Shelf space re-allocation for out of stock reduction. (April 2017)

• Record Type: Journal Article
• Authors: Frontoni, E.; Marinelli, F.; Rosetti, R.; Zingaretti, P.
• Is Part Of: Computers & industrial engineering. Volume 106(2017)
• Page Start: 32
• Page End: 40
• Publication Date: 2017-04
• Subjects: Shelf space allocation -- Out-of-stock -- Shelf Detector System -- Integer linear programming; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2017.01.021
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: An ILP formulation is proposed for Shelf space re-allocation problem. Out-of-stock data are collected from the Shelf Detector System in real time. Space elastic demand function is linked with real-time statistical data. Tests performed on real, random and large instances. Abstract: A planogram is a detailed visual map that establishes product positions over a shelf in a retail store. It is designed to support an innovative merchandising approach, to increase sales and profits, to supply the best location of a product for suppliers and to better manage the shelves. Product selection and the shelf space reserved to each product is a central activity for retailers and Shelf Out of Stock (SOOS) events are often strongly related to planogram design. In this paper we present a solution to optimally re-allocate shelf space to minimize Out of Stock (OOS) events. The approach uses SOOS data coming in real time from a sensor network technology, named Shelf Detector System, and an Integer Linear Programming model that integrates a space elastic demand function. Experimental results, based on a real scenario in the diaper category in Belgium, have proved that the system can efficiently calculate a proper solution able to re-allocate space and reduce OOS events.