Metaheuristics and Machine Learning: Theory and Applications
A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Evolutionary Algorithms and Machine Learning".
Deadline for manuscript submissions: closed (31 May 2022) | Viewed by 4022
Special Issue Editors
Interests: metaheuristics; artificial intelligence; optimization, IoT and WSNs; data mining; image processing
Interests: renewable energy; smart grid; hybrid systems; power electronics; optimization and artificial intelligence
Interests: metaheuristics; bioinspired computation; image processing; machine learning; optimization
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, metaheuristics (MHs) have become essential tools for solving challenging optimization problems encountered in industry, engineering, biomedical, image processing, and the theoretical field. Several different metaheuristics exist, and new ones are under constant development. One of the most fundamental principles in our world is the search for an optimal state. Therefore, there exist a diverse range of MHs have been used for many years in the formulation and solution of computational problems. This special issue brings together outstanding research and recent developments in metaheuristics (MHs), Machine Learning (ML), and their applications in the industrial world. Therefore, recently, MHs have been combined with several ML techniques to deal with different global and engineering optimization problems, also real-world applications. Papers published in this special issue describe original works in different topics in science and engineering, such as Metaheuristics, Ariticial Intillegence, Machine learning, Soft Computing, Neural Networks, Multi-criteria decision-making, Energy efficiency, Sustainable development, etc.
Recommended Topics
The topics covered by this book will present a collection of high-quality research works written by renowned leaders in the field. We invite all researchers and practitioners to develop algorithms, systems, and applications, to share their results, ideas, and experiences. Topics of interest include, but are not limited to, the following:
▪ Hybrid and Parallelization Metaheuristics
▪ Multi-objective optimization
▪ Multilevel segmentation and Image processing
▪ Feature selection
▪ Reinforcement learning and Supervised learning
▪ Pattern recognition
▪ Ariticial Intillegence
▪ Fuzzy systems
▪ Data mining
▪ Computer vision
▪ Quantum Optimization
▪ Bioinformatics and Biomedical applications
▪ Engineering applications
Prof. Dr. Essam H. Houssein
Prof. Dr. Hegazy Rezk
Prof. Dr. Diego Oliva
Prof. Dr. Salah Kamel
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. 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 1600 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
- metaheuristics
- optimization
- convex optimization problem
- constrained optimization problem
- artificial Intelligence
- machine learning
- real-world applications
