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Advances in Markovian Dynamic and Stochastic Optimization Models in Diverse Application Areas
This special issue belongs to the section “D1: Probability and Statistics“.
Special Issue Information
Dear Colleagues,
Markovian dynamic and stochastic optimization is an active research area concerning the design and analysis of optimal or nearly optimal policies for Markov decision models of stochastic systems evolving over time. Such models arise in a wide variety of application areas, including manufacturing, marketing, service operations, finance, call centers, and cloud service systems.
In this Special Issue, we shall collect recent theoretical and application-oriented advances regarding Markovian dynamic and stochastic optimization models in any application area. This includes the design and analysis of optimal and nearly optimal policies, performance analysis, large-scale systems, queueing systems, bandit models,and computational studies.
Prof. Dr. José Niño-Mora
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 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 250 words) can be sent to the Editorial Office for assessment.
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
- Markov decision processes
- stochastic dynamic programming
- optimal policies
- optimal control
- queueing systems
- bandit models
- reinforcement learning
- machine Learning
- operations research
- dynamic and stochastic optimization
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