Advances in Optimal Transport: Algorithms, Theory, and Intelligent System Applications

Dear Colleagues,

Optimal transport (OT) theory has emerged as a transformative framework for modeling resource allocation, distribution networks, and decision-making under constraints. With rapid advances in computational methods and data-driven applications, novel algorithms are urgently needed to address high-dimensional, dynamic, and game-theoretic challenges in modern systems. This Special Issue seeks cutting-edge contributions that bridge theoretical innovations in OT with practical applications in intelligent transportation, emergency management, networked control, and complex systems.

We welcome submissions exploring both computational breakthroughs (e.g., entropy-regularized solvers, deep learning-based approximations, evolutionary metaheuristics) and domain-specific applications (e.g., crowd evacuation dynamics, multi-agent route optimization, spatially distributed resource allocation). Of particular interest are interdisciplinary studies integrating OT with evolutionary game theory for modeling competitive/cooperative behaviors, neural operators for high-dimensional OT mappings, or networked control strategies for large-scale infrastructure systems.

Relevant topics include (but are not limited to) the following:

• Scalable OT algorithms: Quantum-inspired optimization, metaheuristics, or GPU-accelerated solvers.
• Deep OT: Neural networks for Wasserstein metrics, generative modeling, or inverse OT problems.
• OT in intelligent transportation: Traffic flow optimization, ride-sharing, or EV charging networks.
• Emergency evacuation: Crowd dynamics, risk-aware routing, or real-time decision systems.
• Evolutionary game-theoretic OT: Multi-agent equilibria, incentive design, or swarm intelligence.
• Networked control applications: Supply chain resilience, smart grid logistics, or UAV coordination.
• OT for complex systems: Self-organizing networks, socio-technical systems, or sustainability challenges.

We welcome high-quality original research articles and reviews in order to advance the frontiers of OT theory and its role in next-generation intelligent systems.

We look forward to receiving your contributions.

Dr. Kun Li
Dr. Haibo Wang
Guest Editors

Manuscript Submission Information

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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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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.

• optimal transport algorithms
• emergency evacuation
• intelligent transportation systems
• evolutionary game theory
• deep learning
• networked control
• complex systems
• resource allocation