Applications of Evolutionary and Swarm Systems

Dear Colleagues,

Swarm intelligence (SI) and evolutionary computation (EC) techniques are thriving research topics, especially in areas in which conventional methods fail to deal with the size and nature of the problem space.

The self-organizing nature of swarm intelligence and evolutionary computation in both nature and computational models is key to the attractiveness of such techniques; they not only explain and reflect on the natural-and-social phenomena but also their application to solve complex problems in many disciplines.

Additionally, noisy environments and/or incomplete data are often at the heart of real-world data where search- and optimization-related problems are amongst the core issues. Ever since the inception of SI and EC techniques, researchers have been attracted to the complex emergent behavior, robustness, and easy-to-understand architecture of nature-inspired swarm intelligence algorithms. In challenging search environments, these methods have often proved more useful than the conventional approaches.

The aim of this Special Issue is to facilitate the discussion of emerging topics in this context; PhD students, early-career researchers, and senior academics are encouraged to engage in a dialogue surrounding the applications and theories based on swarm intelligence and evolutionary computation techniques.

Topics of interest for this symposium include but are not limited to:

• applied and theoretical research in swarm intelligence and evolutionary computation;
• applications of swarm intelligence and evolutionary computation techniques for real-world problems;
• studies on the behavior of social insects, social animals, and natural phenomena in the context of swarm intelligence and evolutionary computation techniques.

Dr. Mohammad Majid al-Rifaie
Guest Editor

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