Berth allocation problem with uncertain vessel handling times considering weather conditions. (August 2021)

• Record Type: Journal Article
• Authors: Guo, Liming; Wang, Jun; Zheng, Jianfeng
• Is Part Of: Computers & industrial engineering. Volume 158(2021)
• Publication Date: 2021-08
• Subjects: Berth allocation -- Weather conditions -- Particle swarm optimization -- Machine learning; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2021.107417
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Propose a berth allocation problem with ship handling time uncertainty considering the influence of weather conditions. Propose a mixed-integer programming model. Propose an efficient PSO algorithm embedded with machine learning for solving our proposed model. Abstract: The vessel handling times at container terminals can be inevitably affected by weather conditions. This study proposes a berth allocation problem (BAP) with vessel handling time uncertainty considering the impact of weather conditions, which is seldom considered in the previous studies on BAPs. A two-stage optimization method, which focuses on the evaluation of vessel handling time under different weather conditions, is developed for addressing our BAP. In stage I, we determine the vessel handling times considering the influence of weather conditions. Based on the vessel handling times obtained in stage I, stage II presents a mixed-integer programming (MIP) model for solving the BAP. Moreover, an efficient particle swarm optimization algorithm embedded with machine learning approach is devised for solving the BAP model in large-scale problem cases. Numerical experiments are carried out to assess the effectiveness of the proposed model and the efficiency of the proposed algorithm.