Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/15776
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: Heuristic, meta-heuristic and hyper-heuristic approaches for fresh produce inventory control and shelf space allocation
Authors: Bai, Ruibin
Burke, Edmund
Kendall, Graham
Contact Email: e.k.burke@stir.ac.uk
Keywords: meta-heuristics
hyper-heuristics
shelf space allocation
inventory
fresh produce
Issue Date: 2008
Publisher: Palgrave Macmillan
Citation: Bai R, Burke E & Kendall G (2008) Heuristic, meta-heuristic and hyper-heuristic approaches for fresh produce inventory control and shelf space allocation, Journal of the Operational Research Society, 59 (10), pp. 1387-1397.
Abstract: The allocation of fresh produce to shelf space represents a new decision support research area which is motivated by the desire of many retailers to improve their service due to the increasing demand for fresh food. However, automated decision making for fresh produce allocation is challenging because of the very short lifetime of fresh products. This paper considers a recently proposed practical model for the problem which is motivated by our collaboration with Tesco. Moreover, the paper investigates heuristic and meta-heuristic approaches as alternatives for the generalized reduced gradient algorithm, which becomes inefficient when the problem size becomes larger. A simpler single-item inventory problem is firstly studied and solved by a polynomial time bounded procedure. Several dynamic greedy heuristics are then developed for the multi-item problem based on the procedure for the single-item inventory problem. Experimental results show that these greedy heuristics are much more efficient and provide competitive results when compared to those of a multi-start generalized reduced gradient algorithm. In order to further improve the solution, we investigated simulated annealing, a greedy randomized adaptive search procedure and three types of hyper-heuristics. Their performance is tested and compared on a set of problem instances which are made publicly available for the research community.
Type: Journal Article
URI: http://hdl.handle.net/1893/15776
DOI Link: http://dx.doi.org/10.1057/palgrave.jors.2602463
Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
Affiliation: University of Nottingham Ningbo China
Deputy Principal's Office
University of Nottingham

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