,形成全局激励调节策略。耦合2种策略,提出了一种改进混合蛙跳算法。将其应用于李仙江梯级水库优化调度中,结果表明所提算法具有寻优质量高、收敛速度快的特点,有效地克服了标准混合蛙跳算法的早熟缺陷,为水库调度模型的求解提供了一种新方法。
Abstract
In view of the premature convergence in shuffled frog leaping algorithm (SFLA), an improved shuffled frog leaping algorithm (AISFLA) is proposed by coupling the local refine search strategy (LRSS) with the global incentive regulation strategy (GIRS). LRSS improves the local search ability by using chaos technology to conduct more refined search around the optimal individual of each group, while GIRS keeps an efficient global search performance by disturbing the optimum individual to improve the frogs’ population diversity and further motivate frogs jumping out of stable state. AISFLA is applied to the optimal operation of Lixianjiang cascade reservoirs as a demonstration. The modeling result proves that AISFLA is of high optimization quality and fast convergence by effectively handling the premature convergence of SFLA, hence can be a new approach to the solution of optimal operation of cascade reservoirs.
关键词
梯级水库 /
优化调度 /
混合蛙跳算法 /
局部精细搜索 /
全局激励调节 /
耦合改进机制
Key words
cascade reservoirs /
optimal operation /
shuffled frog leaping algorithm /
local refine search strategy /
global incentive regulation strategy /
coupling improvement mechanism
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参考文献
[1] 王本德, 周惠成, 卢 迪. 我国水库(群)调度理论方法研究应用现状与展望. 水利学报, 2016, 47(3): 337-345.
[2]JI Chang-ming, JIANG Zhi-qiang, SUN Ping, et al. Research and Application of Multidimensional Dynamic Programming in Cascade Reservoirs Based on Multilayer Nested Structure. Journal of Water Resource Planning and Management, 2015, 141(7): 1-13.
[3]王 成, 曹庆磊. 水库运行管理中优化调度的计算机算法研究. raybet体育在线
院报, 2011, 28(1): 66-70.
[4]王 森,马志鹏,李善综,等.粗粒度并行自适应混合粒子群算法及其在梯级水库群优化调度中的应用. raybet体育在线
院报, 2017, 34(7): 149-154.
[5]陈 端, 陈求稳, 陈 进. 基于改进遗传算法的生态友好型水库调度. raybet体育在线
院报, 2012, 29(3): 1-6,12.
[6]黄 锋, 王丽萍, 向腾飞, 等.基于混沌人工鱼群算法的水库发电优化调度研究. 中国农村水利水电, 2014, (10): 149-153.
[7]EUSUFF M, LANSEY K, PASHA F. Shuffled Frog-leaping Algorithm: A Memetic Meta-heuristic for Discrete Optimization. Engineering Optimization, 2006, 38(2): 129-154.
[8]KAUR P, MEHTA S. Resource Provisioning and Work Flow Scheduling in Clouds Using Augmented Shuffled Frog Leaping Algorithm. Journal of Parallel and Distributed Computing, 2017, 101: 41-50.
[9]SAMUEL G G, ASIR RAJAN C C. Hybrid: Particle Swarm Optimization-Genetic Algorithm and Particle Swarm Optimization-Shuffled Frog Leaping Algorithm for Long-term Generator Maintenance Scheduling. International Journal of Electrical Power & Energy Systems, 2015, 65: 432-442.
[10]王丽萍, 孙 平, 蒋志强, 等. 基于并行云变异蛙跳算法的梯级水库优化调度研究. 系统工程理论与实践, 2015, 35(3): 790-798.
[11]罗雪晖, 杨 烨, 李 霞. 改进混合蛙跳算法求解旅行商问题. 通信学报, 2009, 30(7): 130-135.
[12]阳春华, 钱晓山, 桂卫华. 一种混沌差分进化和粒子群优化混合算法. 计算机应用研究, 2011, 28(2): 439-441.
[13]易文周, 田立伟. 一种基于混沌搜索和鲶鱼效应策略的粒子群算法. 计算机应用与软件, 2013, 30(5): 311-315.
[14]姜 伟, 王宏力, 何 星, 等. 并行免疫离散粒子群优化算法求解背包问题. 系统仿真学报, 2014, 26(1): 56-61.
[15]纪昌明, 刘 方, 彭 杨, 等. 基于鲶鱼效应粒子群算法的水库水沙调度模型研究. 水力发电学报, 2013, 32(1):70-76.
[16]金荣洪, 袁智皓, 耿军平, 等. 基于改进粒子群算法的天线方向图综合技术. 电波科学学报,2006, 21(6): 873-878.
基金
国家自然科学基金项目(51279062,51509001);“十三五”国家重点研发计划课题(2016YFC0402208);中央高校基本科研业务费专项(2016MS51,2016XS58)
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