A reduced variable neighborhood search-based hyperheuristic for the shelf space allocation problem

Yu, Vincent F.; Maglasang, Renan; Tsao, Yu‐Chung

doi:10.1016/j.cie.2020.106420

Cited by 7 publications

(2 citation statements)

References 36 publications

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“…Shelf space is important for retailers and has been referred to as the most limited retailer's resource [9,[23][24][25]. The ultimate goal of shelf space planning is to maximize profit by assigning products to shelves while keeping limited shelf space and allocation constraints in view-such as product quantities, inventory, and other operational costs.…”

Section: Shelf Space Allocation Decisionsmentioning

confidence: 99%

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Simulated Annealing Hyper-Heuristic for a Shelf Space Allocation on Symmetrical Planograms Problem

Czerniachowska

Hernes

2021

Symmetry

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The allocation of products on shelves is an important issue from the point of view of effective decision making by retailers. In this paper, we investigate a practical shelf space allocation model which takes into account the number of facings, capping, and nesting of a product. We divide the shelf into the segments of variable size in which the products of the specific types could be placed. The interconnections between products are modelled with the help of categorizing the products into specific types as well as grouping some of them into clusters. This results in four groups of constraints—shelf constraints, shelf type constraints, product constraints, position allocation constraints—that are used in the model for aesthetic symmetry of a planogram. We propose a simulated annealing algorithm with improvement and reallocation procedures to solve the planogram profit maximization problem. Experiments are based on artificial data sets that have been generated according to real-world conditions. The efficiency of the designed algorithm has been estimated using the CPLEX solver. The computational tests demonstrate that the proposed algorithm gives valuable results in an acceptable time.

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Section: Shelf Space Allocation Decisionsmentioning

confidence: 99%

“…Constraint ( 24) ensures tags compatibility. Constraint (25) shows that non-specific product is assigned to the subset A or B if it is placed on a pallet, low-level or eye-level shelf. The same is for local and convenience shelves (constraint ( 26)).…”

Section: Shelf Segment Constraintsmentioning

confidence: 99%

Simulated Annealing Hyper-Heuristic for a Shelf Space Allocation on Symmetrical Planograms Problem

Czerniachowska

Hernes

2021

Symmetry

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A genetic algorithm for the retail shelf space allocation problem with virtual segments

Czerniachowska

2021

OPSEARCH

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A hyper-heuristic approach to the strategic planning of bike-sharing infrastructure

Cheng

Zhong

Wang

et al. 2022

Computers & Industrial Engineering

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A reduced variable neighborhood search-based hyperheuristic for the shelf space allocation problem

Cited by 7 publications

References 36 publications

Simulated Annealing Hyper-Heuristic for a Shelf Space Allocation on Symmetrical Planograms Problem

Simulated Annealing Hyper-Heuristic for a Shelf Space Allocation on Symmetrical Planograms Problem

A genetic algorithm for the retail shelf space allocation problem with virtual segments

A hyper-heuristic approach to the strategic planning of bike-sharing infrastructure

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