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    Genetic Optimization for Engine Combustion System Calibration: A Case Study of Optimization Performance Sensitivity to Algorithm Search Parameters 

    Source: Journal of Energy Resources Technology:;2022:;volume( 144 ):;issue: 008:;page 82308-1
    Author(s): Mansfield, Andrew B.; Chakrapani, Varun; Li, Qingyu; Wooldridge, Margaret S.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The use of genetic optimization algorithms (GOA) has been shown to significantly reduce the resource intensity of engine calibration, motivating investigation into the development of these methods. The objective of this ...
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