Today, fleet optimization is a very manual process done by planners and fleet managers. This process takes additional time and cost while introducing significant bias (i.e., preferred carriers).
Goals and Objectives
The goal of dynamic fleet optimization is to optimize fleet capacity, thus saving costs by reducing miles, lowering fuel expenses, and improving vehicle maintenance and longevity.
Enterprise hardware, cloud applications, network optimization software, and fleet management systems (FMS)
Use Case Summary
Machine learning algorithms build an accurate model of private fleet capacity, including physical asset constraints as well as driver availability, hours of service, and fleet maintenance. This allows planners and fleet managers to optimize fleet capacity.