A bi-objective robust model for berth allocation scheduling under uncertainty

被引：77
|
作者：
Xiang Xi [1 ,2 ]
Liu Changchun [1 ]
Miao Lixin [2 ,3 ]
机构：
[1] Tsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Grad Sch Shenzhen, Div Logist & Transportat, Shenzhen 518055, Peoples R China
[3] Tsinghua Berkeley Shenzhen Inst, Intelligent Transportat & Logist Syst Lab, Shenzhen 518055, Peoples R China
来源：
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW | 2017年 / 106卷
基金：
中国国家自然科学基金;
关键词：
Container terminals; Berth allocation scheduling problem; Robust optimization; Adaptive grey wolf optimizer algorithm; Uncertainty; GREY WOLF OPTIMIZER; CONTAINER TERMINALS; OPERATIONS-RESEARCH; HANDLING TIME; TABU SEARCH; PORT; FORMULATION; HEURISTICS; ALGORITHM;
D O I：
10.1016/j.tre.2017.07.006
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
This study examines the berth allocation problem with the consideration of uncertainty factors, including the arrival and operation times of the calling vessels. A bi-objective robust berth allocation model, which focuses on economic performance and customer satisfaction, is formulated. The model aims to optimize the robustness of the berth allocation policy, and an adaptive grey wolf optimizer algorithm is developed to solve the proposed model. The performance of the heuristic is evaluated through randomly generated instances. Experimental results show that the proposed heuristic provides good solution quality and calculation efficiency. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码：294 / 319
页数：26
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