Reducing truck emissions at container terminals in a low carbon economy: Proposal of a queueing-based bi-objective model for optimizing truck arrival pattern

• Truck waiting time and idling emissions at a container terminal are estimated via queuing network.
• Queuing network are non-stationary and solved with fluid flow based approximations.
• Bi-objective optimization is employed to find optimal truck arrival patterns.
• Optimization objective is to minimize both truck idling emission and truck arrival intervention simultaneously.

This study proposes a methodology to optimize truck arrival patterns to reduce emissions from idling truck engines at marine container terminals. A bi-objective model is developed minimizing both truck waiting times and truck arrival pattern change. The truck waiting time is estimated via a queueing network. Based on the waiting time, truck idling emissions are estimated. The proposed methodology is evaluated with a case study, where truck arrival rates vary over time. We propose a Genetic Algorithm based heuristic to solve the resulting problem. Result shows that, a small shift of truck arrivals can significantly reduce truck emissions, especially at the gate.