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Multi-item quick response system with budget constraint

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  • Serel, Doğan A.

Abstract

Quick response mechanisms based on effective use of up-to-date demand information help retailers to reduce their inventory management costs. We formulate a single-period inventory model for multiple products with dependent (multivariate normal) demand distributions and a given overall procurement budget. After placing orders based on an initial demand forecast, new market information is gathered and demand forecast is updated. Using this more accurate second forecast, the retailer decides the total stocking level for the selling season. The second order is based on an improved demand forecast, but it also involves a higher unit supply cost. To determine the optimal ordering policy, we use a computational procedure that entails solving capacitated multi-item newsboy problems embedded within a dynamic programming model. Various numerical examples illustrate the effects of demand variability and financial constraint on the optimal policy. It is found that existence of a budget constraint may lead to an increase in the initial order size. It is also observed that as the budget available decreases, the products with more predictable demand make up a larger share of the procurement expenditure.

Suggested Citation

  • Serel, Doğan A., 2012. "Multi-item quick response system with budget constraint," International Journal of Production Economics, Elsevier, vol. 137(2), pages 235-249.
    • Handle: RePEc:eee:proeco:v:137:y:2012:i:2:p:235-249
    DOI: 10.1016/j.ijpe.2012.02.004
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    7. Priya, Bhawna & Biswas, Indranil & Thürer, Matthias & Avittathur, Balram, 2023. "How to finance the supply chain when you are small? Clearance sale and loan payment timing in financially constrained supply chains," International Journal of Production Economics, Elsevier, vol. 263(C).
    8. Wang, Qingwei & Zheng, Meimei & Lee, Ka-Man & Shi, Xiaoqian & Shen, Yichi & Pan, Ershun, 2024. "Optimal product and after-sales service decisions considering risk attitudes under price-dependent uncertain demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
    9. Patra, T. Devi Prasad & Jha, J.K., 2021. "A two-period newsvendor model for prepositioning with a post-disaster replenishment using Bayesian demand update," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    10. Mou, Shandong & Robb, David J. & DeHoratius, Nicole, 2018. "Retail store operations: Literature review and research directions," European Journal of Operational Research, Elsevier, vol. 265(2), pages 399-422.

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