The optimal replenishment policy for time-varying stochastic demand under vendor managed inventory

Kannan Govindan*

*Kontaktforfatter for dette arbejde

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Resumé

A Vendor Managed Inventory (VMI) partnership places the responsibility on the vendor (rather than on buyers) to schedule purchase orders for inventory replenishment in the supply chain system. In this research, the supply chain network considers the Silver-Meal heuristic with an augmentation quantity replenishment policy between both traditional and VMI systems. We consider time-varying stochastic demand in two-echelon (one vendor, multiple retailers) supply chains. This paper seeks to find the supply chain that minimizes system cost through comparing performance between traditional and VMI systems. A mathematical model is developed, and total supply chain cost is used as the measure of comparison. The models are applied in both traditional and VMI supply chains based on pharmaceutical industry data, and we focus on total cost difference compared through the use of Adjusted Silver-Meal (ASM) and Least Unit Cost heuristics. Finally, a numerical example and a sensitivity analysis are also illustrated to show the applicability of the model.

OriginalsprogEngelsk
TidsskriftEuropean Journal of Operational Research
Vol/bind242
Udgave nummer2
Sider (fra-til)402-423
Antal sider22
ISSN0377-2217
DOI
StatusUdgivet - 2015

Fingeraftryk

Stochastic Demand
Optimal Policy
Supply Chain
Supply chains
Time-varying
Inventory Systems
Costs
Silver
Heuristics
Pharmaceuticals
Augmentation
Drug products
Sensitivity analysis
Sensitivity Analysis
Supply chain
Vendor managed inventory
Replenishment policy
Stochastic demand
Schedule
Industry

Citer dette

@article{c79eaf3ff3994a16881e6bd6b591882e,
title = "The optimal replenishment policy for time-varying stochastic demand under vendor managed inventory",
abstract = "A Vendor Managed Inventory (VMI) partnership places the responsibility on the vendor (rather than on buyers) to schedule purchase orders for inventory replenishment in the supply chain system. In this research, the supply chain network considers the Silver-Meal heuristic with an augmentation quantity replenishment policy between both traditional and VMI systems. We consider time-varying stochastic demand in two-echelon (one vendor, multiple retailers) supply chains. This paper seeks to find the supply chain that minimizes system cost through comparing performance between traditional and VMI systems. A mathematical model is developed, and total supply chain cost is used as the measure of comparison. The models are applied in both traditional and VMI supply chains based on pharmaceutical industry data, and we focus on total cost difference compared through the use of Adjusted Silver-Meal (ASM) and Least Unit Cost heuristics. Finally, a numerical example and a sensitivity analysis are also illustrated to show the applicability of the model.",
keywords = "Adjusted silver-meal (asm) heuristic, Pharmaceutical industry, Safety stock, Time-varying stochastic demand, Vmi supply chain",
author = "Kannan Govindan",
year = "2015",
doi = "10.1016/j.ejor.2014.09.045",
language = "English",
volume = "242",
pages = "402--423",
journal = "European Journal of Operational Research",
issn = "0377-2217",
publisher = "Elsevier",
number = "2",

}

The optimal replenishment policy for time-varying stochastic demand under vendor managed inventory. / Govindan, Kannan.

I: European Journal of Operational Research, Bind 242, Nr. 2, 2015, s. 402-423.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - The optimal replenishment policy for time-varying stochastic demand under vendor managed inventory

AU - Govindan, Kannan

PY - 2015

Y1 - 2015

N2 - A Vendor Managed Inventory (VMI) partnership places the responsibility on the vendor (rather than on buyers) to schedule purchase orders for inventory replenishment in the supply chain system. In this research, the supply chain network considers the Silver-Meal heuristic with an augmentation quantity replenishment policy between both traditional and VMI systems. We consider time-varying stochastic demand in two-echelon (one vendor, multiple retailers) supply chains. This paper seeks to find the supply chain that minimizes system cost through comparing performance between traditional and VMI systems. A mathematical model is developed, and total supply chain cost is used as the measure of comparison. The models are applied in both traditional and VMI supply chains based on pharmaceutical industry data, and we focus on total cost difference compared through the use of Adjusted Silver-Meal (ASM) and Least Unit Cost heuristics. Finally, a numerical example and a sensitivity analysis are also illustrated to show the applicability of the model.

AB - A Vendor Managed Inventory (VMI) partnership places the responsibility on the vendor (rather than on buyers) to schedule purchase orders for inventory replenishment in the supply chain system. In this research, the supply chain network considers the Silver-Meal heuristic with an augmentation quantity replenishment policy between both traditional and VMI systems. We consider time-varying stochastic demand in two-echelon (one vendor, multiple retailers) supply chains. This paper seeks to find the supply chain that minimizes system cost through comparing performance between traditional and VMI systems. A mathematical model is developed, and total supply chain cost is used as the measure of comparison. The models are applied in both traditional and VMI supply chains based on pharmaceutical industry data, and we focus on total cost difference compared through the use of Adjusted Silver-Meal (ASM) and Least Unit Cost heuristics. Finally, a numerical example and a sensitivity analysis are also illustrated to show the applicability of the model.

KW - Adjusted silver-meal (asm) heuristic

KW - Pharmaceutical industry

KW - Safety stock

KW - Time-varying stochastic demand

KW - Vmi supply chain

U2 - 10.1016/j.ejor.2014.09.045

DO - 10.1016/j.ejor.2014.09.045

M3 - Journal article

AN - SCOPUS:84920656413

VL - 242

SP - 402

EP - 423

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 2

ER -