Optimization and Computing using Intelligent Data-Driven Approaches for Decision-Making

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. This book: Addresses solving practical problems such as supply chain management, take-off, and healthcare analytics using intelligent computing. Presents a comparative analysis of machine learning algorithms for power consumption prediction. Discusses a machine learning-based multi-objective optimization technique for load balancing in an integrated fog cloud environment. Illustrates a data-driven optimization concept for modeling environmental and economic sustainability. Explains the use of heuristics and metaheuristics in supply chain networks and the use of fuzzy optimization in sustainable development goals. The text is primarily written for graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, mathematics and statistics, computer science and engineering.