An Exact Approach to the Multi-Compartment Vehicle Routing Problem: The Case of a Fuel Distribution Company

Guilherme Baptista, Miguel Vieira and Telmo Pinto ()
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Guilherme Baptista: University of Coimbra, Centre for Mechanical Engineering, Materials and Processes, ARISE, 3004-531 Coimbra, Portugal
Miguel Vieira: University of Coimbra, Centre for Mechanical Engineering, Materials and Processes, ARISE, 3004-531 Coimbra, Portugal
Telmo Pinto: University of Coimbra, Centre for Mechanical Engineering, Materials and Processes, ARISE, 3004-531 Coimbra, Portugal

Mathematics, 2024, vol. 12, issue 4, 1-14

Abstract: Over the years, the vehicle routing problem has been studied by several authors, creating several extensions, such as the multi-compartment vehicle routing problem. Several studies in the literature have addressed this problem, but few have solved it through exact approaches owing to model convolution. In this way, a mathematical model is proposed for the multi-compartment vehicle routing problem with time windows, in which three types of fuel products are distributed to a set of customers using a limited homogeneous fleet. The model explicitly considers time windows, as well as regulatory rest times for the drivers and time limits for each trip and for working schedules, addressing a real company’s decision support requirements, which is scarce in the literature. The optimal solution determines, for each vehicle, the distribution route and time to carry out the deliveries with the corresponding loading of products to compartments, complemented by the calculation of carbon emissions. The main objective is to minimize the total distance traveled, which corresponds to the sum of the distances traveled by each one of the allocated vehicles. The results allow the assessment of the solution optimization applied to a set of instances for a Portuguese company to evaluate the performance and compare decision support improvements with current baseline company procedures.

Keywords: vehicle routing problem; multi-compartment vehicles; mixed-integer programming; distribution sector; carbon emissions (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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