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Received:October 17, 2014 Revised:November 28, 2014
Received:October 17, 2014 Revised:November 28, 2014
中文摘要: 针对一种混合遗传算法所采用的贪心变换法的不足, 给出了一种改进的贪心修正法; 并基于稳态复制的策略, 对遗传算法的选择操作进行改进, 给出了随机选择操作. 在此基础上, 提出了一种改进的混合遗传算法, 并将新算法用于解决大规模的0-1背包问题, 通过实例将新算法与HGA算法进行实验对比分析, 并研究了变异概率对新算法性能的影响. 实验结果表明新算法收敛速度快, 寻优能力强.
Abstract:An improved greedy correction method is advanced for overcome the flaw of greedy transform method adopted by hybrid genetic algorithm (HGA). And based on steady state reproduction strategy, the choice method of random selection is advanced. These new methods are combined with genetic algorithm to propose a high-efficient hybrid genetic algorithm (IHGA), and new algorithm was used to solve large-scale 0-1 knapsack problem. By many simulation experiments, IHGA algorithm is compared with HGA algorithm, and how the mutation probability affect the performance of the new algorithm has been studied. The experimental results show that the new algorithm has higher convergent speed and better optimization capability.
keywords: hybrid genetic algorithm 0-1 knapsack problem greedy transform random selection greedy correction
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基金项目:郑州市重点实验室资助项目(121PYFZX177)
引用文本:
刘寒冰,张亚娟.求解0-1背包问题的改进混合遗传算法.计算机系统应用,2015,24(6):197-201
LIU Han-Bing,ZHANG Ya-Juan.Improved Hybrid Genetic Algorithm for Solving 0-1 Knapsack Problem.COMPUTER SYSTEMS APPLICATIONS,2015,24(6):197-201
刘寒冰,张亚娟.求解0-1背包问题的改进混合遗传算法.计算机系统应用,2015,24(6):197-201
LIU Han-Bing,ZHANG Ya-Juan.Improved Hybrid Genetic Algorithm for Solving 0-1 Knapsack Problem.COMPUTER SYSTEMS APPLICATIONS,2015,24(6):197-201