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Distributed real-time dynamic cooperative optimization with unknown performance function form under resources constraints
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DOI：10.1016/j.isatra.2025.07.045.png)
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Abstract
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• This paper studies the optimization when the global performance function is unknown. Compared with the traditional distributed optimization with known performance function, the research difficulty is greatly increased. • In terms of real-time performance of the algorithm. The algorithm has dynamic self-adaptability, which can optimize the system in real time according to the environment and generate the current optimal solution online. • This research is extended from the consistency optimization to the optimization problem under certain summation constraints of resources, which is especially applicable to the optimal resource scheduling scenarios, such as power grid scheduling and cargo dispatching scenarios.
Keywords:
distributed optimization
unknown performance function
real-time adaptation
resource scheduling
summation constraints
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