Issue: 2026/Vol.36/No.3, Pages
FLOWER-CUTTING HEURISTICS FOR SHELF SPACE ALLOCATION PROBLEM WITH SIMULTANEOUS VERTICAL AND HORIZONTAL PRODUCT CATEGORIZATION ON THE RETAIL STORE SHELVES
Kateryna Czerniachowska
This is not yet the definitive version of the paper. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article.
Cite as: K. Czerniachowska. Flower-cutting heuristics for shelf space allocation problem with simultaneous vertical and horizontal product categorization on the retail store shelves. Operations Research and Decisions 2026: 36(3). DOI 10.37190/ord/218947
Abstract
We address the retail shelf space allocation problem, which incorporates product simultaneous categorization across horizontal and vertical shelves. The problem also includes products with varying storage conditions and limited compatibility to be sold nearby. Our mathematical model focuses on optimizing the visibility of the products on the shelves in the retail store. We introduce a novel flower-cutting heuristic, which employs two variations of internal sorting rules. Seventeen parameters were used to narrow the solution space and generate efficient solutions without relying on randomization or exhaustive searches. When compared to optimal solutions obtained from a commercial solver, our approach yields solutions with 98.58\%-100\% accuracy. Optimal solutions were achieved for 17 out of 25 instances using both heuristics. The developed heuristics offer an approach that focuses on optimizing resource allocation problems.
Keywords: heuristics, shelf space allocation, retail store, knapsack problem, decision making/process
Received: 27 July 2025 Accepted: 6 March 2026
Published online: 7 March 2026