PROJECT SUMMARY

This position is within a project of the MOMENTUM program financed by the "Secretaría de Estado de Digitalización e Inteligencia Artificial – Ministerio para la Transformación Digital y de la Función Pública" by means of Red.es. Vehicle routing problems (VRPs) constitute an essential family of optimization problems in the logistics sector. Their goal is generally to design routes for an existing fleet of vehicles. This is done under certain constraints (such as time windows) and with various optimization goals (such as the traveled distance). Due to its vital role in the global economy, the logistics sector is a primary contributor to environmental pollution. This has motivated a recent shift towards replacing conventional vehicles with environmentally friendly ones (including electric ones), which has caused the complexity of the resulting green VRPs to increase. This poses a severe challenge to today's available exact and heuristic techniques for solving VRPs. Therefore, researchers have recently turned to machine learning (ML) to assist and improve VRP optimization algorithms. In this project, we aim to explore new options for combining ML techniques with heuristic and exact techniques for solving modern VRPs.

This project aims to contribute to optimization and machine learning in the context of VRPs. With that aim, the selected candidate will become part of the IIIA world-renowned research team working on optimization. Furthermore, the selected candidate will take part in international collaborations with leading groups in optimization. Finally, the selected candidate will enrol in a Master’s degree related to the project (worth 60 ECTS) and participate in training activities (such as courses and summer schools).