The vending machine deployment and shelf display problem: A bi-layer optimization approach

Kung-Jeng Wang and Natalia Febri

Transportation Research Part E: Logistics and Transportation Review, 2024, vol. 187, issue C

Abstract: The vending machine has become one of the non-store marketing channels to generate sales and give consumers convenient services. However, the logistics decisions in the vending machine service industry are challenging, coupled with complex constraints, considering the machine deployment location, product selection, shelf display allocation, and the elasticity of demands and spaces. This paper presents a bi-layer optimization model addressing the challenges associated with deployment location, product selection, and shelf display for a vending machine system consisting of more than ten thousand vending machines. The upper layer model selects appropriate locations for machine deployment, while the lower layer model considers product selection and shelf display in individual machines. Due to the high complexity of the problem, metaheuristic approaches are developed for seeking near-optimal solutions. The proposed model and algorithms are evaluated using various scales of problems, demonstrating their effectiveness in delivering premium logistics and operational solutions. Additionally, the study explores the impact of product cross and space elasticities. The proposed two-level genetic algorithm consistently performs better than Tabu search and Particle swarm optimization in small-scale and large-scale cases. The proposed approach can significantly enhance profitability for large-scale vending machine deployment in the vending machine service industry.

Keywords: Bi-layer optimization; Vending machine; Machine location; Product selection; Shelf display; Elasticity; Genetic algorithm (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.tre.2024.103581

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