A new ensemble machine learning-based prediction mechanism reinitializes evolutionary algorithm populations after ...
Many real-time systems require the optimization of discrete variables. Black-box optimization (BBO) algorithms and multi-armed bandit (MAB) algorithms perform ...
A newly published study in Discover Artificial Intelligence proposes a machine learning framework designed specifically for ...
Expensive optimization problem (EOP) refers to the problem that requires expensive or even unaffordable costs to evaluate candidate solutions, which widely exist in many significant real-world ...
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