SBIR/STTR Research Award

Generating Optimized RSP Loading Plans using modern AI-based Constraint Solvers

Award identifier 1a15c3d67470026e7e25ee926e633ec9bf71929fdd4b6bc9a0c82f6c724726c2Awarding agency Department of Defense · Air Force

Award amount

$180,000

Program and phase

SBIR · Phase I

Award year

2024

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
VIRTUALITICS INC
Proposal award date
2024-03-08
Contract end date
2024-09-12
UEI
YRMLQVHSYKY8
Solicitation number
23.3
Topic code
AF233-0035

Research abstract

Virtualitics proposes a Phase I effort to explore the potential of modern AI-based constraint solving methods, specifically Satisfiability Modulo Theories (SMT), in automating and optimizing the Readiness Spares Packages (RSP) load planning process for the U.S. Air Force. The current manual process, which involves arranging spare parts into containers like the ISU-90 and 463L pallets, is time-consuming and prone to errors. By leveraging the high-performance SMT-solver, Z3, and incorporating heuristic and approximation methods, the aim is to reduce packing time and increase efficiency in the utilization of containers. The initiative draws upon Virtualitics' prior experience with Air Force Global Strike Command, aiming to produce a software solution that can drastically improve RSP assembly and deployment readiness.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

20 SBIR/STTR records share this UEI (2019–2025). Reported award amounts total $11,000,467. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

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