Author : Shiv Kumar Agarwal 1
Date of Publication :30th November 2017
Abstract: Human beings are deeply inspired by nature. Nature has the capability to solve very large complex problems in its own classical way. Nature gives some of the logical and effective ways to find solution to these problems. Nature acts as self optimizer for solving the complex problems. These nature-inspired metaheuristic algorithms can be based on swarm-intelligence-based, bioinspired, physics-based and chemistry-based, depending on the sources of inspiration. Swarm intelligence and bio-inspired algorithms form a hot topic in the developments of novel algorithms inspired by nature. In current decades, meta-heuristic algorithms have been developed to overcome the problem that most of them are inspired from nature. For the past decades, various research efforts have been determined in this particular area. In this paper, the algorithms which are discussed imitate the processes running in nature. Though not all of them are efficient, a few algorithms have proved to be very efficient and thus have become trendy tools for solving real-world problems. In this paper we depict the various Swarm Intelligence Optimization techniques and analysis of these techniques, on the basis of analysis some research issues are given in this paper. This paper also provides the comparison of these techniques and conclusion of the overall paper. This paper proposes the high extent for the development of latest, better and efficient techniques and application in this area. This paper highlights the comparative analysis of nature inspired swarm intelligence based optimization techniques based on literature analysis and the areas where these algorithms have been most successfully applied.
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