Resource Allocation using Market-Based Optimization (RAMBO)

Award Information
Agency:
Department of Defense
Amount:
$999,966.00
Program:
SBIR
Contract:
HQ0147-13-C-7110
Solitcitation Year:
2010
Solicitation Number:
2010.3
Branch:
Missile Defense Agency
Award Year:
2013
Phase:
Phase II
Agency Tracking Number:
B2-1837
Solicitation Topic Code:
MDA10-002
Small Business Information
Charles River Analytics Inc.
MA, Cambridge, MA, 02138-4555
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
115243701
Principal Investigator
 Sctott Reilly
 Principal Scientist
 (617) 491-3474
 snealreilly@cra.com
Business Contact
 Mark Felix
Title: Contracts Manager
Phone: (617) 491-3474
Email: mfelix@cra.com
Research Institution
 Stub
Abstract
Missile defense takes place in a dynamic, uncertain environment. Multi-raid attacks threaten to overload sensor capabilities, leaving fewer sensor resources free to observe each target. Moreover, the shift in emphasis toward early intercept, coupled with the growing importance of short- and medium-range threats, reduces the time available for detection, tracking, and discrimination, because engagement decisions must be made more quickly. These factors increase the need for effective sensor resource management to squeeze the maximum amount of useful information out of an overloaded sensor network. What is needed is a solution that can optimally assign a large number of heterogeneous sensors to a large number of incoming threats fast enough for early intercept, while meeting dynamic constraints on sensor availability and physical constraints. Here, we propose Resource Allocation using Market-Based Optimization (RAMBO), to provide dynamic planning and scheduling of sensors to maximize sensor quality of service while minimizing sensor uncertainty. This approach applies market-based optimization, using solutions from economic theory and game theory, to sensor resource management by creating an artificial market for sensor capabilities and information. With a properly designed market, we can engineer a system that ensures an optimal allocation of sensors and resources.

* information listed above is at the time of submission.

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