The increasing complexity of real-world problems raises new challenges to evolutionary
computation. Distributed models have been successfully employed by many evolutionary …

Island Model (IM) is an alternative often used to parallel Evolutionary Algorithms (EA). In IM,
the population is distributed between islands that evolve their solutions in parallel …

In smart factories, integrated optimisation of manufacturing process planning and scheduling
leads to better results than a traditional sequential approach but is computationally more …

This study introduces a novel Parallel Hybrid Island architecture which shows a parallel way
to combine different meta-heuristic algorithms by using the island model as the base. The …

In recent years, as networks have become increasingly complex and expansive, network
navigation faces new challenges in routing and resource utilization, particularly in the case …

This work introduces a new Parallel Island Model (PIM) that encompasses the benefits of
heterogeneity and algorithmic reconfigurability. The former feature, heterogeneity, means …

The island model allows genetic algorithms to effectively maintain diversity through
migration between multiple independent populations. Due to its flexibility and modularity, it …

Practitioners frequently encounter the challenge of selecting the best optimization algorithm
from a pool of options. However, why not, rather than selecting a single algorithm, let …

In this paper, the possibilities of improving the performance of multi-population-based
algorithms were tested. In the proposed approach, it was decided to test various methods …

Federated learning, as a distributed training framework of machine learning compared to the
traditional training on a single, centralized dataset has been increasingly popular with …