Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/25727
Title: The synergistic effect of operational research and big data analytics in greening container terminal operations: a review and future directions
Authors: Raeesi, R
Sahebjamnia, N
Mansouri, SA
Keywords: OR in maritime industry;container terminal operations;big data;analytics;environmental considerations
Issue Date: 5-Dec-2022
Publisher: Elsevier
Citation: Raeesi, R Sahebjamnia, N. and Mansouri, S.A. (2023) 'The synergistic effect of operational research and big data analytics in greening container terminal operations: a review and future directions', European Journal of Operational Research, 310 (3), pp. 943 - 973. doi: 10.1016/j.ejor.2022.11.054
Abstract: Copyright © 2022 The Author(s). 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 increasing 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 problems 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 better 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 developments 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 uncertainty 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 predictive modelling capabilities. New interdisciplinary research at the intersection of conventional CT optimisation problems, energy management and sizing, and net-zero technology and energy vectors adoption is also presented as a prominent line of future research.
URI: https://bura.brunel.ac.uk/handle/2438/25727
DOI: https://doi.org/10.1016/j.ejor.2022.11.054
ISSN: 0377-2217
Other Identifiers: ORCID iD: Ramin Raeesi https://orcid.org/0000-0002-9267-8294
ORCID iD Navid Sahebjamnia https://orcid.org/0000-0001-5727-9477
ORCID iD: Afshin Mansouri https://orcid.org/0000-0002-1488-7912
Appears in Collections:Brunel Business School Research Papers

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