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 simulation study in Cluster Computing reports that a hybrid chaotic fire hawk and pufferfish optimization algorithm lowered ...

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 ...

What you will gain from this article・ Understanding of a new evolutionary framework that separates the design and evaluation ...