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. Cover Half Title Title Page Copyright Page Dedication Table of Contents Preface Authors 1. An Innovative Framework to Evaluate Smart and Sustainable Cities Using Fuzzy MCDM Method 1.1 Introduction 1.2 Mathematical Preliminary 1.2.1 Fuzzy Set Theory 1.2.2 Fuzzy Operation 1.3 Solution Methodology 1.3.1 Connotation of ANP and TOPSIS 1.3.2 The Computational Steps of the Suggested Hybrid MCDM Approach 1.4 Application of the Suggested Methodology for the Case Study 1.5 Results and Discussion 1.6 Summary References 2. A Conceptual Design and Evaluation Framework for Assessing Smart Health Technologies 2.1 Introduction 2.2 MCDM Model 2.2.1 Fuzzy Set Theory 2.2.2 Fuzzy AHP 2.2.3 Fuzzy VIKOR 2.2.4 The Mathematical Steps of the Hybrid MCDM Framework 2.3 An Illustrated Example 2.3.1 Determination of Basic Information About the Problem 2.3.2 Computation of Criterion Weights with the Fuzzy AHP Method 2.3.3 Ranking of the Smart Health Technologies with the Fuzzy VIKOR Method 2.4 Results and Discussion 2.5 Summary 2.6 Exercises References 3. An Intelligent Approach for Assessing Smart Disaster Response Systems 3.1 Introduction 3.2 Smart Disaster Response Systems 3.3 MCDM Methods for Decision-Making 3.3.1 Fuzzy DEMATEL Method 3.3.2 Fuzzy EDAS Method 3.3.3 The Computational Steps of the Proposed Approach 3.4 An Illustrative Example 3.4.1 Model Implementation 3.4.2 Discussion 3.5 Summary 3.6 Exercises References 4. A Facilitating Paradigm for Analyzing the Adaptation of Internet of Things Obstacles (IoTBs) to Waste Management in Smart Cities 4.1 Introduction 4.2 IoTBs and Waste Management in Smart Cities 4.3 Data Collection and Methodology 4.3.1 Fuzzy DEMATEL Technique 4.3.2 The Implementation Steps of the Fuzzy DEMATEL Technique 4.4 Model Implementation 4.4.1 Results and Discussion 4.5 Summary 4.6 Exercises References 5. A Fusion Approach for Cloud Service Performance Assessment and Selection from Smart Data 5.1 Introduction 5.2 Mathematical Preliminary 5.2.1 Inceptions 5.2.1.1 Intuitionistic Fuzzy Sets (IFSs) 5.2.1.2 Pythagorean Fuzzy Sets (PFSs) 5.2.1.3 q-Rung Orthopair Fuzzy Sets (q-ROFSs) 5.3 Model 5.3.1 Entropy Method 5.3.2 CoCoSo Method 5.3.3 Computational Steps of the Applied Approach 5.4 Model Implementation 5.5 Results and Discussion 5.6 Summary 5.7 Exercises References 6. An Evaluation Approach for Prioritizing Performance of Sustainability Indicators for Smart Campuses 6.1 Introduction 6.2 Methodology 6.2.1 Entropy Method 6.2.2 TOPSIS Method 6.2.3 Computational Steps of the Approach Used 6.3 Case Study 6.4 Results and Discussion 6.5 Summary 6.6 Exercises References 7. Sustainable Supplier Selection for Smart Supply Chain 7.1 Introduction 7.2 Mathematical Preliminary 7.3 Methodology 7.3.1 CRITIC Method 7.3.2 CODAS Method 7.3.3 Computation Steps 7.4 Model Implementation 7.4.1 Case Study 7.4.2 Steps to Apply the Used Model 7.5 Results and Discussion 7.6 Summary 7.7 Exercises References 8. Analyzing and Evaluating Smart Card Systems for Public Transportation 8.1 Introduction 8.2 Methodology 8.2.1 PROMETHEE Method 8.2.2 Mathematical Model 8.3 Model Implementation 8.4 Results and Discussion 8.5 Summary 8.6 Exercises References Index
