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The synergistic effect of operational research and big data analytics in greening container terminal operations: A review and future directions

期刊

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
卷 310, 期 3, 页码 943-973

出版社

ELSEVIER
DOI: 10.1016/j.ejor.2022.11.054

关键词

OR in maritime industry; Container terminal operations; Big data; Analytics; Environmental considerations

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Container Terminals (CTs) are facing complex planning tasks and environmental pressures. This paper reviews the developments in this field and identifies research opportunities for better exploitation of environmental considerations and data utilization.
Container Terminals (CTs) are continuously presented with highly interrelated, complex, and uncertain planning tasks. The ever-increasing intensity of operations at CTs in recent years has also resulted in in-creasing environmental concerns, and they are experiencing an unprecedented pressure to lower their emissions. Operational Research (OR), as a key player in the optimisation of the complex decision prob-lems that arise from the quay and land side operations at CTs, has been therefore presented with new challenges and opportunities to incorporate environmental considerations into decision making and bet-ter utilise the 'big data' that is continuously generated from the never-stopping operations at CTs. The state-of-the-art literature on OR's incorporation of environmental considerations and its interplay with Big Data Analytics (BDA) is, however, still very much underdeveloped, fragmented, and divergent, and a guiding framework is completely missing. This paper presents a review of the most relevant develop-ments in the field and sheds light on promising research opportunities for the better exploitation of the synergistic effect of the two disciplines in addressing CT operational problems, while incorporating un-certainty and environmental concerns efficiently. The paper finds that while OR has thus far contributed to improving the environmental performance of CTs (rather implicitly), this can be much further stepped up with more explicit incorporation of environmental considerations and better exploitation of BDA pre-dictive modelling capabilities. New interdisciplinary research at the intersection of conventional CT opti-misation problems, energy management and sizing, and net-zero technology and energy vectors adoption is also presented as a prominent line of future research.& COPY; 2022 The Author(s). Published by Elsevier B.V.This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

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