Vehicle Routing Optimization
About the company
Quick is a logistics digital platform specialized in Inventory, Transportation and Distribution. Outside of Colombia they operate in Brazil, Chile and Mexico and cover 78 cities in Latin America. Some of their clients are major corporations such as L'Oréal, Unilever, Johnson & Johnson, Nutresa, Homecenter, etc.
This Challenge is based on the case of one of the most important clients of Quick. The objective is to develop a software that optimizes Quick's vehicles routing to deliver more than 200 customers from 15 different warehouses in Bogotá. The software has to automatically decide for each vehicle which warehouses and customers to visit and when, in order to minimize costs and maximize service level.
less vehicles required
compliance with customers' schedules
new insightful performance indicators
A word from the professor
The Vehicle Routing Problem is known to be very complex to optimize. For instance, a problem with only 60 clients leads to more than one icosipentillion combinations (imagine a number with 75 zeros !). To solve this problem, our students combined many optimization algorithms: state of the art metaheuristics and heuristics of their own design. They implemented hybrid techniques such as mutli-stage and high-level relay hybrid. To be less technical, this means that they created a synergy between algorithms that are fast but not so accurate and algorithms that are accurate but rather slow. In the world of Operations Research, this is one of our magic tricks behind finding a very good solution in the shortest time possible.
Prof. Rabie Nait-Abdallah
Leader of the Challenge