Advances of Optimization Theory and Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 132
Special Issue Editors
Interests: mobile computing; optimization theory; machine learning; large language models; federated learning
Interests: edge computing; optimization theory; machine learning
Special Issue Information
Dear Colleagues,
This Special Issue, "Advances of Optimization Theory and Applications," invites researchers and practitioners to explore cutting-edge optimization techniques and their impactful applications across diverse fields, including but not limited to mobile computing environments, energy efficiency, application optimization, LLM-based optimization, federated learning, and edge computing. Optimization theory plays a pivotal role in enhancing performance, efficiency, and user experience across numerous applications, including real-time systems, machine learning, logistics, healthcare, finance, and network communication.
We seek original contributions that address theoretical advancements and innovative practical solutions, tackling unique challenges like limited computational resources, power constraints, latency sensitivity, and dynamic environments. Potential topics include adaptive resource allocation algorithms, energy-aware scheduling methods, low-latency optimization strategies, federated learning optimization, network design and optimization, logistics and supply chain optimization, and real-time data processing enhancements.
By encompassing a broad spectrum of applications, this Special Issue aims to bridge theoretical developments with practical implementations, fostering the creation of efficient, responsive, and intelligent systems across various domains. Contributions should provide rigorous analyses and novel methodologies and demonstrate clear applicability. We eagerly anticipate your valuable contributions, which will enhance both the theoretical foundations and practical applications in the dynamic field of optimization.
Dr. Jie Ren
Dr. Jie Zheng
Dr. Zhiqiang Li
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. 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.
Keywords
- application optimization
- edge computing
- mobile computing
- federated learning
- LLM-based optimization
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