Review and Classification of Bio-inspired Algorithms and Their Applications

Scientists have long looked to nature and biology in order to understand and model solutions for complex real-world problems. The study of bionics bridges the functions, biological structures and functions and organizational principles found in nature with our modern technologies, numerous mathemati...

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Published inJournal of bionics engineering Vol. 17; no. 3; pp. 611 - 631
Main Authors Fan, Xumei, Sayers, William, Zhang, Shujun, Han, Zhiwu, Ren, Luquan, Chizari, Hassan
Format Journal Article
LanguageEnglish
Published Singapore Springer Singapore 01.05.2020
Subjects
Artificial Intelligence
Biochemical Engineering
Bioinformatics
Biomaterials
Biomedical Engineering and Bioengineering
Biomedical Engineering/Biotechnology
Engineering
multi-objective optimization
evolutionary based algorithms
optimization
swarm intelligence based algorithms
ecology based bio-inspired agorithms
bio-inspired
Online AccessGet full text
ISSN1672-6529
2543-2141
2543-2141
DOI10.1007/s42235-020-0049-9

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Abstract Scientists have long looked to nature and biology in order to understand and model solutions for complex real-world problems. The study of bionics bridges the functions, biological structures and functions and organizational principles found in nature with our modern technologies, numerous mathematical and metaheuristic algorithms have been developed along with the knowledge transferring process from the lifeforms to the human technologies. Output of bionics study includes not only physical products, but also various optimization computation methods that can be applied in different areas. Related algorithms can broadly be divided into four groups: evolutionary based bio-inspired algorithms, swarm intelligence-based bio-inspired algorithms, ecology-based bio-inspired algorithms and multi-objective bio-inspired algorithms. Bio-inspired algorithms such as neural network, ant colony algorithms, particle swarm optimization and others have been applied in almost every area of science, engineering and business management with a dramatic increase of number of relevant publications. This paper provides a systematic, pragmatic and comprehensive review of the latest developments in evolutionary based bio-inspired algorithms, swarm intelligence based bio-inspired algorithms, ecology based bio-inspired algorithms and multi-objective bio-inspired algorithms.
AbstractList Scientists have long looked to nature and biology in order to understand and model solutions for complex real-world problems. The study of bionics bridges the functions, biological structures and functions and organizational principles found in nature with our modern technologies, numerous mathematical and metaheuristic algorithms have been developed along with the knowledge transferring process from the lifeforms to the human technologies. Output of bionics study includes not only physical products, but also various optimization computation methods that can be applied in different areas. Related algorithms can broadly be divided into four groups: evolutionary based bio-inspired algorithms, swarm intelligence-based bio-inspired algorithms, ecology-based bio-inspired algorithms and multi-objective bio-inspired algorithms. Bio-inspired algorithms such as neural network, ant colony algorithms, particle swarm optimization and others have been applied in almost every area of science, engineering and business management with a dramatic increase of number of relevant publications. This paper provides a systematic, pragmatic and comprehensive review of the latest developments in evolutionary based bio-inspired algorithms, swarm intelligence based bio-inspired algorithms, ecology based bio-inspired algorithms and multi-objective bio-inspired algorithms.
Author Han, Zhiwu
Sayers, William
Ren, Luquan
Chizari, Hassan
Zhang, Shujun
Fan, Xumei
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  surname: Fan
  fullname: Fan, Xumei
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  organization: School of Management, Jilin University
– sequence: 2
  givenname: William
  surname: Sayers
  fullname: Sayers, William
  organization: School of Computing and Technology, The University of Gloucestershire
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  givenname: Shujun
  surname: Zhang
  fullname: Zhang, Shujun
  email: szhang@glos.ac.uk
  organization: School of Computing and Technology, The University of Gloucestershire
– sequence: 4
  givenname: Zhiwu
  surname: Han
  fullname: Han, Zhiwu
  organization: Key Laboratory of Bionics Engineering of Ministry of Education, Jilin University
– sequence: 5
  givenname: Luquan
  surname: Ren
  fullname: Ren, Luquan
  organization: Key Laboratory of Bionics Engineering of Ministry of Education, Jilin University
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  givenname: Hassan
  surname: Chizari
  fullname: Chizari, Hassan
  organization: School of Computing and Technology, The University of Gloucestershire
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Issue 3
Keywords multi-objective optimization
evolutionary based algorithms
optimization
swarm intelligence based algorithms
ecology based bio-inspired agorithms
bio-inspired
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Snippet Scientists have long looked to nature and biology in order to understand and model solutions for complex real-world problems. The study of bionics bridges the...
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SubjectTerms Artificial Intelligence
Biochemical Engineering
Bioinformatics
Biomaterials
Biomedical Engineering and Bioengineering
Biomedical Engineering/Biotechnology
Engineering
Title Review and Classification of Bio-inspired Algorithms and Their Applications
URI https://link.springer.com/article/10.1007/s42235-020-0049-9
https://mpra.ub.uni-muenchen.de/8468/1/MPRA_paper_8468.pdf
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