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A Heuristic Solution of Multi-Item Single Level Capacitated Dynamic Lot-Sizing Problem with Setup Time

机译:具有设置时间的多项目单级电容动态批量问题的启发式解决方案

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The multi-item single level capacitated dynamic lot-sizing problem consists of scheduling N items over a horizon of T periods. The objective is to minimize the sum of setup and inventory holding costs over the horizon subject to a constraint on total capacity in each period. No backlogging is allowed. Only one machine is available with a fixed capacity in each period. In case of a single item production, an optimal solution algorithm exists. But for multi-item problems, optimal solution algorithms are not available. It has been proved that even the two-item problem with constant capacity is NP-hard, that is, it is in a class of problems that are extremely difficult to solve in a reasonable amount of time. This has called for searching good heuristic solutions. For a multi-item problem, it would be more realistic to consider the setup time, since switching the machine from one item to another would require a setup time. This setup time would be independent of item sequences and this could be a very important parameter from practical point of view. The current research work has been directed toward the development of a model for multi-item problem considering this parameter. Based on the model a program has been executed and feasible solutions with some real life data have been obtained.
机译:多项单级电容动态批量问题包括在T期的地平线上调度N项。目的是最大限度地减少通过每个时期总容量的限制,使地平线上的设置和库存持有成本的总和。允许允许积压。只有一台机器在每个时段都有固定容量。在单个项目生产的情况下,存在最佳解决方案算法。但对于多项目问题,不可用最佳解决方案算法。已经证明,即使是恒定容量的两个项目问题也是NP - 硬,也就是说,它是在合理的时间内极难解决的一类问题。这呼吁寻找良好的启发式解决方案。对于多项问题,考虑设置时间将更加逼真,因为从一个项目切换到另一个项目将需要设置时间。此设置时间将独立于项目序列,这可能是从实际角度来看的一个非常重要的参数。考虑此参数,目前的研究工作已经朝向开发用于多项问题的模型。基于模型,已经执行了一个程序,并且已经获得了一些现实生活数据的可行解决方案。

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