Decision Sciences Journal
Volume 27, Number 4
Fall 1996
A Strategic, Area-wide Contingency Planning Model for Oil Spill
Cleanup Operations with Application Demonstrated to the Galveston
Bay Area
W. E. Wilhelm
Department of Industrial Engineering, Texas A&M University, College
Station, TX 77843-3131
Anand V. Srinivasa
Management Science Division, Bonner and Moore Associates, 2727
Allen Parkway, Houston, TX 77019
ABSTRACT
This paper develops a general integer programming model for
strategic, area-wide contingency planning of oil spill cleanup
operations. Model inputs include the set of risk points and the
likely spill scenarios and response requirements for each, the
sites of existing storage locations and the inventory of components
at each, and potential sites for new storage locations. The model
prescribes a minimum total cost plan to either build new storage
locations, expand existing ones, or both, to purchase new
components and pre-position them, and a contingency plan that
determines which response systems should be composed to enable an
effective time-phased response for each likely spill scenario. A
family of heuristics based on linear programming (LP) is devised to
resolve this strategic problem, providing an area-wide contingency
plan. The heuristics are evaluated on a set of 10 test problems
that involve 1869 general integer variables and 3264 constraints.
Computational tests indicate that four heuristics are quite
effective, prescribing solutions for each of 10 test cases within
1.41% of optimum and within a few minutes runtime. This study
focused on modeling the Galveston Bay Area, and the test problems
represent application in that area. A sensitivity analysis is
demonstrated by assessing the impacts of component availability and
the degradation of cleanup capability over time. Use of the model
as a decision support aid by responsible parties, contractors,
governmental organizations and others is described.
Subject Areas: Contingency Planning, Decision Support,
Heuristics, Oil Spill Cleanup, Policy Determination, and Strategic
Planning.
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