4.7 Article

Dynamic resource allocation to support oil spill response planning for energy exploration in the Arctic

期刊

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
卷 257, 期 1, 页码 272-286

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.ejor.2016.07.023

关键词

OR in disaster relief; Decision analysis; Scheduling; OR in government

资金

  1. U.S. Department of Homeland Security, Command, Control and Interoperability Center for Advanced Data Analysis (CCICADA)
  2. McDevitt Foundation
  3. U.S. National Science Foundation [CMMI-1254258]
  4. Directorate For Engineering
  5. Div Of Civil, Mechanical, & Manufact Inn [1254258] Funding Source: National Science Foundation

向作者/读者索取更多资源

A mixed-integer linear program is proposed to model the dynamic network expansion problem of improving oil spill response capabilities to support energy exploration in the Arctic. Oil spill response operations in this region can be hampered by a lack of existing infrastructure, limited pre-positioned response equipment, and the possibility that response equipment might not arrive in time to mitigate the impact of a spill because of distance and infrastructure limitations. These considerations are modeled by two inter-related constraint sets with the objective of minimized total weighted response time for a set of potential oil spill incidents. One constraint set determines how to dynamically allocate response equipment and improve the infrastructures necessary to stockpile them within a network of response sites. The other set determines how to utilize this stockpile to respond to each task necessary for an incident by scheduling the equipment to complete tasks. These task completion times are subject to deadlines which, if not met, can, instead, require costlier follow-on tasks to be scheduled. The model, its assumptions, and data requirements were assessed by subject matter experts in the United States (U.S.) Coast Guard and a major Oil Spill Response Organization in the context of oil spill response logistics to support energy exploration initiatives in the U.S. Arctic. (C) 2016 Elsevier B.V. All rights reserved.

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