Order Assignment and Scheduling in a Supply Chain

Zhi-Long Chen () and Guruprasad Pundoor ()
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Zhi-Long Chen: Department of Decision and Information Technologies, Robert H. Smith School of Business, University of Maryland, College Park, Maryland 20742-1815
Guruprasad Pundoor: FedEx Express, 3680 Hacks Cross Road, Building H, Memphis, Tennessee 38125

Operations Research, 2006, vol. 54, issue 3, 555-572

Abstract: We consider the supply chain of a manufacturer who produces time-sensitive products that have a large variety, a short life cycle, and are sold in a very short selling season. The supply chain consists of multiple overseas plants and a domestic distribution center (DC). Retail orders are first processed at the plants and then shipped from the plants to the DC for distribution to domestic retailers. Due to variations in productivity and labor costs at different plants, the processing time and cost of an order are dependent on the plant to which it is assigned. We study the following static and deterministic order assignment and scheduling problem faced by the manufacturer before every selling season: Given a set of orders, determine which orders are to be assigned to each plant, find a schedule for processing the assigned orders at each plant, and find a schedule for shipping the completed orders from each plant to the DC, such that a certain performance measure is optimized. We consider four different performance measures, all of which take into account both delivery lead time and the total production and distribution cost. A problem corresponding to each performance measure is studied separately. We analyze the computational complexity of various cases of the problems by either proving that a problem is intractable or providing an efficient exact algorithm for the problem. We propose several fast heuristics for the intractable problems. We analyze the worst-case and asymptotic performance of the heuristics and also computationally evaluate their performance using randomly generated test instances. Our results show that the heuristics are capable of generating near-optimal solutions quickly.

Keywords: production/scheduling; approximation/heuristic; deterministic sequencing; manufacturing; performance/productivity; transportation; scheduling; programming; integer; algorithms; heuristic (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (41)

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