Integrated optimization for truck arrival management and yard capacity utilization in a container terminal

Truck congestion in a container terminal yard is usually caused by the imbalance between the arrival demand of external trucks and the supply of yard service capacity. In the absence of infrastructure expansions, the terminal yard congestion can only be mitigated by optimal control of truck arrivals and the management of yard resource allocation. This paper proposes an integrated modelling framework that mitigates terminal yard congestion by joint optimization of the truck arrival demand and the utilization of yard capacity, subject to truck arrival demand shifting, yard queueing, and yard resource allocation constraints. This integrated model consists of a truck demand management model that manages the distribution of truck arrivals over a planning horizon, a descriptive queueing model that captures the dynamics of truck arrival and service processes, and a yard capacity utilization model that controls the yard resource configuration and the consequent inbound and outbound truck service rates over time. For solving the integrated model, we develop a tailored iterative solution method that decomposes the demand and supply decisions and effectively strikes the balance between truck throughput and yard congestion level. A core contribution of this approach is the interaction between an expansion rule, which iteratively enriches the master problem’s restricted service option set with service rate configurations identified by the subproblem, and a dynamic update rule that strictly tightens the master problem’s congestion threshold. This mechanism is novel in the sense that it offers a convergent and tractable approach to coordinate the demand and supply management decisions that used to be intricate in the literature. We evaluate the computation performance and solution quality of the integrated framework on instances generated from the operational data of a large container terminal. Based on the computation results, we provide insights into truck demand and service management for congestion mitigation in a container terminal.