Resources planning for container terminal in a maritime supply chain using multiple particle swarms optimization (MPSO)

Abstract

Resources planning is an important task in a supply chain in order to achieve a good result. The better the utilization of resources, especially scarce resources, the better the performance of a supply chain. This research focuses on allocating two scarce resources, i.e., berth and quay cranes (QCs), to ships that call at a container terminal in a maritime supply chain. As global container shipments continue to grow, improving the efficiency of container terminals is important. A two-stage approach is used to find the optimal/near-optimal solution, in which the first stage is devoted to generating alternative ship placement sequences as inputs to the second stage that subsequently employs an event-based heuristic to place ships, resolve overlaps of ships, and assign/adjust QCs so as to develop a feasible solution. For identifying a better approach, various heuristics/metaheuristics, including first-come first-served (FCFS), particle swarm optimization (PSO), improved PSO (PSO2), and multiple PSO (MPSO), have been employed in the first stage, respectively. The experimental results show that combining the MPSO with the event-based heuristic leads to a better result.