Freight consolidation and container loading optimization

This project investigates a complex freight consolidation and loading problem faced by Frontline Carrier Systems Inc., a leading transportation and supply chain provider in North America. Frontline seeks to optimize their transportation costs by minimizing the number of trucks required to ship a set of customer orders within a finite planning horizon. The problem integrates freight consolidation decisions to assign skids to trucks, scheduling decisions to determine the departure time of truckloads, and three-dimensional (3D) loading decisions to determine how these skids should be placed inside each truck. Skids weight, volume and lead time constraints are considered to ensure feasibility and effective truck capacity utilization. The main objective is to develop algorithms based on the latest advances in artificial intelligence and analytics – including optimization, probability and statistics. These algorithms will be at the core of an advanced planning system capable of quickly generating feasible shipping plans and 3D animations of the truck loading patterns.

Faculty Supervisor:

Ivan Contreras

Student:

Aditya Malik

Partner:

Frontline Carrier Systems Inc

Discipline:

Other

Sector:

Transportation and warehousing

University:

Concordia University