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

机译:用于集中式和分布式制造网络的多周期设计和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:考虑到投资和运输之间的潜在权衡,本文针对制造网络的设计和规划,考虑了集中式和分布式设施的选择。该问题被公式化为Capacitated Multi-facility Weber问题的扩展,该问题涉及选择在每个时间段内要构建哪些设施,以及它们在连续二维空间中的位置,以便满足需求并最小化成本。该模型是一个多时期的GDP,被重新表述为非凸型MINLP。我们提出了Lara等人的“双水平分解”的加速版本。 (2018年)发现分解方案的界限更强。我们将算法的性能与原始的Bilevel分解和商业全局求解程序进行了比较,结果表明,在所有测试的实例中,我们的方法均优于其他方法。此外,我们通过生物质供应链案例研究说明了所提出的模型和解决方案框架的适用性。 (C)2019 Elsevier Ltd.保留所有权利。

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