Emergency fleet scheduling for maritime oil spill accidents considering demand-site dynamic motion under uncertain demand

This paper studies an optimal scheduling method for emergency fleets in maritime oil spill accidents. An oil spill accident has the characteristic of a multipoint distribution of demand sites. Considering the suddenness of the accident and the dynamic motion of oil film at sea, the demand for emergency resources is uncertain and the location of demand sites is time-varying. Through analysis of these characteristics, an emergency fleet scheduling model with multi-centre and multi-demand points was established. The study considered the demand uncertainty of emergency resources and the time-varying location of the demand sites to minimise emergency transportation costs and environmental pollution losses. Accordingly, an improved hybrid metaheuristic algorithm was designed based on a genetic algorithm and a simulated annealing algorithm. Numerical experiments were conducted to verify the effectiveness and practicability of the proposed method. The results can provide decision-making reference for the emergency response to maritime oil spill accidents.

• Record URL:
  • https://doi.org/10.1016/j.oceaneng.2023.115434
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0029801823018188
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00298018
• Supplemental Notes:
  • © 2023 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Zhang, Hao
  • Gan, Li
  • Tao, Ningrong
  • Yang, Nan
  • Zhan, HuiPing
• Publication Date: 2023-10-1

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: 115434
• Serial:
  • Ocean Engineering
  • Volume: 285
  • Issue Number: 0
  • Publisher: Pergamon
  • ISSN: 0029-8018
  • EISSN: 1873-5258
  • Serial URL: http://www.sciencedirect.com/science/journal/00298018

Subject/Index Terms

• TRT Terms: Demand; Emergency management; Fleet management; Genetic algorithms; Marine engineering; Oil spills; Scheduling
• Subject Areas: Environment; Marine Transportation;

Filing Info

• Accession Number: 01890453
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 23 2023 10:14AM