Optimization and Computing using Intelligent Data‐Driven Approaches for Decision‐Making; Artificial Intelligence Applications

This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming and artificial intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0 and social responsibility Cover Half Title Series Page Title Page Copyright Page Table of Contents About the Editors List of Contributors 1 Linking Green Supply Chain Management Practices with Competitiveness, Industry 4.0, and Social Responsibility 2 Comparative Analysis of Machine Learning Algorithms for the Power Consumption Prediction 3 Prediction of Cardiovascular Disease using Information Gain, Artificial Neural Network, and CART 5.0 Algorithms 4 Weighting of Logistics Management Factors by SWARA and DELPHI Methods 5 Evaluation of Daily Management with Standard Deviation and MOOSRA Tools in Hospitals 6 Machine Learning-based Multi-objective Optimization Technique for Load Balancing in Integrated Fog-cloud Environment 7 Perishable Inventory Fuzzy Optimization Model with Uncertain Deterioration and Preservation Investment 8 Employing Fuzzy Inference System in ant Colony Optimization for Travelling Salesman Problems 9 Type-2 Gaussian Neuro-fuzzy VIKOR Technique in Multi-criteria Decision-making for Medical Diagnostic 10 Overview of AI and Explainable AI Decision-making (XAIDM) 11 Harnessing the Power of Industry 4.0: Synergizing Smart Manufacturing, Supply Chain, and Reshoring Strategies 12 Digital Revolution in cold Supply Chain Management Related to the Food Industry 13 The Impact of Blockchain Technology and Decentralized Supply Chain on Production Index