Master's Thesis : Optimization of pick-ups and deliveries in a circular economy system while respecting environmental and logistical constraints

Abstract

Nowadays, the resolutions of the Traveling Salesman Problem are extremely numerous and diverse and will likely continue to spread until the famous question "P versus NP" is answered. This thesis was realized in partnership with Usitoo, a Belgian object borrowing platform based in Brussels, and thus proposes a solution in a real case application. The goal of this work is to plan deliveries and retrievals of objects in the event that certain constraints have been relaxed. The most delicate constraint that was removed is the day of the journey, which considerably increases the number of possibilities to evaluate compared to a conventional Traveling Salesman Problem. The cost representing a journey was thought so that this metric best meets the environmental issue that we are trying to address with this thesis. The suggested solution involves both exhaustive search and genetic algorithms in order to respond to the request correctly but also quickly. The final proposed algorithm was implemented in Python. In this way, we hope to respond to the request of Usitoo through a Django website presenting the obtained results. With it, they will likely be able to continue to follow their eco-responsible vocation while remaining efficient.