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The application of nature-inspired optimization algorithms on the modern management: A systematic literature review and bibliometric analysis

Published online by Cambridge University Press:  21 October 2022

Yi Zhou ,
Weili Xia  and
Jiapeng Dai Open the ORCID record for Jiapeng Dai [Opens in a new window]
Yi Zhou
Affiliation:
School of Management, Northwestern Polytechnical University, Xi'an 710072, China
Weili Xia
Affiliation:
School of Management, Northwestern Polytechnical University, Xi'an 710072, China
Jiapeng Dai*
Affiliation:
School of Government, Nanjing University, Nanjing, 210023, China
*
Author for correspondence: Jiapeng Dai, E-mail: dai2015@snnu.edu.cn
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Abstract

With the expanding adoption of technology and intelligent applications in every aspect of our life, energy, resource, data, and product management are all improving. So, modern management has recently surged to cope with modern societies. Numerous optimization approaches and algorithms are used to effectively optimize the literature while taking into account its many restrictions. With their dependability and superior solution quality for overcoming the numerous barriers to generation, distribution, integration, and management, nature-inspired meta-heuristic optimization algorithms have stood out among these methods. Hence, this article aims to review the application of nature-inspired optimization algorithms to modern management. Besides, the created clusters introduce the top authors in this field. The results showed that nature-inspired optimization algorithms contribute significantly to cost, resource, and energy efficiency. The genetic algorithm is also the most important and widely used method in the previous literature.

Keywords

Data managementenergy managementmodern managementnature-inspired optimization algorithmsorganization managementproduct managementresource management
Type
Research Article
Information
Journal of Management & Organization , Volume 29 , Issue 4: The Role of New ICT-based Systems in Modern Management , July 2023 , pp. 655 - 678
Copyright
© The Author(s), 2022. Published by Cambridge University Press in association with the Australian and New Zealand Academy of Management

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