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Computer Modeling in Engineering & Sciences
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DOI: 10.32604/cmes.2023.029710

EDITORIAL

Bio-Inspired Optimization in Engineering and Sciences

Yudong Zhang1,* and Huiling Chen2

1School of Computing and Mathematical Sciences, University of Leicester, Leicester, LE1 7RH, UK
2College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, 325035, China
*Corresponding Author: Yudong Zhang. Email: yudongzhang@ieee.org
Received: 04 March 2023; Accepted: 06 March 2023; Published: 31 May 2023

Bio-inspired optimization algorithms [1,2] are a set of optimization algorithms inspired by natural phenomena, such as evolutionary processes, social behaviours, and swarm intelligence [3]. These algorithms attempt to simulate these processes to solve optimization problems [4,5].

Classical bio-inspired algorithms include genetic algorithm, ant colony optimization, artificial bee colony, particle swarm optimization, firefly algorithm, Japanese tree frog algorithm, Harris hawks optimization [6], slime mould algorithm [7], grey wolf optimization, sparrow search algorithm, whale optimization algorithm, etc. Fig. 1 shows the taxonomy of common bio-inspired optimization algorithms. There are some recent newly proposed bio-inspired algorithms, such as Siberian tiger optimization [8], jellyfish search algorithm [9], etc.

Figure 1: Taxonomy of common bio-inspired optimization algorithms

Bio-inspired optimization algorithms can be applied to engineering and sciences in several ways, such as data mining classification [10], biomarker extraction, food processing [11], image segmentation [12], renewable-powered smart grids [13], concurrent software [14], disease classification [15], lesion localization, treatment recommendation, power dispatch [16,17], mammogram diagnosis [18], rectangle layout problem [19], etc.

This special issue, bio-inspired optimization in engineering and sciences, is now calling for papers to the journal ‘Computer Modeling in Engineering & Sciences’. The aim is to report the recent advances in bio-inspired optimization in Engineering and Sciences. The ultimate goal of this special issue is to promote research and development of bio-inspired optimization theories and their applications in engineering and sciences by publishing high-quality research articles and surveys in this rapidly growing interdisciplinary field.

Funding Statement: The authors received no specific funding for this study.

Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present editorial.

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