OptForceT: New Human Resource Optimization Methods

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-05-C-0017
Agency Tracking Number: N033-0022
Amount: $750,000.00
Phase: Phase II
Program: STTR
Awards Year: 2005
Solicitation Year: 2003
Solicitation Topic Code: N03-T004
Solicitation Number: N/A
Small Business Information
OPTTEK SYSTEMS, INC.
1919 Seventh Street, Boulder, CO, 80302
DUNS: 135556848
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Dr. Keith Womer
 Director
 (662) 915-5497
 kwomer@bus.olemiss.edu
Business Contact
 Jay April
Title: Chief Development Officer
Phone: (303) 447-3255
Email: april@opttek.com
Research Institution
 UNIV. OF MISSISSIPPI
 Keith Womer
 Hearin Center
University, MS, 38677
 (662) 915-5497
 Nonprofit college or university
Abstract
OptTek Systems, Inc. is developing new software to significantly enhance optimization applications. The software, called OptForce, incorporates a sophisticated Meta-Structured Optimization (MSO) approach directly into the representation of the decision-making process. It has been demonstrated to be more effective than traditional mixed integer programming and heuristic solvers. Coupled with simulation, it enables a virtually unlimited number of what-if questions to be asked and their answers to be sorted and prioritized efficiently and accurately. MSO is based on a unique algorithm that integrates the two extreme ends of the optimization spectrum, involving the very general and the highly special. The procedure is designed to carry out a special "non-monotonic search," where the successively generated inputs produce varying evaluations, which over time provide a highly efficient trajectory to the best solutions. MSO represents a departure that does not depend on classical rules for generating a mixed zero-one formulation. Its use of layered envelopes (LEVER) is better suited to handling real world complexity. By avoiding identifying in advance the domains of the variables over which the approximation operates -- and more specifically, avoiding identifying the subdomains that characterize regions where the function takes different forms, MSO gives rise to a previously unequalled optimization capability.

* information listed above is at the time of submission.

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