This book applies both industrial engineering and computational intelligence to demonstrate intelligent machines that solve real-world problems in various smart environments. It presents fundamental concepts and the latest advances in multi-criteria decision-making (MCDM) techniques and their application to smart environments. Though managers and engineers often use multi-criteria analysis in making complex decisions, many core problems are too difficult to model mathematically or have simply not yet been modeled.
In response, as well as discussing AI-based approaches, Soft Computing for Smart Environments covers various optimization techniques, decision analytics, and data science in applying soft computing techniques to a defined set of smart environments, including smart and sustainable cities, disaster response systems, and smart campuses.
This state-of-the-art book will be essential reading for both undergraduate and graduate students, researchers, practitioners, and decision-makers interested in advanced MCDM techniques for management and engineering in relation to smart environments.
This book applies both industrial engineering and computational intelligence to demonstrate intelligent machines that solve real-world problems in various smart environments. This state-of-the-art book will be essential reading for both undergraduate and graduate students, researchers, practitioners.
Preface. Authors.
1. An Innovative Framework to Evaluate Smart and Sustainable Cities Using Fuzzy MCDM Method.
2. A Conceptual Design and Evaluation Framework for Assessing Smart Health Technologies.
3. An Intelligent Approach for Assessing Smart Disaster Response Systems.
4. A Facilitating Paradigm for Analyzing the Adaptation of Internet of Things Obstacles (IoTBs) to Waste Management in Smart Cities.
5. A Fusion Approach for Cloud Service Performance Assessment and Selection from Smart Data,
6. An Evaluation Approach for Prioritizing Performance of Sustainability Indicators for Smart Campuses.
7. Sustainable Supplier Selection for Smart Supply Chain.
8. Analyzing and Evaluating Smart Card Systems for Public Transportation. Index.
Mohamed Abdel-Basset is Associate Professor in the Faculty of Computers and Informatics, Zagazig University, Egypt. His work focuses on the application of multi-objective and robust metaheuristic optimization techniques. His current research interests include optimization, operations research, data mining, computational intelligence, applied statistics, decision support systems, robust optimization, engineering optimization, multi-objective optimization, swarm intelligence, evolutionary algorithms, and artificial neural networks.
Ripon K. Chakrabortty is Program Coordinator for the Master of Decision Analytics and the Masters of Engineering Science Programs, and team leader of the Decision Support and Analytics Group at the School of Engineering and Information Technology, UNSW Canberra. His research interests cover a range of topics in Operations Research, Project Management, Supply Chain Management, Artificial Intelligence, and Information Systems Management. Many organizations have funded his research programs.
Abduallah Gamal is a Senior Researcher in the Faculty of Computers and Informatics in the Department of Operations Research at Zagazig University, Egypt. His research interests include computational intelligence, optimization, swarm intelligence, evolutionary algorithms and neutrosophic sets and logic. He currently works on applying multi-criteria decision making.
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