Swarm Intelligence and Evolutionary Algorithms for Real World Applications

Dear Colleagues,

Swarm intelligence (SI) and evolutionary computation (EC) techniques have been thriving research topics, especially in areas where 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 natural 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 among the core issues. Ever since the inception of SI and EC techniques, researchers have been attracted to the complex emergent behaviour, robustness, and easy-to-understand architecture of nature-inspired swarm intelligence and evolutionary algorithms. In challenging search environments, these methods have often proved more useful than the conventional approaches.

This Special Issue journal will facilitate the discussion of emerging topics in this context and encourages PhD students, early career researchers, as well as senior academics to engage in a dialogue surrounding the real-world applications of swarm intelligence and evolutionary computation techniques.

Dr. Mohammad Majid al-Rifaie
Guest Editor

Manuscript Submission Information

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