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Optimizing Weapons System and Sensor Pairing Through Efficient Binary…

Award Information

Department of Defense
Award ID:
Program Year/Program:
2013 / SBIR
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
43 Lantern Rd. Belmont, MA 02478-1706
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Phase 1
Fiscal Year: 2013
Title: Optimizing Weapons System and Sensor Pairing Through Efficient Binary Polynomial Optimization
Agency: DOD
Contract: HQ0147-13-C-7318
Award Amount: $148,809.00


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.

Principal Investigator:

Adrian Becker
Senior Engineer
(617) 945-7692

Business Contact:

Georgia Mourtzinou
Founding Partner
(617) 945-7686
Small Business Information at Submission:

Dynamic Ideas
43 Lantern Rd Belmont, MA -

EIN/Tax ID: 043446823
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No