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Global optimization algorithm for multi-period design and planning of centralized and distributed manufacturing networks

机译:集中式和分布式制造网络多周期设计与规划的全局优化算法

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This paper addresses the design and planning of manufacturing networks considering the option of centralized and distributed facilities, taking into account the potential trade-offs between investments and transportation. The problem is formulated as an extension of the Capacitated Multi-facility Weber Problem, which involves the selection of which facilities to build in each time period, and their location in the continuous two-dimensional space, in order to meet demand and minimize costs. The model is a multi-period GDP, reformulated as a nonconvex MINLP. We propose an accelerated version of the Bilevel Decomposition by Lara et al. (2018) that finds stronger bounds in the decomposition scheme. We benchmark the performance of our algorithm against the original Bilevel Decomposition and commercial global solvers and show that our approach outperforms the others in all instances tested. Additionally, we illustrate the applicability of the proposed model and solution framework with a biomass supply chain case study. (C) 2019 Elsevier Ltd. All rights reserved.
机译:本文考虑到投资与运输之间的潜在权衡,涉及制造网络的设计和规划,考虑到集中式和分布式设施。该问题被制定为电容多设施韦伯问题的延伸,这涉及在每次时段中选择哪些设施,以及它们在连续二维空间中的位置,以满足需求并最小化成本。该模型是一个多时期GDP,重新重新设计为非核解MINLP。我们提出了Lara等人的加速版本的彼得分解。 (2018)在分解方案中发现更强大的范围。我们将算法的性能进行基准,对原始的Bilevel分解和商业全球求解器的表现,并表明我们的方法在所测试的所有实例中占外。此外,我们说明了所提出的模型和解决方案框架与生物质供应链案例研究的适用性。 (c)2019 Elsevier Ltd.保留所有权利。

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