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- W4310711292 endingPage "101826" @default.
- W4310711292 startingPage "101826" @default.
- W4310711292 abstract "The design of complex systems has been the forte of and therefore limited to engineers while algorithms have only aided in the representation and optimization of the design options. This human-centric approach has several limitations that leads to sub-optimal design results. In this work, a novel algorithmic design framework ALGINEER is proposed with a concept-proof implementation that overcomes the limitations. ALGINEER formalizes the design processes to isolate the design process from the design problem. It implements genetic algorithms and machine learning to explore the complete solution space, achieve trade-off among many design objectives, and demonstrate design behavior and learning akin to engineers. It is modular, scalable and empowers engineers to concentrate more on problem formulation. The work also suggests future research possibilities towards extending ALGINEER’s abilities." @default.
- W4310711292 created "2022-12-16" @default.
- W4310711292 creator A5069031739 @default.
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- W4310711292 date "2023-01-01" @default.
- W4310711292 modified "2023-10-13" @default.
- W4310711292 title "ALGINEER: Algorithmic design of complex systems" @default.
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- W4310711292 doi "https://doi.org/10.1016/j.aei.2022.101826" @default.
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