Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.tre.2017.07.006
Title: A bi-objective robust model for berth allocation scheduling under uncertainty
Authors: Xiang, Xi
Liu, Changchun 
Miao, Lixin
Keywords: Social Sciences
Science & Technology
Technology
Economics
Engineering, Civil
Operations Research & Management Science
Transportation
Transportation Science & Technology
Business & Economics
Engineering
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
Issue Date: 1-Oct-2017
Publisher: PERGAMON-ELSEVIER SCIENCE LTD
Citation: Xiang, Xi, Liu, Changchun, Miao, Lixin (2017-10-01). A bi-objective robust model for berth allocation scheduling under uncertainty. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 106 (C) : 294-319. ScholarBank@NUS Repository. https://doi.org/10.1016/j.tre.2017.07.006
Abstract: © 2017 Elsevier Ltd 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.
Source Title: TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
URI: https://scholarbank.nus.edu.sg/handle/10635/155206
ISSN: 1366-5545
DOI: 10.1016/j.tre.2017.07.006
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