Optimizing Weapons System and Sensor Pairing Through Efficient Binary Polynomial Optimization

Award Information
Agency:
Department of Defense
Branch
Missile Defense Agency
Amount:
$148,809.00
Award Year:
2013
Program:
SBIR
Phase:
Phase I
Contract:
HQ0147-13-C-7318
Award Id:
n/a
Agency Tracking Number:
B122-004-0117
Solicitation Year:
2012
Solicitation Topic Code:
MDA12-004
Solicitation Number:
2012.2
Small Business Information
43 Lantern Rd, Belmont, MA, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
360984814
Principal Investigator:
Adrian Becker
Senior Engineer
(617) 945-7692
abecker@dynamicideasfinancial.com
Business Contact:
Georgia Mourtzinou
Founding Partner
(617) 945-7686
gmourtzinou@dynamicideasfinancial.com
Research Institution:
Stub




Abstract
Exact formulations of weapon-to-threat assignment problems have long been identified as binary polynomial optimization problems which are theoretically difficult (NP-hard), thus previous research for implementation in the area has focused on heuristic solution methods or methods which compromise full formulation with limits on assignment. The introduction of sensor pairing further complicates formulation and solution. However, we explain an approach in this proposal to transform problems of this type into what are known as binary second-order cone problems. While still in the same theoretical computational complexity class, such problems have proven to be practically efficiently solvable by commercial optimization engines such as CPLEX and Gurobi. The algorithm we propose to develop and test in Phase I implements our proposed modeling approach on a detailed formulation of the simultaneous asset pairing and engagement scheduling problem thus fully integrating optimization of the exact problem.

* information listed above is at the time of submission.

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