Large language models (LLMs) have not only revolutionized natural language processing
but also extended their prowess to various domains, marking a significant stride towards …

Vehicles around the world are being converted to electric power in order to combat climate
change and lower pollution levels. Sustaining this process calls for more electric vehicle …

This study proposes a novel artificial protozoa optimizer (APO) that is inspired by protozoa in
nature. The APO mimics the survival mechanisms of protozoa by simulating their foraging …

Learning and optimization are the two essential abilities of human beings for problem
solving. Similarly, computer scientists have made great efforts to design artificial neural …

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 …

In recent years, the optimization community has witnessed a surge in the popularity of
population-based optimization methods. However, many of these methods suffer from …

With the enormous increase in energy usage by cloud data centers for handling various
workflow applications, the energy-aware cloud workflow scheduling has become a hot …

Knowledge transfer plays a vastly important role in solving multitask optimization problems
(MTOPs). Many existing methods transfer task-specific knowledge, such as the high-quality …

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

Distributed differential evolution (DDE) is an efficient paradigm that adopts multiple
populations for cooperatively solving complex optimization problems. However, how to …