An Improved Greedy Genetic Algorithm for Solving Travelling Salesman Problem

An Improved Greedy Genetic Algorithm for Solving Travelling Salesman Problem
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DOI：
10.1109/icnc.2009.504
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发表时间：
2009-08
期刊：
2009 Fifth International Conference on Natural Computation
影响因子：
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通讯作者：
Zhenchao Wang;H. Duan;Xiangyin Zhang
Zhenchao Wang;H. Duan;Xiangyin Zhang
中科院分区：
其他
文献类型：
--
作者：
Zhenchao Wang;H. Duan;Xiangyin Zhang

文献摘要

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Genetic algorithm (GA) is too dependent on the initial population and a lack of local search ability. In this paper, an improved greedy genetic algorithm (IGAA) is proposed to overcome the above-mentioned limitations. This novel type of greedy genetic algorithm is based on the base point, which can generate good initial population, and combine with hybrid algorithms to get the optimal solution. The proposed algorithm is tested with the Traveling Salesman Problem (TSP), and the experimental results demonstrate that the proposed algorithm is a feasible and effective algorithm in solving complex optimization problems.