Recent Advances in Swarm Intelligence Algorithms and Their Applications

Dear Colleagues, 

As a branch of artificial intelligence, swarm intelligence refers to the collective behavior of decentralized, self-organized systems. Swarm intelligence is mainly to attract, gather, and manage large-scale participants interacting locally with one another and with their environment. It aims to jointly cope with challenging tasks by means of competition, cooperation, and other independent or collaborative ways, especially the complex system decision-making tasks in the open environment, which leads to the emergence of intelligent global behavior, unknown to individuals.

In recent years, the research community has witnessed an explosion of swarm intelligence algorithms efficiently solving complex computation tasks. This trend has been especially dramatic in what relates to optimization problems, mainly due to the unprecedented complexity of problem instances, arising from a diverse spectrum of domains, such as transportation, logistics, energy, climate, social networks, health and industry 4.0, among many others.

This Special Issue provides a platform for researchers from academia and industry to present their new and unpublished work and to promote future studies in swarm intelligence and its combination with real-world problems and other fields, including but not limited to antenna design, vehicle scheduling, drug design and discovery, image segmentation, feature selection, data clustering, traveling salesman problems, etc.

The second Special Issue volume on this topic has been successfully organized, and the subsequent research can be found at the following link: https://www.mdpi.com/journal/mathematics/special_issues/Y758SX8ZQC.

Prof. Dr. Jian Dong
Guest Editor

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