An evolutionary approach for the offsetting inventory cycle problem

In inventory management, a fundamental issue is the rational use of required space. Among the numerous techniques adopted, an important role is played by the determination of the replenishment cycle offsetting which minimizes the warehouse space within a considered time horizon. The NP-completeness...

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Bibliographic Details
Published in:Cogent engineering 2017-01, Vol.4 (1), p.1370764
Main Authors: Franciosi, Chiara, Carrabs, Francesco, Cerulli, Raffaele, Miranda, Salvatore
Format: Article
Language:English
Subjects:
Engineering Sciences
genetic algorithm
Genetic algorithms
Integer programming
Inventory
Inventory management
joint replenishment problem
Mixed integer
mixed integer programming
Model testing
offsetting inventory cycle problem
OICP
Replenishment
replenishment cycle offsetting
Reproducibility
warehouse space
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Summary:In inventory management, a fundamental issue is the rational use of required space. Among the numerous techniques adopted, an important role is played by the determination of the replenishment cycle offsetting which minimizes the warehouse space within a considered time horizon. The NP-completeness of the Offsetting Inventory Cycle Problem (OICP) has led the researchers towards the development and the comparison of specific heuristics. We propose and implement a genetic algorithm for the OICP, whose effectiveness is validated by comparing its solutions with those found by a mixed integer programming model. The algorithm, tested on realistic instances, shows a high reduction of the maximum space and a more regular warehouse saturation with negligible increase of the total cost. This paper, unlike other papers currently available in literature, provides instances data and results necessary for reproducibility, aiming to become a benchmark for future comparisons with other OICP algorithms.
ISSN:2331-1916
2331-1916
DOI:10.1080/23311916.2017.1370764