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 Multi-Sensor Fusion, Exploitation & Resource Allocation | Genetic Scheduling Algorithm |
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| Genetic Scheduling Algorithm |
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The Genetic Scheduling Algorithm is a result of work performed through SBIR Phase I & II contracts.
The objective of this research was to develop a guided random search algorithm, based on a biological
process of evolution, to control adaptive sensor resource management. A fitness function is used to determine the
viability of each task. Subsequent tasks are weighted using methods of tournament selection (i.e. survival of the
fittest), crossover (reproduction between parent nodes) and mutation (random modifications to newly created solutions).
Algorithm verification was performed using MatLab code and analysis. A standard C library has been implemented within
the Black River Systems Sensor Resource Manager suite.
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Specifications
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- Algorithm Implementations: MatLab, standard C
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Related Technologies
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Sensor Resource Manager
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| Release Information & Requests |
Contact Black River Systems for acquisition questions regarding this technology. |
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Sample results plot of allocated tasks
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Fitness function score per generation
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Last modified: April 2006
