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A single‐period, multi‐echelon stochastic model under a mix of assemble to order and assemble in advance policies

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  • Moncer Hariga

Abstract

This article presents a stochastic model for a single‐period production system composed of several assembly/processing and storage facilities in series. The production system operates under a composite strategy of the assemble to order and assemble in advance policies. The developed mathematical model is simpler and more compact than the ones provided in earlier articles. Moreover, the formulation allows the optimal inventory levels at the start of the period to be determined from the solution to the well‐known newsboy problem. We also analyze the problem under the free distribution approach which only assumes the knowledge of the first two moments of the demand distribution. The robustness of this approach is tested by carrying an extensive experimental comparison using different demand distributions. Finally, the composite model is extended by considering the effects of some budgetary constraints. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 599–614, 1998

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  • Moncer Hariga, 1998. "A single‐period, multi‐echelon stochastic model under a mix of assemble to order and assemble in advance policies," Naval Research Logistics (NRL), John Wiley & Sons, vol. 45(6), pages 599-614, September.
    • Handle: RePEc:wly:navres:v:45:y:1998:i:6:p:599-614
    DOI: 10.1002/(SICI)1520-6750(199809)45:63.0.CO;2-Y
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    1. Amit Eynan & Meir J. Rosenblatt, 1995. "Assemble to order and assemble in advance in a single‐period stochastic environment," Naval Research Logistics (NRL), John Wiley & Sons, vol. 42(5), pages 861-872, August.
    2. John M. Cozzolino & Michael J. Zahner, 1973. "The Maximum-Entropy Distribution of the Future Market Price of a Stock," Operations Research, INFORMS, vol. 21(6), pages 1200-1211, December.
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    1. Ting-Chen Hu & Kuo-Chen Hung & Kuo-Lung Yang, 2019. "The Convergence of Gallego’s Iterative Method for Distribution-Free Inventory Models," Mathematics, MDPI, vol. 7(5), pages 1-10, May.

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