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Annual production budget in the beverage industry

机译:饮料行业的年度生产预算

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Driven by a real-world application in the beverage industry, this paper provides a design of a new VNS variant to tackle the annual production budget problem. The problem consists of assigning and scheduling production lots in a multi-plant environment, where each plant has a set of filling lines that bottle and pack drinks. Plans also consider final product transfers between the plants. Our algorithm fixes setup variables for family of products and determines production, inventory and transfer decisions by solving a linear programming (LP) model. As we are dealing with very large problem instances, it is inefficient and unpractical to search the entire neighborhood of the incumbent solution at each iteration of the algorithm. We explore the sensitivity analysis of the LP to guide the partial neighborhood search. Dual-reoptimization is also used to speed-up the solution procedure. Tests with instances from our case study have shown that the algorithm can substantially improve the current business practice, and it is more competitive than state-of-the-art commercial solvers and other VNS variants.
机译:在饮料行业的实际应用的驱动下,本文提供了一种新的VNS变体设计,以解决年度生产预算问题。问题在于在多工厂环境中分配和调度生产批次,在每个工厂中,每个工厂都有一组用于灌装和包装饮料的灌装线。计划还考虑了工厂之间的最终产品转移。我们的算法修复了产品系列的设置变量,并通过求解线性规划(LP)模型来确定生产,库存和转移决策。由于我们正在处理非常大的问题实例,因此在算法的每次迭代中搜索现有解决方案的整个邻域都是低效率且不切实际的。我们探索LP的敏感性分析,以指导部分邻域搜索。双重重新优化也可用于加快求解过程。从我们的案例研究中对实例进行的测试表明,该算法可以大大改善当前的商业惯例,并且比最新的商业求解器和其他VNS变体更具竞争力。

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