Swarm Optimization With Intra- and Inter-Hierarchical Competition for Large-Scale Berth Allocation and Crane Assignment

Yanghe Zou, Peilan Xu, Hao Dai, Heng Song, Wenjian Luo

Abstract: The trend of global economic integration has fostered the prosperity of the maritime transportation industry, which has placed higher demands on the construction of automated container terminals, and the optimization of the integrated berth allocation and crane assignment problems (BACAPs) is a key link. Currently, population-based computational intelligence methods have attracted attention on BACAPs, but on small-scale cases and simplified problem models. In this paper, we propose a novel swarm optimization with intra- and inter-hierarchical competition (I2HCSO) for addressing large-scale BACAPs, which is a major challenge in container terminals. First, we construct a hierarchical model with better particles at the higher hierarchy, and the populations at different hierarchies are divided into several sub-swarm. Then, we design an intra- and inter-hierarchical competitive mechanism to balance the exploration and exploitation of the population, in which intra-hierarchical competition is carried out within sub-swarm at any hierarchy, whereas inter-hierarchical competition occurs in different sub-swarms of neighboring hierarchies. Third, we consider optimizing the priorities of vessels for efficient use of resources berth and crane for the first time in BACAPs and employ $\varepsilon$-constraints to search for feasible regions. Additionally, we develop a local search operator as a repair strategy to improve the quality of the solution. Finally, we test I2HCSO in a set of cases consisting of 25 BACAPs. Compared with the several typical optimizers with experimental results, I2HCSO is more competitive on BACAPs with different scales.

External IDs:dblp:journals/tetci/ZouXDSL25