Title: An approach for inventory routing under vendor managed inventory system

Authors: Atul B. Borade, Satish V. Bansod

Addresses: Mechanical Engineering Department, Jawaharlal Darda Institute of Engineering and Technology, Yavatmal, Maharashtra, India. ' Mechanical Engineering Department, Professor Ram Meghe Institute of Research and Technology, Bandera, India

Abstract: Vendor managed inventory is a collaborative business practice adopted by organisations to improve the business performance. Under this practice, the retailers share demand and other related information with the manufacturer, who in turn manages the inventory of the retailer. In such event, the manufacturer assumes the responsibility of taking the decisions about size and time of delivery, vehicle routing, etc. This study examines the vendor managed inventory practice, specifically inventory routing problem, for retailers and a manufacturer when there is a wide fluctuation of daily demand. We have addressed a special issue related to inventory replenishment in vendor managed inventory system, where demand exceeds the finite production capacity .We construct a numerical experiment in MATLAB to find the optimal daily demand distribution and vehicle routing using fuzzy min-max learning algorithm. First, for deciding the sequence in which the quantity to be delivered to the retailers, a fuzzy set hyperboxes are used .Then, assignment is done with the help of discounting coefficient. Lastly, routing is done using fuzzy iterative algorithm. The focus of this paper is on demonstrating the effectiveness of our approach and comparing the results with that of simple greedy heuristics.

Keywords: vendor managed inventory; VMI; inventory routing; fuzzy logic; collaborative business practices; collaboration; business performance; retailers; retail industry; manufacturers; manufacturing industry; inventories; delivery times; vehicle routing; demand fluctuation; daily demand distribution; inventory replenishment; finite production capacity; MATLAB; matrix laboratory; learning algorithms; delivery quantities; hyperboxes; discounting coefficients; iterative algorithms; greedy heuristics.

DOI: 10.1504/IJSSCI.2010.035761

International Journal of Services Sciences, 2010 Vol.3 No.4, pp.293 - 318

Published online: 03 Oct 2010 *

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