Adaptive metaheuristics for pickup and delivery problems in humanitarian logistics

• Grant number: 23/03627-6
• Support Opportunities: Scholarships abroad - Research Internship - Scientific Initiation
• Start date: June 01, 2023
• End date: August 31, 2023
• Field of knowledge: Engineering - Production Engineering - Operational Research
• Principal Investigator: Pedro Augusto Munari Junior
• Grantee: Eduardo Fechus Beker Reis
• Supervisor: Douglas José Alem Júnior
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Institution abroad: University of Edinburgh, Scotland
• Associated to the scholarship: 21/13246-4 - Adaptive metaheuristics for the pickup and delivery problem with time windows, BP.IC

Abstract

Pickup and Delivery Problems (PDPs) are variants of the vehicle routing problem which involves determining minimum-cost routes to collect goods or individuals and deliver them to their destinations. They have been widely applied to model and solve many situations that arise in real-world logistic operations, mainly focused on commercial logistics (CL). However, the approaches proposed so far may fail to properly represent and provide effective solutions for situations that emerge from humanitarian logistics (HL). Applications in HL differ from those in CL because the focus shifts from cost reduction to, e.g., the maximization of victims' welfare and the design of routes in the circumstances of catastrophic events, such as flooding and landslides. Hence, the models and solution approaches in HL often require different types of objectives and requirements that are not present in CL applications. In this project, we design models and metaheuristic methods for PDPs that arise from HL, seeking to effectively solve these problems in low computational times. These approaches will be based on extensions of those developed for the traditional PDP with time windows, addressed in the main project related to this proposal, and will complement the contributions of the overall study. This research will be conducted under the supervision of Prof. Douglas Alem from the Business School of the University of Edinburgh, who is an expert in modelling and solving HL problems. (AU)