Symmetry-Driven Artificial Intelligence for Logistics and Operations
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".
Deadline for manuscript submissions: 30 December 2025 | Viewed by 52
Special Issue Editors
Interests: digital; resilient; sustainable and circular supply chain; deep reinforcement learning; multi agent systems
Interests: Lean Six Sigma; Industry 4.0; circular economy; supply chain management
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Symmetry is becoming an increasingly important concept in artificial intelligence, with exciting potential for real-world applications—particularly within the domain of logistics. This Special Issue welcomes original research at the crossroads of mathematical symmetry, AI methods, and logistics optimization, with a special emphasis on industrial and healthcare contexts.
We are particularly interested in work that explores how symmetry—such as repeating patterns in demand over time, similarities in distribution networks, or interchangeable resource assignments—can be used to improve decision making and planning. The goal is to highlight how recognizing these patterns can lead to smarter, more adaptable systems for managing supply chains, allocating resources, and streamlining operations.
By tapping into these underlying structures, researchers and practitioners can develop models that help reduce waste, cut costs, and improve the quality and reliability of services, especially in sectors where efficiency, sustainability, and resilience are critical.
Topics of interest include (but are not limited to) the following:
- Equivariant and Invariant Neural Networks;
- Supply Chain Optimization;
- Mathematical Symmetry in AI;
- Predictive Analytics for Logistics and Supply Chains;
- Intelligent Resource Allocation and Scheduling;
- Invariant Models and Architectures;
- Healthcare Logistics and Patient Flow Optimization;
- Industrial Flow and Production System Management;
- Temporal Demand Forecasting and Pattern Recognition;
- Digital Twins for Supply Systems and Operations;
- Symmetry-Aware Algorithms for Decision Support.
We welcome both original research articles and comprehensive review papers that align with the scope of Symmetry.
We look forward to receiving your valuable contributions and to showcasing innovative research at the crossroads of symmetry, artificial intelligence, and logistics.
Dr. Asmaa Benghabrit
Dr. Cherrafi Anass
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. Symmetry 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 2400 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
- supply chains
- neural networks
- artificial intelligence
- predictive analytics
- logistic
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