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Solving Job-shop Scheduling Problem with an Ant Colony Optimization Algorithm Based on Mutation and Dynamic Pheromone Updating

Solving Job-shop Scheduling Problem with an Ant Colony Optimization Algorithm Based on Mutation and Dynamic Pheromone Updating
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摘要 The validity of the ant colony algorithm has been demonstrated as a powerful tool solving the optimization. An ant colony optimization algorithm based on mutation and dynamic pheromone updating in this paper was applied to settle job shop scheduling problem. Result of computer simulation shows that this method is effective.
作者 Jia Na
出处 《Journal of Systems Science and Information》 2006年第3期443-450,共8页 系统科学与信息学报(英文)
关键词 ant colony optimization job shop scheduling mutation algorithm 蚂蚁集群优化 作业调度 突变算法 信息素
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