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Efficient algorithm to find makespan in manufacturing systems under multiple scheduling perturbations

机译:在多重调度扰动下在制造系统中寻找有效期的有效算法

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摘要

Manufacturing scheduling improvement heuristics iterate over trial schedules to determine a satisfactory schedule. During each iteration, a performance measure (e.g. makespan) is calculated. The paper presents an efficient algorithm, Structural Perturbation Algorithm (SPA), that accelerates the calculation of the makespan. This means all scheduling improvement heuristics using SPA to calculate makespan for each trial schedule will run faster. To achieve this goal, the manufacturing system is modelled by a Directed Acyclic Graph (DAG). Schedule trials can be described as a perturbed DAG where multiple edges are added and deleted. The major contribution of this research is that SPA can handle multiple edge deletions/additions with a single pass which makes it more efficient in terms of time complexity than current approaches. SPA accomplishes this by partitioning the nodes into three regions based on the locations of the added and deleted edges. Then, SPA updates the length of the affected nodes in each region. The application of SPA is not limited to the scheduling problem. The SPA can be applied in other fields as long as the problem can be described as a Perturbed DAG.
机译:制造进度计划改进试探法在试用计划表上进行迭代以确定满意的计划表。在每次迭代期间,都会计算出性能指标(例如,制造期)。本文提出了一种有效的算法,即结构扰动算法(SPA),它可以加快计算有效期。这意味着所有使用SPA来计算每个试验计划的制造时间的计划改进启发法都将运行得更快。为了实现此目标,制造系统通过有向无环图(DAG)建模。进度试验可以描述为扰动的DAG,其中添加和删除了多个边。这项研究的主要贡献在于,SPA可以通过一次处理来处理多个边缘删除/添加,这使得它在时间复杂度方面比当前方法更为有效。 SPA通过根据添加和删除边的位置将节点划分为三个区域来实现此目的。然后,SPA更新每个区域中受影响节点的长度。 SPA的应用不限于调度问题。 SPA可以应用于其他领域,只要问题可以描述为扰动DAG。

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