1. AIMS AND SCOPE
Over the last five decades fuzzy optimization have found numerous successful applications in diverse fields including operational research, manufacturing, information technology, energy optimization, data science and smart cities, big data analytics and the list goes on. Fuzzy optimization has strongly influenced research and development in other areas of intelligent computing leading to many hybrid and deep learning systems. It has opened up new horizons in thinking, research and development and it will certainly guide us into another half century of progress. Actually, fuzzy optimization is one kind of the approximation of nonlinear optimization techniques, which has basically formed some systematic but not unified theory of fuzzy systems and other fuzzy-sets based methodologies. Fuzzy Optimization and Decision Making is an interdisciplinary area focusing upon methodologies for extracting useful knowledge and experiences from data technology. Specific topics include fuzzy sets, rough sets, statistical methods, parallel/distributed data mining, hybrid fuzzy optimization such as hybrid evolutionary and swarm intelligence methods and human interaction, big data optimization, IoTs, flexibility, reliability and robustness, smart systems in specific domains, high-dimensional data, energy optimization and software engineering, data science, analytics, etc.
The high complexity of neural systems and the large number of constituents with an often unknown functional interconnections lead to significant computational challenges. An important consideration is the development of mathematical models incorporating the many influences of randomness, noise, uncertainty and fuzziness in both their static and time-dependent versions. The quality of prediction by a model highly depends on the integration of imprecise data and the quantification of uncertain structural parameters. A sophisticated analysis of the influence of all types of randomness, uncertainty and noise is indispensable for the development of reliable computational and neural models and programs.
Objective of this special issue is to explore latest modeling, simulation and fuzzy optimization, related with and renewable energy, electronics and electricity, and various related subjects. This offers a concentrative venue for researchers to make rapid exchange of ideas and innovative research findings in fuzzy optimization and Operational Research. In particular, new interdisciplinary approaches in fuzzy optimization applications, computer science and engineering applications, or strong conceptual foundations in newly evolving topics are especially welcomed. We invite researchers and experts worldwide to submit high-quality innovative research papers and critical review articles on the subsequent potential topics.
2. TOPICS COVERED
The topics include but are not limited to:
o Power supply reliability
o System reliability
Fuzzy modeling and simulation
o Fuzzy cybercrime
Big Data Analytics and IoTs
o Cloud computing
3. SUBMISSION GUIDELINES
All authors should read ‘Information for Authors’ before submitting a manuscript
Submissions should be through the IEEE TFS journal website http://mc.manuscriptcentral.com/tfs-ieee.
It is essential that your manuscript is identified as a Special Issue contribution:
– Ensure you choose ‘Special Issue’ when submitting.
– A cover letter must be included which includes the title ‘Special Issue on Smart Fuzzy Optimization in Operational Research and Renewable Energy: Modelling, Simulation, and Applications’
4. IMPORTANT DATES
1 November 2019 – Submission Deadline
For Guidance only
January 2020 – Notification of the first round review
April 2020 – Revised submission due
July 2020 – Final notice of acceptance/reject
5. GUEST EDITORS
– Prof. Dr. Gerhard-Wilhelm Weber
Poznan University of Technology, Poland
Affiliation: IAM, METU, Ankara