Genetic Algorithm Allocation and Assignment Tool for Missile Defense Battle Management

Award Information
Agency:
Department of Defense
Branch
Missile Defense Agency
Amount:
$100,000.00
Award Year:
2008
Program:
SBIR
Phase:
Phase I
Contract:
HQ0006-08-C-7867
Agency Tracking Number:
B073-045-0578
Solicitation Year:
2007
Solicitation Topic Code:
MDA07-045
Solicitation Number:
2007.3
Small Business Information
SCIENTIFIC SYSTEMS CO., INC.
500 West Cummings Park - Ste 3000, Woburn, MA, 01801
Hubzone Owned:
N
Socially and Economically Disadvantaged:
Y
Woman Owned:
N
Duns:
859244204
Principal Investigator:
Michael Perloff
Principal Investigator
(781) 933-5355
mike@ssci.com
Business Contact:
Jay Miselis
Corporate Controller
(781) 933-5355
jmiselis@ssci.com
Research Institution:
n/a
Abstract
An increasing number of countries are acquiring nuclear, biological, and chemical weapons together with missile systems that enable them to deliver these weapons beyond their borders. Short response times require effective, efficient planning tools for resource and weapons allocation, assignment, and placement so that these tasks can be executed effectively in a highly stressed environment with many potential targets and high uncertainty. Under this effort, we will develop a comprehensive, practical Genetic Algorithm (GA) based solution whose intrinsic representation accounts for attack and tracking uncertainty and weapons capability, supports shoot-look-shoot and contains event-driven alternatives. Scientific Systems (SSCI) has previously developed GA approaches for problems in missile routing, attack planning, search, and medical scheduling. The missile routing product, CMARS (Cruise Missile Autonomous Routing System) has been integrated into the Tomahawk Planning System (TPS) and is undergoing Phase III development. Our project team includes Prof. Dimitri Bertsekas of MIT, and Lockheed Martin Tactical Systems (LMTS). Prof. Bertsekas, a leading expert in optimization techniques, will aid us in formulating, testing and validating our methods, comparing them with other methods, and, if needed, in real-time, parallel, distributed implementation. LMTS will provide expertise in complex multi-target tracking, identification, and discrimination and knowledge of Missile Defense (MD) interceptors and strategies. The team's combined proven experience in advanced Genetic Algorithms, optimization techniques, advanced multi-target tracking techniques, and their knowledge of MD interceptors will ensure a successful demonstration in Phase I of a flexible, and effective Genetic Algorithm tool for Missile Defense (MD) weapons allocations and assignment, followed by development and thorough testing in Phase II, and successful transition to DoD and commercial products in Phase III. Raytheon also supports this effort and is interested in working with us in transitioning to Phase II and III applications.

* information listed above is at the time of submission.

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