Supply chain scheduling: Batching and delivery

Nicholas G. Hall () and Chris N. Potts ()
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Nicholas G. Hall: Fisher College of Business, The Ohio State University, Columbus, Ohio 43210
Chris N. Potts: Faculty of Mathematical Studies, University of Southampton, Southampton SO17 1BJ, United Kingdom

Operations Research, 2003, vol. 51, issue 4, 566-584

Abstract: Although the supply chain management literature is extensive, the benefits and challenges of coordinated decision making within supply chain scheduling models have not been studied. We consider a variety of scheduling, batching, and delivery problems that arise in an arborescent supply chain where a supplier makes deliveries to several manufacturers, who also make deliveries to customers. The objective is to minimize the overall scheduling and delivery cost, using several classical scheduling objectives. This is achieved by scheduling the jobs and forming them into batches, each of which is delivered to the next downstream stage as a single shipment. For each problem, we either derive an efficient dynamic programming algorithm that minimizes the total cost of the supplier or that of the manufacturer, or we demonstrate that this problem is intractable. The total system cost minimization problem of a supplier and manufacturer who make cooperative decisions is also considered. We demonstrate that cooperation between a supplier and a manufacturer may reduce the total system cost by at least 20%, or 25%, or by up to 100%, depending upon the scheduling objective. Finally, we identify incentives and mechanisms for this cooperation, thereby demonstrating that our work has practical implications for improving the efficiency of supply chains.

Keywords: Production/scheduling: sequencing; deterministic; single machine; multiple machine; Manufacturing: performance/productivity; Games/group decisions: cooperative; noncooperative (search for similar items in EconPapers)
Date: 2003
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Citations: View citations in EconPapers (89)

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