Flower-cutting heuristics for shelf space allocation problem with simultaneous vertical and horizontal product categorization on the retail store shelves

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.