Scalability of optimization algorithms is a major challenge in coping with the ever-growing
size of optimization problems in a wide range of application areas from high-dimensional …

Large-scale global optimization (LSGO) problems have widely appeared in various real-
world applications. However, their inherent complexity, coupled with the curse of …

The increasing complexity of Multi-Agent Systems (MASs), coupled with the emergence of
Artificial Intelligence (AI) and Large Language Models (LLMs), have highlighted significant …

Modern computational mathematics and informatics for Digital Environments deal with the
high dimensionality when designing and optimizing models for various real-world …

To resolve the issue of the curse of dimensionality in continuous large-scale optimization
problems, the cooperative coevolution divide-and-conquer framework was proposed by …

Cooperative co-evolution (CC) is an evolutionary framework for dealing with large-scale
optimization problems. The divide-and-conquer strategy is widely used in CC. The large …

Unconstrained continuous large-scale global optimization (LSGO) is still a challenging task
for a wide range of modern metaheuristic approaches. A cooperative coevolution approach …

Non-contact three-phase instantaneous voltage measurement is an emerging and
challenging topic in modern smart grids. Existing measurement methods can hardly obtain …

Cooperative coevolution (CC) is an effective framework for solving large‐scale global
optimization (LSGO) problems. However, CC with static decomposition method is ineffective …

При решении прикладных задач различных сфер человеческой деятельности
возникает необходимость в поиске наилучшего набора параметров по заданному …