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Exact and heuristic approaches for lot splitting and scheduling on identical parallel machines

机译:在相同的并行计算机上进行批量分割和调度的精确和启发式方法

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摘要

In this paper, we address a lot splitting and scheduling problem existent in a textile factory. The factory we study produces a set of products that are made of, or assembled from, a list of components. During production, each component can be split into one or several lots of different sizes and each lot will be produced independently on one of a group of identical parallel machines. We formulate the problem into a mixed integer programming model and develop a heuristic method to solve the model. The heuristic method is based on a network flow model with the objective to minimise the weighted sum of the total tardiness of products and the deviations occurred during production of each product. The deviation of a product is measured by the deviation of product completion time (the last component lot completion time) and completion time of the rest of components lots for the same product. We present computational results and performance measures of the network flow heuristic for a set of randomly generated instances based on real world data.
机译:在本文中,我们解决了纺织工厂中存在的许多拆分和调度问题。我们研究的工厂生产的产品由一系列零件制成或组装而成。在生产过程中,每个组件可以分为一个或几个不同大小的批次,并且每个批次将在一组相同的并行机器中的一个上独立生产。我们将问题公式化为混合整数规划模型,并开发一种启发式方法来求解该模型。启发式方法基于网络流模型,其目的是最小化产品总拖延率的加权总和以及每种产品生产过程中发生的偏差。产品的偏差是通过同一产品的产品完成时间(最后一个组件批次完成时间)和其余组件批次的完成时间的偏差来衡量的。我们为基于现实世界数据的一组随机生成的实例提供了网络流启发式的计算结果和性能度量。

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