Genetic algorithm with variable neighborhood search for the optimal allocation of goods in shop shelves

Mauro Castelli; Leonardo Vanneschi

doi:10.1016/j.orl.2014.06.002

Genetic algorithm with variable neighborhood search for the optimal allocation of goods in shop shelves

Mauro Castelli, Leonardo Vanneschi

Research output: Contribution to journal › Article › peer-review

30 Citations (Scopus)

Abstract

Shelves on which products are being displayed are one of the most important resources in retail environment. The decision of shelf-space allocation and management is therefore a critical issue in retail operation management. In this paper a hybrid algorithm that combines a genetic algorithm with a variable neighborhood search is proposed to address the shop shelf allocation problem. Results obtained from an extensive experimental phase show the suitability of the proposed algorithm in addressing the problem at hand.

Original language	English
Pages (from-to)	355-360
Number of pages	6
Journal	Operations Research Letters
Volume	42
Issue number	5
DOIs	https://doi.org/10.1016/j.orl.2014.06.002
Publication status	Published - 1 Jan 2014

Keywords

Allocation
Heuristics
Shelf space

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10.1016/j.orl.2014.06.002

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abstract = "Shelves on which products are being displayed are one of the most important resources in retail environment. The decision of shelf-space allocation and management is therefore a critical issue in retail operation management. In this paper a hybrid algorithm that combines a genetic algorithm with a variable neighborhood search is proposed to address the shop shelf allocation problem. Results obtained from an extensive experimental phase show the suitability of the proposed algorithm in addressing the problem at hand.",

keywords = "Allocation, Heuristics, Shelf space",

author = "Mauro Castelli and Leonardo Vanneschi",

note = "Castelli, M., & Vanneschi, L. (2014). Genetic algorithm with variable neighborhood search for the optimal allocation of goods in shop shelves. Operations Research Letters, 42(5), 355-360. https://doi.org/10.1016/j.orl.2014.06.002",

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AU - Vanneschi, Leonardo

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N2 - Shelves on which products are being displayed are one of the most important resources in retail environment. The decision of shelf-space allocation and management is therefore a critical issue in retail operation management. In this paper a hybrid algorithm that combines a genetic algorithm with a variable neighborhood search is proposed to address the shop shelf allocation problem. Results obtained from an extensive experimental phase show the suitability of the proposed algorithm in addressing the problem at hand.

AB - Shelves on which products are being displayed are one of the most important resources in retail environment. The decision of shelf-space allocation and management is therefore a critical issue in retail operation management. In this paper a hybrid algorithm that combines a genetic algorithm with a variable neighborhood search is proposed to address the shop shelf allocation problem. Results obtained from an extensive experimental phase show the suitability of the proposed algorithm in addressing the problem at hand.

KW - Allocation

KW - Heuristics

KW - Shelf space

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SP - 355

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JO - Operations Research Letters

JF - Operations Research Letters

IS - 5

ER -

Genetic algorithm with variable neighborhood search for the optimal allocation of goods in shop shelves

Abstract

Keywords

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