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Zhang, L, Lu, J and Yang, Z (2020) Optimal scheduling of emergency resources for major maritime oil spills considering time-varying demand and transportation networks. European Journal of Operational Research, 293 (2). pp. 529-546. ISSN 0377-2217
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Optimal scheduling of emergency resources for major maritime oil spills considering time-varying demand and transportation networks.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (1MB) | Preview |
Abstract
During an emergency response to a major oil spill accident, the features of the motion of the oil films affect the response decisions. A highly dynamic optimal solution is needed to tackle the continuous changes in the demand for emergency resources and transportation networks for logistics deliveries that must occur. To effectively balance the responsiveness and the total response cost in emergency operations, this paper proposes a dynamic multi-objective location-routing model to address new challenges, such as the time-varying conditions in the response to oil spills and the interrelationship between the decision-making environment and emergency operations. Since the problem is NP-hard, to efficiently obtain Pareto solutions, a novel implementation of a heuristic framework based on particle swarm optimization is developed to conduct numerical experiments. Additionally, to handle the multi-objective model, an alternative solution based on the cost performance method is adopted to help decision makers select the ideal options for Pareto solutions. A case study of a major oil spill accident that occurred in the Bohai Bay is conducted to demonstrate the application of the proposed model and approaches and the real-world implications.
| Item Type: | Article |
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| Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD61 Risk Management H Social Sciences > HE Transportation and Communications T Technology > TA Engineering (General). Civil engineering (General) |
| Divisions: | Engineering |
| Publisher: | Elsevier |
| Date Deposited: | 28 Apr 2021 08:53 |
| Last Modified: | 29 Dec 2022 00:50 |
| DOI or ID number: | 10.1016/j.ejor.2020.12.040 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/14874 |
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