The performance of microgrid operation requires hierarchical control and estimation
schemes that coordinate and monitor the system dynamics within the expected manipulated …

The utilization of surrogate models to approximate complex systems has recently gained
increased popularity. Because of their capability to deal with black-box problems and lower …

Complex continuous optimization problems widely exist nowadays due to the fast
development of the economy and society. Moreover, the technologies like Internet of things …

As an advanced artificial intelligence technique for solving learning problems, deep learning
(DL) has achieved great success in many real-world applications and attracted increasing …

Evolutionary algorithms have been shown to be very successful in solving multi-objective
optimization problems (MOPs). However, their performance often deteriorates when solving …

Only a small number of function evaluations can be afforded in many real-world
multiobjective optimization problems (MOPs) where the function evaluations are …

Federated learning is an emerging technique used to prevent the leakage of private
information. Unlike centralized learning that needs to collect data from users and store them …

Convolutional neural networks (CNNs) have shown remarkable performance in various real-
world applications. Unfortunately, the promising performance of CNNs can be achieved only …

Many industrial applications require time-consuming and resource-intensive evaluations of
suitable solutions within very limited time frames. Therefore, many surrogate-assisted …

As the population in cities continues to increase, large-city problems, including traffic
congestion and environmental pollution, have become increasingly serious. The …