Computational Intelligence and Nature Inspired Algorithms
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Evolutionary Algorithms and Machine Learning".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 10
Special Issue Editors
Interests: swarm and evolutionary computation; computational intelligence; optimization; computer networks
Special Issues, Collections and Topics in MDPI journals
2. Department of Information Science, Faculty of Sciences, Toho University, 2-2-1 Miyama, Funabashi 274-8510, Japan
Interests: artificial intelligence; soft computing for optimization; evolutionary computation; computational intelligence
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are pleased to announce a call for papers for a Special Issue of Algorithms entitled “Computational Intelligence and Nature Inspired Algorithms”. This Special Issue provides a venue for researchers, academics, and practitioners to share recent advances in theory, methodology, and applications across computational intelligence and nature-inspired algorithms.
Computational intelligence encompasses the design, analysis, and application of nature-inspired or linguistically motivated methods, traditionally spanning evolutionary computation and swarm intelligence, neural networks, and fuzzy approaches. Swarm and evolutionary computation comprise a broad family of algorithms for solving challenging optimization problems—single- or multi-objective; continuous, discrete, or mixed-variable; constrained; combinatorial; and static, dynamic, or stochastic—arising in a wide range of real-world settings. Neural networks excel when correct behaviour is easier to learn by examples than to encode as rules, while fuzzy methods address vagueness and partial truths. These paradigms can also be mixed, combined, and hybridized to work together.
We welcome theoretical, experimental, and applied research, including (but not limited to) rigorous analyses, novel algorithmic designs, parameter landscapes, hybrid frameworks, reproducible benchmarking studies, and impactful applications in engineering, data science, logistics, planning, robotics, energy, healthcare, and beyond.
Dr. Nikola Ivković
Prof. Dr. Akemi Galvez Tomida
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- evolutionary computation
- swarm intelligence
- natural computation
- bioinspired optimization
- metaheuristics
- stochastic algorithms
- soft computing
- computational intelligence
- fuzzy methods
- neural networks
- ant colony optimization
- evolutionary algorithms
- particle swarm optimization
- differential evolution
- memetic algorithms
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