Green pickup and delivery problems under demand and travel time uncertainty

• Grant number: 23/08678-8
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree
• Effective date (Start): October 01, 2023
• Effective date (End): March 31, 2024
• Field of knowledge: Engineering - Production Engineering - Operational Research
• Principal Investigator: Pedro Augusto Munari Junior
• Grantee: Alex Paranahyba de Abreu
• Supervisor: Maria Battarra
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Research place: University of Bath, England
• Associated to the scholarship: 22/10993-6 - Vehicle routing problems with pickup and delivery under travel time and demand uncertainty, BP.MS

Abstract

We address green variants of the vehicle routing problem with pickup and delivery requests, considering uncertainty on demand and travel times. These variants align with current sustainability practices aimed at reducing CO2 emissions by providing less polluting routes. Our focus is on extending the pickup and delivery problem (PDP), which has gained popularity due to its practical applications in carrier services, meal delivery, load transportation in offshore terminals, and disaster relief operations. The PDP involves routing a set of transportation requests from pickup to drop-off locations. We aim at proposing new mathematical models and exact solution approaches that consider the pollutant emissions of conventional vehicles and incorporate the usage of electric vehicles in the PDP. This integration aims to reduce the environmental impacts caused by transportation in urban areas. Furthermore, we intend to address data uncertainty via robust optimization to promote a more effective use of vehicles and prevent the designed routes from becoming infeasible or excessively polluting in the presence of unexpected events. Therefore, this research aims to build efficient solution approaches that support decision-making in the presence of data uncertainty while considering sustainability objectives, resulting in robust green PDP variants. (AU)