Genetic Algorithm for the Retailers’ Shelf Space Allocation Profit Maximization Problem

This paper discusses the problem of retailers’ profit maximization regarding displaying products on planogram shelves, which may have different dimensions in each store but allocate same product sets. We develop a mathematical model and genetic algorithm for solving shelf space allocation with criteria maximization. The implemented program executes reasonable time. quality has been evaluated using CPLEX solver. determine four groups constraints that should be allocated shelf: constraints, type virtual segment constraints. validity developed checked 25 retailing test cases. Computational results prove proposed approach allows obtaining efficient short running time, complex model, considers multiple attributes shelf, segment, product, as well capping nesting rule, is high practical relevance. retailers to receive higher profits regard actual merchandising rules.