Self-organizing Logistics Networks for Less-Than-Truckload

Modeling of Collaborative Less-than-truckload Carrier Freight Networks

Dynamic Decision Making for Less-than-truckload Trucking Operations

Title of Dissertation: DYNAMIC DECISION MAKING FOR LESS-THAN-TRUCKLOAD TRUCKING OPERATIONS Behrang Hejazi, Doctor of Philosophy, 2009 Directed By: Professor Ali Haghani Department of Civil and Environmental Engineering On a typical day, more than 53 million tons of goods valued at about $36 million are moved on the US multimodal transportation network. An efficient freight transportation indust...

A dynamic driver management scheme for less-than-truckload carriers

This paper describes a scheme for the dynamic management of linehaul drivers developed for a large U.S. LTL carrier. Virtually all scheduling problems faced by transportation service providers are complicated by time-constrained vehicle operators that can be renewed only after resting. LTL driver scheduling is further complicated by the fact that trucking moves, unlike passenger airline flights...

Self-organizing logistics systems

When a logistics system is “self-organizing” it can function without significant intervention by managers, engineers, or software control. The social insects, such as ants or bees, provide models of self-organizing logistics systems that may be profitably emulated. We illustrate some of these ideas for the problem of balancing assembly lines.

Robust dock assignments at less-than-truckload terminals

Less-than-truckload industry has a valuable potential for applications of operations research in two areas, network design and efficiency improvement within existing networks. This thesis focuses on the latter, specifically the less-than-truckload terminals where cross docking operations occur. The assignment of incoming trailers to inbound docks is one of the critical decisions that affect the...