Review on Nature-Inspired Algorithms

Wael Korani () and Malek Mouhoub ()
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Wael Korani: University of Regina
Malek Mouhoub: University of Regina

SN Operations Research Forum, 2021, vol. 2, issue 3, 1-26

Abstract: Abstract Optimization and its related solving methods are becoming increasingly important in most academic and industrial fields. The goal of the optimization process is to make a system or a design as effective and functional as possible. This is achieved by optimizing a set of objectives while meeting the system requirements. Optimization techniques are classified into exact and approximate algorithms. Nature-inspired (NI) methods, a sub-class of approximate techniques, are widely recognized for providing efficient approaches for solving a wide variety of real-world optimization problems. In this paper, we discuss many scenarios where we can or cannot use different NI methods in tackling real-world optimization problems. We also enrich our survey with many studies for the reader to prove the efficiency and efficacy of using NI methods to tackle many real-world applications. Therefore, NI methods should be considered as alternative reliable approaches in the absence of exact methods to provide satisfactory solutions.

Keywords: Optimization; Nature-inspired algorithms; Swarm Intelligence; Evolutionary Computation; Genetic Algorithms (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s43069-021-00068-x

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