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ACO Algorithms for the Scheduling Mixed-model Assembly Lines

机译:混合模型装配线调度的ACO算法

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摘要

Solving the mixed-model scheduling problem is the most important goal for Just-in-time production systems. The main desirable characteristics of ant algorithm are versatile, robust and parallel searching. This paper presents a novel co-operative agents approach, ant colony optimization algorithm (ACO) scheme, for solving the scheduling mixed-model assembly lines. The results show that the solution which ant algorithm produces is better than the one Toyota's Goal Chasing Algorithm, Simulated annealing algorithm and GA.
机译:解决混合模型调度问题是即时生产系统的最重要目标。蚂蚁算法的主要特点是通用,鲁棒和并行搜索。本文提出了一种新型的合作代理方法,蚁群优化算法(ACO)方案,用于解决混合模型装配线的调度问题。结果表明,蚂蚁算法产生的解决方案优于丰田的目标追逐算法,模拟退火算法和遗传算法。

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