Please use this identifier to cite or link to this item:
|Title:||Optimal Retail Shelf Space Allocation with Dynamic Programming using Bounds|
|Citation:||IEEM: 2008 INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT, VOLS 1-3, (), 1068-1072|
|Abstract:||Efficient shelf space allocation increases profitability of a retail store and thus provides competitive advantage to the retailer. Several shelf space allocation models exist in literature. However, these models are generally solved using heuristic approaches due to NP-hard nature and there is a need to develop exact methods. In this paper, we present a non-linear shelf-space allocation model (NLSSAM) and optimally, solve it with a new dynamic programming (NDP) using bounds which fathoms unpromising states. It is found from experimental studies that NDP using bound was much more efficient to solve large problems as compared to original dynamic programming (ODP) without using bound. ODP could not solve all problem instances of problem sizes (number of products, n = 30 and 40) within specified CPU time limit of 400 seconds while NDP could solved problem instances of size (n = 200) with average CPU time of 7.89 seconds.|
|Appears in Collections:||Article|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.