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An integrated approach to vehicle routing and container loading problems under uncertainty

Grant number: 23/16405-1
Support Opportunities:Scholarships in Brazil - Post-Doctoral
Effective date (Start): April 01, 2024
Effective date (End): March 31, 2026
Field of knowledge:Engineering - Production Engineering - Operational Research
Principal Investigator:Franklina Maria Bragion de Toledo
Grantee:Douglas Nogueira Do Nascimento
Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

The aim of this research project is to study the integration of the Vehicle Routing Problem (VRP) with the Container Loading Problem (CLP), considering a heterogeneous fleet with alcohol/petrol and electric vehicles, and a cargo consisting of three-dimensional items. This integrated problem, known in the literature as 3L-VRP, is challenging as it combines the cost minimization of vehicle routes with the maximization of efficiency in the three-dimensional loading of containers. To this problem, we incorporate uncertainties in travel times, which are critical factors in the distribution in megacities. Two global trends, urbanization, and e-commerce have significantly boosted road transport, in particular the demand for last-mile delivery services. In this context, environmental impact is a growing concern, as the increase in demand for urban deliveries results in a greater number of delivery vehicles circulating in city centers. Operations research literature has contributed to solving these challenges by optimizing distribution operations along three main axes: (i) integrating the resolution of the vehicle routing problem with the vehicle loading problem; (ii) considering mixed fleets, with vehicles with conventional combustion engines and electric vehicles; (iii) considering uncertainty in travel times. However, these three axes have not intersected, thus preventing the potential for improvement that they bring from being fully exploited. The aim of this project is to consider these three axes simultaneously for the first time. The VRP involves determining the most efficient routes for a fleet of vehicles to attend to a set of customers and optimizing criteria such as cost or time. The CLP, on the other hand, focuses on the efficient allocation of items to be loaded into containers, considering geometric and capacity constraints. Integrating these two problems is of great practical relevance, as the efficiency in load allocation directly impacts the effectiveness of delivery routes. Both problems, fundamental in optimizing logistics operations, are traditionally addressed in a deterministic context and with a homogeneous fleet of vehicles. In this research work, we will seek to reduce costs and the environmental impact of delivery routes. In this way, by solving the problem in an integrated way, we aim to make better use of the space available for delivery (packing) and also reduce greenhouse gas emissions, including electric vehicles in the planning. Therefore, the fleet will be heterogeneous, considering combustion and electric vehicles. In addition, we will also address uncertainties regarding travel times. Thus, this research aims to fill an important research gap: developing exact and heuristic solution methods for VRP-CLP integration, using a mixed fleet and under uncertainties, that present optimal solutions and/or good quality heuristic solutions in an acceptable resolution time for real situations. In this way, we intend to generate less polluting and robust solutions capable of dealing with unforeseen scenarios. The efficiency of the methods developed will be evaluated through computational experiments with randomly generated data and data from the literature.

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