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A New Contribution for Solving Dynamic Scheduling Problems Using a Tabu Search

机译:使用禁忌搜索解决动态调度问题的新贡献

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Many real-world optimisation problems are eventually dynamic. New jobs are to be added to the schedule, the quality of the raw material may be changing, new orders have to be included into the problem etc. In such cases, when the problem changes over the course of the optimisation, the purpose of the optimisation algorithm changes from finding an optimal solution to being able to continuously track the movement of the optimum through time. This paper starts by presenting a new scheduling method based on Tabu Search for the resolution of the dynamic Job-Shop Scheduling Problem, which considers job release times, job due dates and different assembly levels (parallel operations). This framework is based on a decomposition of the Job-Shop Scheduling Problem into a series of deterministic Single Machine Scheduling Problem (SMSP) and on a Tabu Search Algorithm, which solves each SMSP whose solutions are, then, integrated. An inter-machine activity coordination mechanism is described. Finally, the used approach adapts the resolution of the deterministic problem to the non-deterministic one in which changes may occur continually. This takes into account dynamic occurrences in a manufacturing system and adapts the current neighbourhood to a new regenerated neighbourhood.
机译:许多现实世界中的优化问题最终都是动态的。新工作将添加到计划中,原材料的质量可能会发生变化,新订单必须包含在问题中,等等。在这种情况下,当问题在优化过程中发生变化时,优化算法从找到最佳解决方案到能够连续跟踪最佳行为的变化。本文首先介绍一种基于禁忌搜索的新调度方法,以解决动态Job-Shop调度问题,该方法考虑了作业发布时间,作业到期日期和不同的装配级别(并行操作)。该框架基于将Job-shop调度问题分解为一系列确定性单机调度问题(SMSP)以及禁忌搜索算法,该算法可解决每个集成了其解决方案的SMSP。描述了机器间活动协调机制。最后,所使用的方法使确定性问题的解决方案适应于不确定性问题,在不确定性问题中,变化可能会连续发生。这考虑了制造系统中的动态事件,并使当前邻域适应新的再生邻域。

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