Production and transportation integration for a make-to-order manufacturing company with a commit-to-delivery business mode
Production and transportation integration for a make-to-order manufacturing company with a commit-to-delivery business mode
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DOI：
10.1287/msom.1060.0138
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发表时间：
2007-03-01
影响因子：
6.3
通讯作者：
Zhao, Xuying
中科院分区：
文献类型：
--
作者：
Stecke, Kathryn E.;Zhao, Xuying
订单制造企业采用委托-交货业务模式时，对订单承诺交货期，并承担运费。在不失一般性的情况下，我们认为运输是由第三方物流公司完成的，如联邦快递或UPS，提供多种运输模式，如隔夜，一天，两天交付等。当运输时间必须很短时，显然，运输成本比本来可能的要贵。公司应该如何安排已接受订单的生产，以便公司为订单留出足够的运输时间，采取慢速运输模式以降低运输成本？我们研究这个问题的集成生产和运输功能的制造公司生产的各种定制的产品在一个按订单生产的环境与承诺交付的业务模式。各种现实的情况下，调查的复杂性增加的顺序。当客户允许部分交货时，我们给出了一个混合整数规划模型和一个最小费用流模型。当允许部分交货且运输成本是随运输时间递减的凸函数时，非抢占式最早交货期（NEDD）生产计划是最优的。当不允许部分交付时，我们建立了一个MIP模型，并证明了该问题是NP-难的。对于NP难问题，给出了一个有效的多项式时间启发式算法。它给出了接近最优的生产计划，通过数以千计的数值实验所示。我们还为运输成本占客户位置和数量折扣的其他场景提供模型和分析。
When a make-to-order manufacturing company adopts a commit-to-delivery business mode, it commits a delivery due date for an order and is responsible for the shipping cost. Without loss of generality, we consider that transportation is done by a third-party logistics company, such as FedEx or UPS, which provides multiple shipping modes such as overnight, one-day, two-day delivery, and more. When the transportation time has to be short, clearly, shipping cost is more expensive than it could have been. How should a company schedule production for accepted orders so that the company can leave enough transportation time for orders to take slow shipping modes to reduce the shipping cost? We study this problem of integrating the production and transportation functions for a manufacturing company producing a variety of customized products in a make-to-order environment with a commit-to-delivery mode of business. Various realistic scenarios are investigated in increasing order of complexity. When partial delivery is allowed by customers, we provide both a mixed-integer programming (MIP) model and a minimum cost flow model. We show that nonpreemptive earliest due date (NEDD) production schedules are optimal when partial delivery is allowed and shipping cost is a decreasing convex function with transportation time. When partial delivery is not allowed, we develop an MIP model and prove that the problem is NP-hard. An efficient heuristic algorithm with polynomial computation time is provided for the NP-hard problem. It gives near-optimal production schedules, as shown via thousands of numerical experiments. We also provide models and analysis for other scenarios where shipping cost accounts for customer locations and quantity discounts.