Local container drayage problem with improved truck platooning operations

Abstract

Truck platooning has been identified as a promising technology to save labor force for the local container drayage problem (LCDP). However, existing studies for the platoon-based LCDP assumed that each driver was attached to respective leading truck throughout the service process, and the driverless following trucks dropped off at customer sites cannot further serve the drayage requests until regaining guidance, resulting in low efficiency and utilization of drivers and trucks. To overcome this issue, this paper examines the LCDP under a novel improved platooning operation mode (IPOM), where the drivers are not necessarily attached to their respective leading trucks but can move by alternative transport modes to perform subsequent tasks. The objective is to determine the optimal numbers, routes, and schedules of the drivers and trucks that minimize the total operational cost to complete all the delivery and pickup requests of customers. A mixed-integer linear programming (MILP) model is developed to capture the features pertaining to the new platooning mode. A heuristic construction method incorporating simulated annealing is proposed to solve the problem. Numerical experiments are carried out to evaluate the proposed model and solution method and quantify the advantages of the improved platooning mode. Sensitivity analysis is also conducted to explore the impacts of some major influential factors on the system performance and derive managerial insights.