Classical and Quantum Metaheuristic Optimization Tools to Improve the Constrained Vehicle Routing Problem Solutions

The constrained vehicle routing problem is a typical optimization problem with many real-life applications, such as last-mile route planning for delivery services. The goal is to find the optimal routes for a set of vehicles to deliver all the packages, such that the time and cost of delivery is minimized, sometimes with additional constraints such as a loading capacity for each vehicle. In recent years, quantum computing has started to show great potential in providing a speedup to optimization solutions. This project aims to understand the current state-of-the-art classical solutions to the vehicle routing problem and explore the application of quantum computing in this field, with the hope of developing a quantum hybrid algorithm that a customer will eventually use to improve their logistics planning.

Faculty Supervisor:

Christopher Beck

Student:

Partner:

ForeQast Technologies Limited

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program: