ASSET PRE-POSITIONING AND POST-ATTACK SEQUENTIAL NETWORK RECONSTITUTION IN A CONTESTED ROAD NETWORK
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Authors
Chang, Hong Yu
Subjects
mixed-integer linear programming
MILP
Benders decomposition
optimization
military
pre-positioning
asset allocation
combat engineers
MILP
Benders decomposition
optimization
military
pre-positioning
asset allocation
combat engineers
Advisors
Craparo, Emily M.
Date of Issue
2024-09
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
Combat engineer operations planning is often tedious and reliant on intelligence reports, which can quickly become outdated due to the dynamic nature of enemy tactics. Traditional planning methods are reactive, focusing on overcoming known obstacles, which limits the flexibility and effectiveness of the planning process. This research proposes the use of optimization tools to enhance combat engineer planning. We develop a sequential network reconstitution model to optimize engineering asset employment, and we use it as a sub-problem in an algorithm to optimize pre-positioning of engineering assets. By employing mixed-integer linear programming (MILP) and Benders decomposition, our model generates optimal plans considering possible enemy actions. Our model effectively solves small-scale scenarios providing insights into pre-positioning for sequential network reconstitution.
Type
Thesis
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Distribution Statement
Distribution Statement A. Approved for public release: Distribution is unlimited.
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