Adaptive particle swarm optimization for integrated quay crane and yard truck scheduling problem

Abstract

This thesis tackles the integrated Quay Crane and Yard Truck scheduling problem at container terminal, considering practical conditions as well as specific requirements of Cat Lai Terminal. In particular, the study takes into account the unloading process of inbound containers, which means the Yard Truck transports required containers to the container yard then return to the Quay Crane without carrying exported containers. Regarding the study’s objective, an optimal schedule for Quay Crane and Yard Truck is planned, especially the joint schedule of those two facilities. In order to achieve that objective, a mixed – integer programming is formulated to minimize the makespan, the time to complete the unloading and transporting operations of all required containers. Moreover, the modified Particle Swarm Optimization (PSO) algorithm is introduced and developed to address this issue. For the small sized problem, the mixed – integer programming is solved by using CPLEX IBM LOG 12.8.0. On the other hand, the improved PSO will tackle the large sized problem because CPLEX could not solve that issue in reasonable time. Experimental result shows that the proposed PSO is significantly efficient to address the integrated Quay Crane and Yard Truck scheduling problem for unloading inbound containers at Cat Lai Terminal as well as other Container Terminals. Keywords: Joint schedule, Quay Crane, Yard Truck, mixed – integer programming, Particle Swarm Optimization algorithm (PSO).