Berth allocation problem with uncertain vessel handling times considering weather conditions

被引:41
作者
Guo, Liming [1 ]
Wang, Jun [1 ]
Zheng, Jianfeng [1 ]
机构
[1] Dalian Maritime Univ, Transportat Engn Coll, Dalian, Peoples R China
基金
中国国家自然科学基金;
关键词
Berth allocation; Weather conditions; Particle swarm optimization; Machine learning; CRANE ASSIGNMENT; CONTAINER TERMINALS; FUEL CONSUMPTION; MODEL; ALGORITHM; ARRIVAL; SEARCH; DESIGN;
D O I
10.1016/j.cie.2021.107417
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页数:17
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