Optimization-based allocation of force protection resources in an asymmetric environment

More than four years after the end of major combat operations in the 2003 Iraq War, the United States military continues to sustain casualties at rates higher than those during the ground campaign. Combat service support soldiers conducting daily convoy operations on the Iraqi road network account for a large number of these casualties. One reason for this is the threat's affinity to targeting soft, vulnerable, high-payoff targets through the use of roadside bombs, otherwise known as improvised explosive devices. This enemy tactic is characteristic of asymmetric warfare, in which a lesser opponent opposes a force far superior in numbers, equipment, and technology. In an asymmetric operating environment, threats blend in with the local populace making them hard to detect and are easily capable of multi-directional attacks; absent are the linear battlefields of past wars where logistical soldiers operated in the relative safety of the rear battlefield. This thesis explores a mathematical approach to decide how to use available resources to best protect logistical convoys. To achieve this we first model the threat using probabilistic models and identify input data requirements associated with the operating environment and other relevant factors.

Department dc:contributor.department

Massachusetts Institute of Technology. Operations Research Center.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2007

Author dc:creator

• DeGregory, Keith W. (Keith William)

Advisor dc:contributor.advisor

• Cynthia Barnhart.

• Operations Research Center.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/40878

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/40878