Decision Analytics and Intelligent Computing: Models And Applications

Guest Editors:
Dr. Prasenjit Chatterjee
Department of Mechanical Engineering, MCKV Institute of Engineering, India
Website | E-Mail
Interests: Decision Analytics, Sustainability Modelling, Optimization, Multi-criteria Decision Making, Uncertainty Modelling.

Dr. Željko Stević
University of East Sarajevo, Faculty of Transport and Traffic Engineering, Doboj, Bosnia and Herzegovina
Website | E-Mail
Interests: Operations Research and Optimization, Multi-criteria Decision Making, Financial Modelling, Soft Computing, Uncertainty Modelling, Transport, Logistics, SCM.

Dr. Morteza Yazdani
ESIC Business & Marketing School, Spain
Website | E-Mail
Interests: Multi-criteria Decision Making, Sustainability Modelling, Intelligent Computing, Fuzzy Modelling.

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Special Issue Information

In recent years, there has been a growing interest in data-driven decision analytics and intelligent computing which attempt to integrate technologies from computer science, information science, operations research, applied mathematics, and statistics. This amalgamation is allowing policymakers to understand the dynamics of their business, anticipate market shifts, and manage risks to stay at the forefront of competition by innovative strategic decisions. Data is everywhere and continuing to grow massively, which has created a huge demand for qualified experts who can uncover valuable insights from data. As the study of data has become more popular, there is an urgent demand for researches on high-level computational intelligence and computing services for analyzing this significant area of information science. Real-world decision systems require consideration and analysis of multiple criteria that affect final decisions. However, one of the most challenging issues for such a system is to effectively handle real-world uncertainties that cannot be eliminated. These uncertainties include various types of information that are incomplete, imprecise, and vague. Therefore, to obtain valuable information within the data, one must use a variety of innovative analytical methods, such as computational intelligent techniques, decision trees, expert systems, fuzzy set, machine learning, multi-criteria decision making, neutrosophic set, neural networks, optimization rough set, support vector machines and simulation to name a few.

Tentative Topics:

Focusing on a variety of methods, systems as well as practical case studies, this Special Issue aims to provide a common platform for global research communities to share their novel research results, findings, and innovations for a diverse range of engineering and management applications. This Special Issue, therefore, solicits high-quality original research and review articles that cover novel, cutting-edge technologies, and methods concerned with but not limited to:

  • Applications of interdisciplinary tools and techniques in solving real-time engineering and management problems with the latest computing and optimization technologies and approaches.
  • Applications of bio-inspired optimization, data mining, evolutionary computing, machine learning, mobile computing, neural computing, and soft computing algorithms
  • Aggregation operators, multi-criteria decision-making models and their implementations in real-world applications
  • Intelligent decision-support systems
  • Latest trends and concepts in data analytics and sustainable computing methods and applications.
  • Use of knowledge and data-driven hybrid/integrated decision-making models

During submission of the papers for the special issue select section: Spec_iss: Decision Analytics and Intelligent Computing: Models And Applications

Proposed Dates:

Paper Submission Starts: 1st December 2020;
Paper Submission Closes: 30th August 2021;
Expected Publication of Special Issue: September 2021.