Applications of nature-inspired meta-heuristic algorithms: a survey Online publication date: Thu, 18-Nov-2021
by Avjeet Singh; Anoj Kumar
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 20, No. 3/4, 2021
Abstract: Nature-inspired meta-heuristic algorithms (NIMAs) combine the properties of nature-inspired and mete-heuristic algorithms. Evolutionary inspired and swarm-inspired algorithms are the most researched techniques for the developments of new nature-inspired algorithms. NIMAs are based on swarm intelligence, biological systems, and chemical systems. These algorithms thoroughly explore the solution space to get a better optimal solution. Although not all NIMAs are efficient, yet a few algorithms have proved to be very effective and are popularly used as tools for solving real-world problems. NIMAs can be categorised into evolutionary-based, swarm-intelligence-based, physics-based, and human-based algorithms, depending on the sources of inspiration. This paper surveys evolutionary inspired algorithms and swarm inspired algorithms. The paper commences with a summary of NIMAs, followed by the literature survey of some popular evolutionary inspired and swarm inspired meta-heuristic algorithms. This paper also specifies the domain and application areas of all the NIMAs.
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