Methods and systems for intelligent evolutionary optimization of workflows using big data infrastructure

Methods and systems for optimizing the configuration and parameters of a workflow using an evolutionary approach augmented with intelligent learning capabilities using a Big Data infrastructure. In an embodiment, a Big Data infrastructure receives workflow input parameters, an objective function, a...

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Bibliographic Details
Main Authors Williams Jenny Marie Weisenberg, Aggour Kareem Sherif
Format Patent
LanguageEnglish
Published 26.12.2017
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Summary:Methods and systems for optimizing the configuration and parameters of a workflow using an evolutionary approach augmented with intelligent learning capabilities using a Big Data infrastructure. In an embodiment, a Big Data infrastructure receives workflow input parameters, an objective function, a pool of initial configuration parameters, and completion criteria from a client computer, and then runs multiple instances of a workflow based on the pool of initial configuration parameters resulting in corresponding output results. The process includes storing the workflow input parameters and the corresponding output results, modeling the relationship between changes in the workflow input parameters and the corresponding output results, determining that optimal output results have been achieved, and then transmitting the optimal output and the input-output variable relationships results to the client computer.
Bibliography:Application Number: US201414297351