LS/ATN: Reporting on a Successful Agent-Based Solution for Transport Logistics Optimization

Abstract

A considerable volume of research exists concerning the domain of automatic planning and scheduling, hut many real-world scheduling problems, and especially that of transportation logistics, remain difficult to solve. In particular, this domain demands schedule-solving for every vehicle in a transportation fleet where pick-up and delivery of customer orders is distributed across multiple geographic locations, while satisfying time-window constraints on pickup and delivery per location. This paper presents a successful commercial-grade solution to this problem called living systems adaptive transportation networks (LS/ATN), which has been proven through real-world deployment to reduce transportation costs through the optimization of route solving for both small and large fleets. LS/ATN is a novel agent-based resource management and decision system designed to address this highly dynamic and complex domain in commercial settings. We show how LS/ATN employs agent cooperation algorithms to derive truck schedules that optimize the use of available resources leading to significant cost savings. The solution is designed to support, rather than replace, the day-to-day activities of human dispatchers