SBIR/STTR Research Award

Accelerating ATM Optimization Algorithms Using High Performance Computing Hardware

Award identifier 530b111b245208e1b2ba481463ff11c017ea622ea183224d83215eeb11977669Awarding agency National Aeronautics and Space Administration

Award amount

$900,000

Program and phase

SBIR · Phase II

Award year

2012

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Award details

Awarding agency
National Aeronautics and Space Administration
Branch
Not reported
Recipient company
OPTIMAL SYNTHESIS INC.
Proposal award date
2012-04-30
Contract end date
2015-04-28
UEI
REAUM5F2AM94
Solicitation number
Not reported
Topic code
A3.01

Research abstract

NASA is developing algorithms and methodologies for efficient air-traffic management. Several researchers have adopted an optimization framework for solving problems such as flight scheduling, route assignment, flight rerouting, nationwide traffic flow management (TFM) and dynamic airspace configuration. Computational complexity of these problems have led investigators to conclude that in many instances, real time solutions are computationally infeasible, forcing the use of relaxed versions of the problem to manage computational complexity. The primary objective of the proposed research is to accelerate optimization algorithms that play central roles in NASA's ATM research, by parallel implementation on emerging high performance computing (HPC) hardware. The Phase I R&D effort implemented a Simplex-based Dantzig-Wolfe (DW) decomposition solver that exploits both coarse-grain and fine-grain parallelism in the sub-problem and master iterations of the DW decomposition. The implementation also exploits the sparsity in the problems, to manage both memory requirements and run-times for large-scale optimization problems. This parallel implementation was used to solve a Traffic Flow Management (TFM) problem with 17,000 aircraft (linear program with 7 million constraints), in 15 seconds. The implementation is 30¿ faster than the exact same code running on the CPU. It is also 16¿ faster than the NASA's current solution that implements parallel DW decomposition using the GNU Linear Programming Kit (GLPK) on an 8-core computer with hyper-threading. Based on the promising Phase I results, the Phase II R&D effort will explore Mixed Integer Linear Programming (MILP) methods to solve optimization problems arising in the terminal area and on the airport surface, in addition to DW decomposition for the nationwide TFM problem. Phase II work will develop operational prototypes of the algorithm implementations on HPC hardware, and deliver them to NASA for further evaluation.

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

102 SBIR/STTR records share this UEI (1994–2020). Reported award amounts total $28,307,929. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: National Aeronautics and Space Administration, Department of Defense

Agency intelligence

National Aeronautics and Space Administration

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