Special Issue "Algorithms in Convex Optimization and Applications"

A special issue of Algorithms (ISSN 1999-4893).

Deadline for manuscript submissions: 31 July 2019

Special Issue Editor

Guest Editor
Dr. Sorin-Mihai Grad

Faculty of Mathematics and Computer Science, Leipzig University, Augustusplatz 10, 04109 Leipzig, Germany
Website | E-Mail
Interests: continuous optimization; numerical and applied optimization; vector and set-valued optimization; convex and nonsmooth analysis; monotone operators

Special Issue Information

Dear Colleagues,

During the last half century, optimization problems, consisting in minimizing a (sum and/or other combination of) convex function(s) (often subject to convex constraints), have been intensively investigated and various methods have been proposed to iteratively solve such problems. One of the most important such methods is the proximal point one introduced by Martinet and extended by Rockafellar and other authors, that it still intensively used due to the employment of the so-called splitting techniques, and thanks to direct applications in fields such as image processing and support vector machines classification problems. However, there are still many open questions and unsolved problems in this research area. For instance, the convergence of an algorithm that performs well on a class of problems is still uncertain (under standard hypotheses) or is quite slow for others.

The main concern of this Special Issue of Algorithms consists in papers dealing with iterative methods for solving convex optimization problems and applications that can be modelled as such, respectively. Special interest will be given to novel approaches to proximal point methods and significant improvements (e.g., better convergence properties or convergence under lighter hypotheses) of existing algorithms, as well as to iterative methods for solving constrained convex optimization problems. Extensions to the nonconvex case or multiobjective optimization will be taken into consideration as well, provided they are motivated by concrete applications. Investigations on connections to similar algorithms for solving monotone inclusions or dynamical systems can be considered provided the main focus of the contribution is on convex optimization problems. Among the possible application fields we note machine learning, clustering, location theory, game theory, signal processing and finance mathematics, but this list is far from being comprehensive.

Dr. Sorin-Mihai Grad
Guest Editor

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 papers will be 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. 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 1000 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.


  • Proximal point method
  • Convex optimization problem
  • Constrained optimization problem
  • Splitting technique
  • Image processing
  • Machine learning
  • Stochastic proximal algorithm
  • Location theory
  • Game theory

Published Papers (1 paper)

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Open AccessArticle A Cross-Layer Optimization QoS Scheme in Wireless Multimedia Sensor Networks
Algorithms 2019, 12(4), 68; https://doi.org/10.3390/a12040068
Received: 20 January 2019 / Revised: 15 March 2019 / Accepted: 26 March 2019 / Published: 30 March 2019
PDF Full-text (937 KB) | HTML Full-text | XML Full-text
There are two main challenges in wireless multimedia sensors networks: energy constraints and providing DiffServ. In this paper, a joint flow control, routing, scheduling, and power control scheme based on a Lyapunov optimization framework is proposed to increase network lifetime and scheduling fairness. [...] Read more.
There are two main challenges in wireless multimedia sensors networks: energy constraints and providing DiffServ. In this paper, a joint flow control, routing, scheduling, and power control scheme based on a Lyapunov optimization framework is proposed to increase network lifetime and scheduling fairness. For an adaptive distribution of transmission opportunities, a differentiated queueing services (DQS) scheme is adopted for maintaining data queues. In the Lyapunov function, different types of queues are normalized for a unified dimension. To prolong network lifetime, control coefficients are designed according to the characteristics of the wireless sensor networks. The power control problem is proved to be a convex optimization problem and two optimal algorithms are discussed. Simulation results show that, compared with existing schemes, the proposed scheme can achieve a better trade-off between QoS performances and network lifetime. The simulation results also show that the scheme utilizing the distributed media access control scheme in scheduling performs best in the transmission of real-time services. Full article
(This article belongs to the Special Issue Algorithms in Convex Optimization and Applications)

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