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

This book comprehensively discusses nature-inspired algorithms, deep learning methods, applications of mathematical programming, and artificial intelligence techniques. It further covers important topics such as the use of machine learning and the Internet of Things and multi-objective optimization under Fermatean hesitant fuzzy and uncertain environment. This book: Addresses solving practical problems such as supply chain management, smart manufacturing, and healthcare analytics using intelligent computing and discusses solving the fuzzy inference system in ant colony optimization for traveling salesman problem Presents an overview of artificial intelligence (AI) and explainable AI decision-making (XAIDM) and illustrates a data-driven optimization concept for modeling environmental and economic sustainability Discusses machine learning-based multi-objective optimization technique for load balancing in integrated fog-cloud environment Explains the use of heuristics and metaheuristics in supply chain networks and the use of fuzzy optimization in sustainable development goals Discusses sustainable transit of hazardous waste, green fractional transportation system, perishable inventory, M-estimation of functional regression operator, and intuitionistic fuzzy sets applications The text is primarily written for graduate students and academic researchers in diverse fields, including operations research, mathematics, statistics, computer science, information and communication technology, and industrial engineering.