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A Continuous Time Mixed Integer Linear Programming Model for Short Term Scheduling of Multistage Batch Plants

机译:多阶段批量工厂短期调度的连续时间混合整数线性规划模型

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The problem of short term scheduling of batch plants consists of determining the optimal production policy for satisfying the production demands for different products at due dates and/ or at the end of a given time horizon. The objective of this work is to propose an optimization model and solution method to the short term scheduling of batch plants with multiple stages which may contain equipment in parallel. A large scale mixed integer linear programming (MILP) model with continuous time domain representation is proposed that relies on the use of parallel time axes for units and tasks. Although in principle an LP-based branch and bound method can be used to solve the problem, there is a limitation when the instances become large. The first solution strategy that is proposed consists of the use of preordering constraints. Furthermore, a second strategy relies on a decomposition scheme for large systems which is based on the solution of an MILP model that minimizes total in process time in which assignments are determined and the subsequent solution of an LP to minimize earliness and to eliminate unnecessary setups. Several examples are presented, including a large real world problem, to illustrate the performance of the model and solution method.
机译:批处理工厂的短期调度问题包括确定最佳生产策略,以便在到期日和/或给定时间范围结束时满足不同产品的生产需求。这项工作的目的是为具有多个阶段(可能包含并行设备)的批处理工厂的短期调度提出一种优化模型和解决方法。提出了具有连续时域表示的大规模混合整数线性规划(MILP)模型,该模型依赖于单元和任务使用并行时间轴。尽管原则上可以使用基于LP的分支定界方法来解决此问题,但是当实例变大时存在局限性。提出的第一个解决方案策略包括使用预排序约束。此外,第二种策略依赖于大型系统的分解方案,该方案基于MILP模型的解决方案,该方案使确定分配的总处理时间最小化,以及LP的后续解决方案,以最大程度地减少提前性并消除不必要的设置。给出了几个示例,包括一个大的现实问题,以说明模型和求解方法的性能。

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