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A general quantity discount and supplier selection mixed integer programming model

机译:一般数量折扣和供应商选择混合整数规划模型

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Recently, new models and heuristics for exploiting quantity discounts have been proposed that are applicable in classical purchasing as well as in an e-business environment and can be implemented as part of an advanced planning system. These models can now handle both the single- and multi-item case with fixed cost to be shared among several products ordered at the same point in time from a single supplier. Furthermore, the supplier selection problem is addressed, i.e., how to best exploit quantity discounts over time offered by several suppliers. Last but not least, additional constraints on the buyer's or on the supplier's side may be included. While so far only purpose-built heuristics have been proposed for this generalized problem, we present a linear mixed integer programming (MIP) model, which not only represents the all-units discount but also the incremental discount case. Furthermore, the objective function chosen resolves (former) conflicts among proponents of a purely cost oriented and a cash flow oriented modeling approach. Computational tests show that our model yields near optimal solutions within a given CPU time limit by making use of a standard MIP solver.
机译:最近,已经提出了利用数量折扣的新模型和试探法,这些模型和试探法可应用于经典购买以及电子商务环境中,并且可以作为高级计划系统的一部分来实施。这些模型现在可以处理固定成本的单项和多项情况,并可以在同一时间点从单个供应商处订购的几种产品之间共享。此外,解决了供应商选择问题,即,如何最佳地利用几个供应商提供的随时间推移的数量折扣。最后但并非最不重要的一点是,可以包括对买方或供应商方面的其他约束。虽然到目前为止,仅针对此广义问题提出了专门构建的启发式方法,但我们提出了一种线性混合整数规划(MIP)模型,该模型不仅表示所有单位折扣,而且还表示增量折扣情况。此外,选择的目标函数可以解决(以前的)纯成本导向和现金流导向建模方法的支持者之间的冲突。计算测试表明,通过使用标准MIP求解器,我们的模型在给定的CPU时间限制内可获得接近最佳的解决方案。

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