首页> 外文会议>2009 International Symposium on Computer Science and Technology(2009 中国宁波国际计算机科学与技术学术大会) >IMPROVED METHOD OF GA'S INITIATION POPULATION BASED ON LOCAL-EFFECTIVE-INFORMATION FOR SOLVING TSP
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IMPROVED METHOD OF GA'S INITIATION POPULATION BASED ON LOCAL-EFFECTIVE-INFORMATION FOR SOLVING TSP

机译:基于局部有效信息的遗传算法初始种群求解TSP的改进方法

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Genetic Algorithm (GA) is restricted by actual system computing ability.Because of the limited number of population and iteration, the choice of initiation Population is a vital of fact,which directly influents the result of algorithm and the efficiency.GA's Initiation Population is created by the path of well-proportioned choosing seed or stochastic choosing seed generally,but both of them have a vice of inefficient search.The paper, combining with interrelated theories in graph theory,brings forward two kinds of Optimization Algorithms of Initiation Population based on Minimize Spanning Tree Local Effective Information Theory towards the limitations of them, and we successes it to TSP by example analysis.
机译:遗传算法(GA)受实际系统计算能力的限制。由于种群数量和迭代次数的限制,初始种群的选择是至关重要的,它直接影响算法的结果和效率。一般采用均衡选择种子或随机选择种子的路径,但两者都有效率低下的弊端。本文结合图论相关理论,提出了两种基于最小化的初始种群优化算法。生成树局部有效信息论克服了它们的局限性,我们通过实例分析将其成功应用于TSP。

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