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Dynamic Decision Making for Less-Than-Truckload Trucking Operations

Principal Investigator(s) 

Behrang Hejazi, Ph.D. Candidate

Among different modes of transportation, trucking remains the shipping choice for many businesses and is increasing its market share. Less-than-truckload (LTL) trucking companies provide consolidated transportation, where several customers are served simultaneously by using the same truck, and shipments need to be consolidated at some terminals to build economical loads.

Intelligent transportation system (ITS) technologies offer the possibility to control the operations in real-time. Prior research efforts have considered real-time acceptance/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.

The research presents a mathematical formulation for the problem. A decision making procedure, as well as a decision support application have been developed, which is used to handle the LTL shipment requests. Using exact methods to solve the MIP problem the execution time grows quickly with problem size. Our next step in this study is to introduce alternative methods and algorithms to solve the MIP problem.