Towards an evolutionary tool for the allocation of supermarket shelf space
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Rearrangement Clustering: Pitfalls, Remedies, and Applications
The Journal of Machine Learning Research
A Multiobjective Evolutionary Algorithm for the Linear Shelf Space Allocation Problem
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
A genetic algorithm approach to an integrated problem of shelf space design and item allocation
Computers and Industrial Engineering
Heuristic approach for automated shelf space allocation
Proceedings of the 2009 ACM symposium on Applied Computing
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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.