Metaheuristics with local search techniques for retail shelf-space optimization

Metaheuristics with local search techniques for retail shelf-space optimization

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Article ID: iaor20073260
Country: United States
Volume: 50
Issue: 1
Start Page Number: 117
End Page Number: 131
Publication Date: Jan 2004
Journal: Management Science
Authors: , ,
Keywords: heuristics: local search
Abstract:

Efficient shelf-space allocation can provide retailers with a competitive edge. While there has been little study on this subject, there is great interest in improving product allocation in the retail industry. This paper examines a practicable linear allocation model for optimizing shelf-space allocation. It extends the model to address other requirements such as product groupings and nonlinear profit functions. Besides providing a network flow solution, we put forward a strategy that combines a strong local search with a metaheuristic approach to space allocation. This strategy is flexible and efficient, as it can address both linear and nonlinear problems of realistic size while achieving near-optimal solutions through easily implemented algorithms in reasonable timescales. It offers retailers opportunities for more efficient and profitable shelf management, as well as higher-quality planograms.

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