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《Computer Engineering and Applications》 2005-08
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An Improved Partheno Evolution Genetic Algorithm on the Shortest Route Problem

Zhu Yanjun Hu Chunde Gao Suixiang(Graduate School of the Chinese Academy of Sciences,Beijing 100039)  
Because DACO(ant colony optimization based on dynamic pheromone updating) algorithm costs too much time in order to find an optimal solution in solving the Shortest Route Problem for large-scaled optimization,and PEGA(partheno-evolution genetic algorithm) is too highly optional in producing primal group,choosing father-body,gene exchange operator,this article combines the two algorithms and puts forth the PEGA based on DACO.Through controlling covering times of ant colony,it firstly attains better solution,and secondly improves the attained solution as primal group to come at the best solution.The experiments demonstrate that the proposed algorithm is very effective in solving the Shortest Route Problem.
【Fund】: 国家自然科学基金资助(编号:10171095);; 国家863高技术研究发展计划项目(编号:2002AA103061)
【CateGory Index】: TP18
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