Bi-objective optimization for integrating quay crane and internal truck assignment with challenges of trucks sharing

Abstract

Due to both the rapid growth of world and the expansion of the flow of container shipment, a maritime container terminal plays a vital role in global coverage of supply chain. In this market, because shipping is growing fast, container terminals should be able to serve the vessels in the shortest possible time. Alternatively, the limited availability of operational facilities, such as internal trucks, makes servicing more complicated in container terminals. Therefore, this study aimed to integrate the assignment of quay cranes in container terminals and internal truck sharing assignment among them. For this purpose, a bi-objective optimization model is developed. In the proposed model, several assignment phases, including the assignments of the vessel to container terminals, cranes to terminals, cranes to vessels and trucks to cranes are performed. The model also seeks to increase and improve the efficiency and effectiveness of internal trucks by sharing them among different terminals, so that there is an appropriate balance between the volume of workloads of the terminals and the trucks in question. The first objective function in the proposed model seeks to minimize operational costs and the second objective function seeks to minimize the maximum overflowed workload in the terminals. Furthermore, in order to solve the proposed model, two meta-heuristic multi-objective algorithms, including modified non-dominated sorting genetic algorithm-II (MNSGA-II) and modified multi-objective particle swarm optimization (MMOPSO) are presented. Several numerical examples have been investigated and analyzed to show the accuracy of the proposed model and the methods. In addition, the results demonstrated that the simultaneous consideration of the assignments and the sharing of trucks would reduce the remaining workload in the terminals.