Swarm Intelligence Algorithms and Applications to Real-world Optimization Problems: A Survey.

Exact approaches have been inadequate to provide optimal results to complex optimization problems in acceptable time, and it is a common belief that nature produces an intrinsic result to complicated problems. Nature's concepts and ideas were investigated by researchers to develop heuristic approaches that offer solutions to difficult problems. The technology of swarm intelligence (SI) that is motivated by the social habit of animals has been found effective to handle complex problems. There are different types of SI methods and their variants in the literature include cockroach swarm optimization, bees colony optimization, particle swarm optimization, and ant colony optimization. The focus of this paper is on SI techniques, and its application to some of the real world optimization problems such as timetabling, scheduling, transportation, and logistics problems. SI methods research trends and applications are highlighted. [ABSTRACT FROM AUTHOR]

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