International Journal of Bio-Inspired Computation

Aims & Scope

IJBIC discusses the new bio-inspired computation methodologies derived from the animal and plant world, such as new algorithms mimicking the wolf schooling, the plant survival process, etc.

Topics covered include: -New bio-inspired methodologies coming from creatures living in nature artificial society- physical/chemical phenomena- New bio-inspired methodology analysis tools, e.g. rough sets, stochastic processes- Brain-inspired methods: models and algorithms- Bio-inspired computation with big data: algorithms and structures- Applications associated with bio-inspired methodologies, e.g. bioinformatics.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	2
2024	1.70

Journal Rank

Year	Value
2024	15730

Journal Citation Indicator

Year	Value
2024	278

SJR (SCImago Journal Rank)

Year	Value
2024	0.330

Quartile

Year	Value
2024	Q3

h-index

Year	Value
2024	45

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science and Mathematics, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Firefly algorithm, stochastic test functions and design optimisation

  Citation: 2181

  Authors: Xin She

• Bat algorithm: literature review and applications

  Citation: 797

  Authors: Xin She, Xingshi

• Bat algorithm for multi-objective optimisation

  Citation: 707

  Authors: Xin She

• Earthworm optimisation algorithm: a bio-inspired metaheuristic algorithm for global optimisation problems

  Citation: 440

  Authors: Gai Ge, Suash, Leandro Dos Santos

• The intelligent water drops algorithm: a nature-inspired swarm-based optimization algorithm

  Citation: 327

  Authors: Hamed Shah

• New inspirations in swarm intelligence: a survey

  Citation: 287

  Authors: R.S., H.S.

• A new metaheuristic optimisation algorithm motivated by elephant herding behaviour

  Citation: 276

  Authors: Gai Ge, Suash, Xiao Zhi, Leandro Dos Santos

• Review of meta-heuristics and generalised evolutionary walk algorithm

  Citation: 162

  Authors: Xin She

• Firefly algorithm with random attraction

  Citation: 148

  Authors: Hui, Wenjun, Hui, Shahryar

• An effective improved co-evolution ant colony optimisation algorithm with multi-strategies and its application

  Citation: 144

  Authors: Wu, Junjie, Yingjie, Huimin

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