L2M – Smart Logistics Optimization System Using Artificial Intelligence

The logistics industry faces significant inefficiencies due to lengthy planning and dispatching re-optimization processes, resulting in delays, increased compensations, and suboptimal transit times. These challenges arise from difficulties in assessing resource status, managing incoming requests, and coordinating communication between dispatchers, drivers, and resources. Our smart logistics optimization system leverages real-time data and advanced Artificial Intelligence algorithms to optimize resource dispatching, thereby improving overall operational efficiency and significantly reducing planning times. By adapting to real-world conditions, our system ensures efficient resource use, minimizing downtime and maximizing productivity. Improved visibility into the supply chain allows for proactive problem-solving, preventing issues before they become significant. This leads to timely deliveries and consistent service quality, resulting in higher customer satisfaction.

Faculty Supervisor:

Xin Wang

Student:

Partner:

Edmonton Unlimited

Discipline:

Engineering

Sector:

Professional, scientific and technical services; Public administration

University:

University of Calgary

Program: