Modeling and real-time optimization for sustainable and robust smart freight transportation platform

Urban freight transportation plays an essential role in the future of smart and sustainable cities. The emerging of e-commerce, new business models, and evolving technologies will affect logistics efficiency, policymaking, and planning in the freight transportation context. Smart freight platforms will be the next generation of shared mobility in global supply chain and logistics. It contributes to the sustainability of cities and all stakeholders involved in these platforms. This research project aims to develop the optimization models and learning based solutions for matching, pricing, repositioning and routing in this platform under uncertainties.

Faculty Supervisor:

Samira Keivanpour

Student:

Partner:

ShipHaul Logistics Inc.

Discipline:

Engineering

Sector:

Professional, scientific and technical services; Transportation and warehousing

University:

Polytechnique Montréal

Program: