Research & Projects

Abstract

Route optimization in logistics transportation is a complex effort which requires consistent adjustments to ever changing variables.  The demand for timely deliveries, cost effectiveness and fulfilled expectations have been the driving force behind innovation in this area of logistics.  Recently, the trajectory of that innovation has increased dramatically as advances in Artificial Intelligence and our interaction with it have fueled the pace of its technological development.  In lieu of that, this research begins with organizing and quantifying that trajectory by reviewing route optimization and AI fundamentals, by examining traditional methods for optimizing routes, how AI is currently being used in that process and what literary gaps exist on the topic.  It culminates with an examination of how AI as we know it and how the AI of the future can drive further innovation in route optimization.  Given that AI advancements currently seem to be fluid and evolving, particular attention has been paid to academic and industry publications that are recent and likely more relevant from both a qualitative and quantitative perspective.  Additionally, particular attention has been paid to diversity in logistics transportation use cases so that similarities and differences in route optimization strategies can be examined (i.e. e-bikes and advanced air mobility vs. box trucks and container ships).  The result of this research is thus expected to be a comprehensive analysis of where the field has been, where it currently is, and where it is going with respect to route optimization and AI’s ability to enhance it.