An Efficient Algorithm for the Berth and Quay Crane Assignments Considering Operator Performance in Container Terminal Using Particle Swarm Model

Abstract

In the existing literature, the berthing operations, the quay crane assignments, and the scheduling problems were usually conducted without considering the worker performances (WPs) and the yard truck tasks (YTTs). However, professionals in situ corroborate the crucial effect of WPs and the yard YTTs on quay crane performance and efficiency. This study introduced a new feasible model for investigating the berth and the quay crane assignments based on the scheduling problem, including worker performances and yard truck deployment constraints. First, a mixed-integer programming (MIP) model is implemented to reduce the vessel’s departure time. Then, a particle swarm optimization (PSO) algorithm is introduced to solve the problems. The Dar es Salaam port is selected as a case study to test the proposed model with a real-time dataset that was collected from a multinational company managing container terminals. The results show the efficiency and the accuracy of the proposed model. The PSO algorithm is 86% and 62% more time-saving than MILP and T2S solutions for a small number of containers, respectively. Additionally, the PSO solution is 73% and 53% time-saving for a medium number of containers than MILP and T2S models, respectively. Finally, the present study proposes consideration of the worker assignment and the yard truck deployment during the planning phase.