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学习型和声搜索算法及其在0-1 背包问题中的应用
引用本文:李若平,欧阳海滨,高立群,邹德旋.学习型和声搜索算法及其在0-1 背包问题中的应用[J].控制与决策,2013,28(2):205-210.
作者姓名:李若平  欧阳海滨  高立群  邹德旋
作者单位:1. 东北大学信息科学与工程学院,沈阳110819
2. 徐州师范大学电气工程及自动化学院,江苏徐州221116
基金项目:国家自然科学基金项目(60674021)
摘    要:针对现有和声搜索算法存在的不足,提出一种学习型和声搜索算法(LHS).根据目标函数值的变化,自适应调整和声记忆考虑概率(HMCR);引入学习机制,加快算法的搜索速度;动态调节基音调整概率(PAR),增强算法的全局搜索能力.对16个标准函数的测试结果表明,所提出的LHS算法与其他4种和声搜索算法相比具有较好的效果.最后将改进算法应用于10个0-1背包问题和1个经典的50维背包实例,实验结果表明LHS算法优于其他算法.关键词:和声搜索算法;自适应;学习策略;搜索速度;0-1背包问题

关 键 词:和声搜索算法  自适应  学习策略  搜索速度  0-1背包问题
收稿时间:2012/1/10 0:00:00
修稿时间:2012/3/28 0:00:00

Learned harmony search algorithm and its application to 0-1 knapsack
LI Ruo-ping,OUYANG Hai-bin,GAO Li-qun,ZOU De-xuan.Learned harmony search algorithm and its application to 0-1 knapsack[J].Control and Decision,2013,28(2):205-210.
Authors:LI Ruo-ping  OUYANG Hai-bin  GAO Li-qun  ZOU De-xuan
Affiliation:1.College of Information Science and Engineering,Northeastern University,Shenyang 110819,China;2.School of Electrical Engineering and Automation,Xuzhou Normal University,Xuzhou 221116,China.)
Abstract:For the purpose of avoiding the disadvantage of harmony search algorithm, a learned harmony search(LHS)
algorithm is proposed. The adaptive parameter harmony memory consideration rate(HMCR) is designed based on the change
of objective function value and the learning strategy is used to accelerate the speed of search. Then pitch adjustment rate(PAR)
is adjusted dynamically to enhance the global search. The 16 classic test functions are tested, and the results show that LHS
algorithm outperforms the other four harmony search algorithms. Finally, LHS algorithm is applied to 10 0-1 knapsack
problems and a classic knapsack example, and the result shows that LHS algorithm is better than other algorithms.
Keywords:harmony search algorithm  adaptive  learning strategy  search speed  0-1 knapsack problem
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