Staggering Periodic Replenishment in Multivendor JIT Environments

Sin-Hoon Hum (), Moosa Sharafali () and Chung-Piaw Teo ()
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Sin-Hoon Hum: Department of Decision Sciences, NUS Business School, National University of Singapore, Singapore 117591
Moosa Sharafali: Department of Management, Faculty of Economics and Commerce, University of Melbourne, Melbourne, Victoria 3010, Australia
Chung-Piaw Teo: SKK Graduate School of Business, Sungkyunkwan University, Seoul, South Korea 110745, teocp@skku.edu, and Department of Decision Sciences, NUS Business School, National University of Singapore, Singapore 117591

Operations Research, 2005, vol. 53, issue 4, 698-710

Abstract: The delivery scheduling problem studied in this paper was motivated by the operation in a large personal computer assembly plant, which was using multisourcing for some of its materials. The company’s objective was to design a delivery schedule so that the average inventory level in the factory was minimized. We show that the problem is intimately related to a classical inventory staggering problem, where the focus is on the computation of the peak inventory level associated with the replenishment policy. This connection allows us to show that the delivery scheduling problem is NP-hard. For the two-vendor case with integral replenishment intervals, we propose a generalized form of Homer’s scheduling heuristic and obtain performance bounds for the classical inventory staggering problem. Our analysis uses the Chinese remainder theorem in an interesting way. The approach can be generalized to the case with more than two vendors, leading to a strong linear-programming-based lower bound for the inventory staggering problem. We illustrate this technique for the case in which all the replenishment intervals are relatively prime, establishing a bound that is not greater than 140% of the optimal. We examine the implications of these results to the delivery scheduling problem.

Keywords: logistics; inventory management; multisourcing; Chinese remainder theorem (search for similar items in EconPapers)
Date: 2005
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