Algorithms in Nonsmooth Optimization
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Algorithms for Multidisciplinary Applications".
Deadline for manuscript submissions: 31 May 2025 | Viewed by 804
Special Issue Editor
Interests: convex analysis; convex optimization; monotone operators; vector optimization
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In this Special Issue of Algorithms, we welcome contributions presenting and/or analyzing iterative methods for solving nonsmooth optimization problems and real-life applications that can be modeled in this way. A preference is given to splitting proximal point type methods and improvements of existing ones as well as iterative procedures for solving convex and nonconvex optimization problems where the involved functions lack differentiability. However, submissions on other types of iterative methods for solving nonsmooth optimization problems are welcome as well. In particular, extensions to multiobjective and vector optimization of known algorithms from scalar optimization are of special interest. Iterative methods for solving monotone inclusions, variational inequalities and equilibrium problems involving nonsmooth functions as well as continuous versions of proximal point type algorithms by means of dynamical systems and differential inclusions will also be considered. The proposed algorithms are expected to be illustrated by means of computational results; however, theoretical schemes of potential high interest can be accepted for publication as well as those hinting toward possible implementation approaches. Possible applications of the proposed iterative methods can be found in fields such as artificial intelligence, machine learning, location and logistics, game theory, image processing, etc.
Dr. Sorin-Mihai Grad
Guest Editor
Manuscript Submission Information
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Keywords
- proximal point method
- convex optimization problem
- nonsmooth optimization problem
- splitting technique
- image processing
- machine learning
- stochastic proximal algorithm
- location theory
- game theory
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