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An Iterated Greedy approach to integrate production by multiple parallel machines and distribution by a single capacitated vehicle

机译:一种迭代的贪婪方法,可以通过单个电容车辆整合生产和分布

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Studies in the literature have shown that for production systems the integration of manufacturing and distribution decisions is appealing for both experimental and real-world applications. Although the number of papers in which strategies are proposed to solve such Integrated Scheduling Production, Inventory and Distribution Problems (ISPIDP) is growing, algorithms are required for this category of problems. This study was aimed to integrate a scheduling problem of parallel machines with sequence dependent setup time with a delivery system composed of a single vehicle with multiple routes. To address this ISPIDP, two new algorithms, one constructive heuristic and an improvement heuristic based on the Iterated Greedy technique were implemented and their results compared with a Mixed-Integer Programming model and a Genetic Algorithm adapted from studies in the literature. The results indicated that the algorithms were able to obtain good results, although it is clear that the number of machines involved affected the performance of each algorithm differently.
机译:文献中的研究表明,对于生产系统,制造和分配决策的整合对实验和现实世界的应用起见。虽然提出了策略来解决此类综合调度生产,库存和分布问题(ISPIDP)的论文数量增长,但这类问题需要算法。本研究旨在将并联机器的调度问题与序列相关的设置时间集成,其中具有由具有多个路由的单个车辆组成的递送系统。为了解决这一ISPIDP,实现了两个新的算法,一个基于迭代贪婪技术的一个建设性启发式和改进启发式,与混合整数编程模型和改编的遗传算法相比,从文献中的研究改编。结果表明,该算法能够获得良好的效果,尽管很明显,所涉及的机器数量会影响每个算法的性能。

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