Dissertation/Thesis Abstract

Dynamic modeling of arctic resource allocation for oil spill response
by Garrett, Richard A., M.Eng., Rensselaer Polytechnic Institute, 2016, 67; 10159829
Abstract (Summary)

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.

Indexing (document details)
Advisor: Sharkey, Thomas
Commitee: Grabowski, Martha, Wallace, William A.
School: Rensselaer Polytechnic Institute
Department: Industrial and Management Engineering
School Location: United States -- New York
Source: MAI 55/06M(E), Masters Abstracts International
Subjects: Industrial engineering, Operations research
Keywords: Decision analysis, Or in disaster relief, Or in government, Scheduling
Publication Number: 10159829
ISBN: 978-1-369-14757-5
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