Survey on nature inspired algorithm for smart city applications

Nature Inspired Computing (NIC) paradigms, namely, swarm intelligence, evolutionary computation and computational intelligence techniques are widely applied to develop versatile and adaptable systems and create computational methods that can assist human to resolve real world complex problems. It can be achieved by transferring knowledge from natural systems to engineering systems. The objective of this paper is to analyze the recent trends and advancement in the application of metaheuristic algorithms to solve various domains, especially, denoising, edge detection and classification problem. This paper provides a comprehensive list of global optimization algorithms that can be applied to develop innovative system and soft computing applications integrates with computational intelligence techniques. Several fitness functions and parameters implemented in the evaluation of global optimization algorithm to find global optimum for solving diverse applications are thoroughly investigated. The implications for the selection of fitness function to solve specific optimization problems and applications are also discussed.

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