Data Analytics, Algorithms and Artificial Intelligence in Transport, Finance and Healthcare
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Randomized, Online, and Approximation Algorithms".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 1
Special Issue Editors
Interests: metaheuristics; simulation; machine learning; transportation; risk analysis
Special Issues, Collections and Topics in MDPI journals
Interests: simulation; artificial intelligence; optimization; parallel and distributed computing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Modern industries and organizations face growing challenges in decision-making, efficiency, and digital transformation. Advanced business analytics, artificial intelligence, and optimization algorithms are key tools to address these challenges, bridging research and practice. For this Special Issue of Algorithms, we are seeking high-quality contributions that demonstrate innovative methods, practical applications, and interdisciplinary approaches with tangible industrial or enterprise impact.
We welcome original research and application-oriented papers on topics including, but not limited to, the following:
- Business Analytics: Predictive modeling, decision support systems, and advanced analytics for strategic management and operational improvement.
- Artificial Intelligence: Machine learning, Generative AI, and AI-driven solutions for enterprise digitalization, process automation, and intelligent decision-making.
- Industrial Optimization: Metaheuristic optimization methods applied to transportation, logistics, supply chains, manufacturing, production planning, finance, and insurance.
- Computing and Algorithm Design: Computational techniques, frameworks, and software supporting analytics, AI, and optimization in practical applications.
This Special Issue targets researchers, practitioners, and industry professionals working at the intersection of analytics, AI, and optimization. Submissions that combine methodological innovation with practical relevance, including case studies, technology transfer initiatives, and interdisciplinary approaches, are particularly encouraged. Contributions inspired by events such as ValencianTech’26 (https://valenciaicsotech.webs.upv.es/) and the DSS’26 (https://decisionsciencesummit.com/) are welcome, but participation in these events is not required.
Prof. Dr. Angel A. Juan
Dr. Javier Panadero
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 250 words) can be sent to the Editorial Office for assessment.
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
- business analytics
- artificial intelligence
- industrial optimization
- computing and algorithm design
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