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Simulation Optimization Engine (SIMON) for Missile Defense

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0006-09-C-7152
Agency Tracking Number: B083-036-0061
Amount: $99,953.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: MDA08-036
Solicitation Number: 2008.3
Timeline
Solicitation Year: 2008
Award Year: 2009
Award Start Date (Proposal Award Date): 2009-03-27
Award End Date (Contract End Date): 2009-09-27
Small Business Information
625 Mount Auburn Street
Cambridge, MA 02138
United States
DUNS: 115243701
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Brad Rosenberg
 Senior Scientist
 (617) 491-3474
 brosenberg@cra.com
Business Contact
 Ninos Hanna
Title: Contract Specialist
Phone: (617) 491-3474
Email: nhanna@cra.com
Research Institution
N/A
Abstract

As evidenced by recent events, missile defense remains a crucial component for protecting the United States and her allies from potential long range threats. Modeling and simulation (M&S) is recognized by the Missile Defense Agency as a key enabling technology supporting Warfighters and analysts alike in Ballistic Missile Defense System (BMDS) design, testing, performance assessment, training, wargaming, and system acquisition. The use of M&S becomes even more essential as the numbers, capabilities, complex behaviors, and interactions between evolving BMDS elements, configurations and threats dramatically increase. Currently, however, exploration of decision variables within a BMDS-level simulation is a manual process lacking an automated method to determine the optimal parameters for offensive scenario designs or BMDS configurations. To satisfy these needs, we propose to design and demonstrate the feasibility of a Simulation Optimization Engine (SIMON) for missile defense. SIMON features the use of evolutionary algorithms to discover optimal parameters for BMDS-level simulations. This is complemented by a suite of graphical configuration, analysis, and visualization tools to support the M&S analyst in exploring and understanding the design optimization space. This capability will be integrated with modern BMDS simulations to support automated exploration of offensive scenario designs, BMDS architectures, and operational decision-making strategies.

* Information listed above is at the time of submission. *

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