Decision support system for vendor managed inventory supply chain:a case study

Abstract

Vendor-managed inventory (VMI) is a widely used collaborative inventory management policy in which manufacturers manages the inventory of retailers and takes responsibility for making decisions related to the timing and extent of inventory replenishment. VMI partnerships help organisations to reduce demand variability, inventory holding and distribution costs. This study provides empirical evidence that significant economic benefits can be achieved with the use of a genetic algorithm (GA)-based decision support system (DSS) in a VMI supply chain. A two-stage serial supply chain in which retailers and their supplier are operating VMI in an uncertain demand environment is studied. Performance was measured in terms of cost, profit, stockouts and service levels. The results generated from GA-based model were compared to traditional alternatives. The study found that the GA-based approach outperformed traditional methods and its use can be economically justified in small- and medium-sized enterprises (SMEs).

Publication DOI: https://doi.org/10.1080/00207543.2014.993047
Divisions: College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering > Engineering Systems and Supply Chain Management
College of Engineering & Physical Sciences
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 23/12/14, available online: http://wwww.tandfonline.com/10.1080/00207543.2014.993047
Uncontrolled Keywords: case study,decision support system,genetic algorithm,vendor-managed inventory,Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management
Publication ISSN: 1366-588X
Last Modified: 08 Mar 2024 08:11
Date Deposited: 04 Jun 2015 14:50
Full Text Link: http://www.tand ... 543.2014.993047
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2015
Published Online Date: 2014-11-18
Authors: Borade, Atul B.
Sweeney, Edward (ORCID Profile 0000-0002-8389-4446)

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Version: Accepted Version


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