Dynamic Decision Making for Less-Than-Truckload Trucking Operations

Of modes of transportation, trucking remains the shipping choice for many businesses, and its market share is increasing. Less-than-truckload (LTL) trucking companies provide consolidated transportation whereby several customers are served simultaneously by the same truck, and shipments need to be consolidated at terminals to build economical loads. Intelligent transportation system technologies offer the possibility of con-trolling the operations in real time. Prior research efforts have considered real-time acceptance or rejection of shipping requests, but mostly have focused on truckload trucking operations. This study attempts to use real-time information in decision making for LTL carriers in the dynamic environment and presents a mathematical formulation for solving the problem. A decision-making procedure and a decision-support application are developed and presented. Numerical experiments are constructed to study the behavior of the system under different demand and supply situations to check the accuracy of the mathematical problem, and to study the characteristics of the LTL trucking operations.