求解大规模约束tsp的自利基因容忍度通用算法

2006 IEEE International Conference on Information Reuse & Integration Pub Date : 2006-12-04 DOI:10.1109/IRI.2006.252405

Yoshitaka Sakurai, T. Onoyama, S. Kubota, Yoshihiro Nakamura, S. Tsuruta

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引用次数: 0

摘要

适用于供应链管理的大规模分销网络仿真要求在交互响应时间内求解数百个具有时间约束的大规模(最多2000个城市)旅行商问题(TSP)，并具有切实可行的最优性。为了满足这一要求，提出了一种自私基因耐受型遗传算法。在这里，个体的每个基因只自私地满足自己的约束，而不考虑同一个体中其他基因的约束。进一步说，在某种程度上，即使是违反约束的个体也可以存活几代，并获得改进的机会。实验证明，该方法可以在几秒内为时间约束的大规模tsp提供专家级的解决方案

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Selfish-gene Tolerant Generic Algorithms to solve large-scale constraint TSPs

Large-scale distribution network simulation applicable to supply-chain management requires to solve hundreds of time-constraint large-scale (max 2000 cities) traveling salesman problems (TSP) within interactive response time, with practicable optimality. To meet this requirement, a selfish-gene tolerant type GA is proposed. Here, each gene of an individual satisfies only its constraints selfishly, disregarding the constraints of other genes in the same individual Further, to some extent, even individuals that violate constraints can survive over generations and are given the chance of improvement. Our experiment proves that this method provides expert-level solutions for time constraint large-scale TSPs within a few seconds

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2006 IEEE International Conference on Information Reuse & Integration

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