MATHEMATICAL FORMULATION FOR DISTRIBUTION CENTER ALLOCATION: A CASE STUDY IN THE BICYCLE SECTOR

The allocation of distribution centers (DCs) is one of the most strategic decisions in modern logistics management, exerting a direct impact on service levels, operating costs and business competitiveness. The choice of suitable locations for DCs must consider several factors, such as proximity to consumer markets, transportation costs, available infrastructure, service capacity, and even regional incentive policies. Incorrect choices can compromise supply chain efficiency, lead to delays, increase waste, and reduce customer satisfaction. Quantitative methods have been widely used to support location decisions, with emphasis on programming and optimization methods, which provide an abstract representation of the allocation problem and optimized solutions. This work presents a mixed integer programming model for the problem of DC allocation, with application in a Colombian company in the bicycle import and commercialization sector. The model encompasses the minimization of the total cost of the logistics operation, incorporating allocation costs, maritime and land transport, capacity limitations, budgets and incentives to meet new demands. Computational experiments were carried out with real data from the company, involving intercity distances, demand volumes and operating costs. Three economic incentive scenarios and two port origins were considered to validate the mathematical model.