Investigators from University of Minnesota Zero in on Machine Learning (Computat ionally Efficient Solution of Mixed Integer Model Predictive Control Problems Vi a Machine Learning Aided Benders Decomposition)
Investigators from University of Minnesota Zero in on Machine Learning (Computat ionally Efficient Solution of Mixed Integer Model Predictive Control Problems Vi a Machine Learning Aided Benders Decomposition)
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news originating from Minneapolis, Minnesota, by Ne wsRx correspondents, research stated, “Mixed integer Model Predictive Control (M PC) problems arise in the operation of systems where discrete and continuous dec isions must be taken simultaneously to compensate for disturbances. The efficien t solution of mixed integer MPC problems requires the computationally efficient online solution of mixed integer optimization problems, which are generally diff icult to solve.” Financial support for this research came from National Science Foundation (NSF).
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Minneapolis/Minnesota/United States/N orth and Central America/Cyborgs/Emerging Technologies/Machine Learning/Univ ersity of Minnesota
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