Multi-Criteria Decision Making Theory and Applications in Sustainable Healthcare

This book examines the advantages of evolutionary algorithms and traditional multi-criteria decision making (MCDM) techniques together in the healthcare field. It also discusses smart technology integration practices for general medical centers.

Mohamed Abdel- Basset (Senior Member, IEEE) received the B.Sc., M.Sc., and PhD degrees in operations research from the Faculty of Computers and Informatics, Zagazig University, Egypt. He is currently Associate Professor with the Faculty of Computers and Informatics, Zagazig University. He has published more than 200 articles in international journals and conference proceedings. He is working 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. He is an editor and a reviewer of different international journals and conference. Ripon K. Chakrabortty (Senior Member, IEEE) is the Program Coordinator for Master of Decision Analytics and Master of Engineering Science Programs, and the team leader of 'Decision Support & Analytics Research Group' at the School of Engineering & Information Technology, UNW Canberra, Australia. He obtained his PhD from the same University in 2017 while completing his MSc and BSc from Bangladesh University of Engineering and Technology in Industrial and Production Engineering in 2013 and 2009, respectively. He has written four book chapters and over 170 technical journal and conference papers. His research interest covers a wide range of topics in Operations Research, Project Management, Supply Chain Management, Artificial Intelligence, and Information Systems Management. Many organizations have funded his research program, such as the Department of Defence, Commonwealth Government, Australia. He is an associate editor and a reviewer of different international journals and conferences. Abduallah Gamal (Member, IEEE) is a senior researcher at Zagazig University, Faculty of Computers and Informatics, Department of Operations Research, Egypt. He obtained his bachelor's, master's, and PhD degrees in Information Systems in 2012, 2016, and 2021, respectively, from the Faculty of Computers and Informatics, Department of Operations Research, Zagazig University, Egypt. His area of interest includes computation intelligence, Optimization, Swarm Intelligence, Evolutionary Algorithms, and neutrosophic sets and logic. He is working on the application of multi-criteria decision-making. He is also a reviewer in different international journals and conferences. He has published more than 45 articles in international journals and conference proceedings.

Chapter 1. Developing an Efficient Model for Supplier Performance Evaluation and Selection in Healthcare Industries with Incomplete Information. Chapter 2. A Consolidated Strategic for Analyzing and Ranking Smart Healthcare Management System Portfolios in a Resource-Restricted Environment. Chapter 3. A Computational Reliance Approach for Assessing Healthcare Service Quality Aspects and their Measurement in an Uncertain Environment. Chapter 4. An Efficient Verified and Provable Approach for Recommending Suitable Mobile Healthcare Products under Uncertainty Environment. Chapter 5. Establishing a Decision-Making Strategy for a Causality Analysis of Current Status and Potential Challenges and Selection of Healthcare Waste Treatment Methods. Chapter 6. Assessment the Usability and Understanding the Perception Towards mHealth Applications in Practice Related to Type 2 Diabetes Mellitus. Chapter 7. Development of a Multi-Criteria Decision-Making Based Assessment Model for Cloud Computing Adoption in the Medical and Healthcare Sector. Chapter 8. An Optimized Neutrosophic Parameterized Multi-Criteria Decision-Support System for a Medical Device Selection in the Healthcare Industry.