Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems, natural or artificial. SI systems are typically made up of a population of simple agents or boids interacting locally with one another and with their environment. The inspiration often comes from nature, especially biological systems. The agents follow very simple rules, and although there is no centralized control structure dictating how individual agents should behave, local, and to a certain degree random, interactions between such agents lead to the emergence of “intelligent” global behavior, unknown to the individual agents. Natural examples of SI include ant colonies, bird flocking, animal herding, bacterial growth, and fish schooling.

Recently, SI algorithms have attracted close attention of researchers and have also been applied successfully to solve optimization problems in engineering. Nevertheless, for large and complex problems, SI algorithms consume considerable computation time due to stochastic feature of the search approaches. Therefore, there is a potential requirement to develop efficient algorithm to find solutions under the limited resources, time, and money in real-world applications.

The aim of this special issue is to highlight the most significant recent developments on the topics of SI and to apply SI algorithms in real-life scenario. Contributions containing new insights and findings in this field are welcome. Particular attention will be given to the following theme areas; however, it should be stressed that a broad range of submissions are encouraged. We invite authors to contribute with original research articles as well as review articles to this special issue. Potential topics include, but are not limited to:

• Convergence proof for SI algorithms
• Benchmarking and evaluation of new SI algorithms
• Comparative theoretical and empirical studies on SI algorithms (e.g., artificial bee optimization, ant colony optimization, artificial fish algorithm, artificial immune system, bat algorithm, bacterial foraging optimization, cuckoo search, firefly algorithm, intelligent water drops, magnetic optimization algorithm, and particle swarm optimization)
• SI algorithms for real-world applications (e.g., aerospace engineering, bioengineering, chemical engineering, computer engineering, electrical engineering, image processing, industrial engineering and manufacturing systems, mechanical engineering, signal processing, etc.)

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/tswj/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/tswj/computer.science/sia/ according to the following timetable: