Prasenjit Chatterjee

The 1st Doctoral Colloquium on Artificial Intelligence Research (DCAIR-2025) marks an important step toward advancing cutting-edge research, encouraging intellectual collaboration, and promoting academic dialogue in the field of Artificial Intelligence (AI). Organized by Adonic Informatics, in collaboration with MBien Analytica and Systems, this inaugural edition of DCAIR was held on 30th August 2025, through online mode, bringing together a vibrant community of research scholars, academicians, and practitioners from diverse disciplines and institutions across India and abroad. The central vision of DCAIR-2025 is to create a knowledge-driven forum that promotes cutting-edge research in AI, data science, and computational intelligence, while encouraging interdisciplinary perspectives that address real-world challenges.

This new volume provides detailed insight into supply chain management (SCM) and supply chain performance measurement (SCPM) in the textile industry. The book provides a comprehensive set of performance sub-criteria for the evaluation of SCPM, offering the information needed to understand, implement, and evaluate the supply chain performance of the textile industry and its cyclic processes.Using the Delphi method (a process used to arrive at a group opinion or decision by surveying a panel of experts), the authors studied several companies of diverse sizes and applied an analytical hierarchy process to establish crucial performance measurement criteria and sub-criteria. Around 80 textile industry personnel were contacted, including general managers, factory managers, managers, assistant managers, executives, and supervisors involved in various functions related to textile supply chains to discuss procurement, production, and distribution alternatives. The authors employed the multi-criteria decision-making technique, i.e. analytical hierarchy process, for executing pair-wise comparison and establishing priority weights of criteria, sub-criteria, and for estimating the contribution of supply chain cyclic processes to overall supply chain performance.

This book introduces the step-by-step processes involved in using MCDM methods, starting from problem formulation, model development, and criteria weighting to the final ranking of the alternatives. The authors explain the different MCDM methods that can be used in specific manufacturing environments. The book explains the conceptual frameworks of how these methods are applied with special focus on their applicability and usefulness. The authors begin with an introduction to multi-criteria decision-making, followed by explanations of 29 MCDM methods and their applications. The final sections of the book describe helpful normalization techniques and criteria weight measurement techniques. The collection of diverse range of manufacturing applications and case studies presented here will aid readers in applying cutting-edge MCDM methods to their own manufacturing projects. As both a research and teaching tool, this book encourages critical and logical thinking when applying MCDM methods for solving complex manufacturing decision-making problems.

This book addresses the problem of waste management by using multi-criteria decision-making (MCDM) methods. The authors discuss how to apply MCDM, a complex decision-making tool that involves both quantitative and qualitative factors, to develop strategies for effective waste management using various optimization models to rank alternatives, while also incorporating the concerns and needs of multiple stakeholders to find the most optimal decisions for various types of wastes. Typically, there does not exist a single optimal solution to waste problems; with help of MCDM, far better solutions can often be found and utilized to facilitate sustainable waste management techniques in various industries.This book provides unique, effective, and quick decision-making strategies for waste management. With the ever-increasing population and continuing human development, the problem of managing waste becomes increasingly essential, and this volume helps lead the way to finding sustainable solutions.

This book explores the significance, challenges and benefits of digital twin technologies; it focuses in particular on various architectures, applications and challenges in the implementation of digital twins to Machine Learning and Internet of Things capabilities. Through the analysis of smart city and smart manufacturing case studies, the book explores the benefits of digital technologies in the Industry 4.0 Era.

This book covers the emerging applications of different computational and optimization techniques in order to achieve a sustainable agriculture. A sustainable agricultural management requires tools in providing integrated, area-specifi c, and interpreted prediction or forecasting and guidance in every aspect in agriculture.

This book addresses the problem of waste management by using multi-criteria decision-making (MCDM) methods. The authors discuss how to apply MCDM, a complex decision-making tool that involves both quantitative and qualitative factors, to develop strategies for effective waste management using various optimization models to rank alternatives, while also incorporating the concerns and needs of multiple stakeholders to find the most optimal decisions for various types of wastes. Typically, there does not exist a single optimal solution to waste problems; with help of MCDM, far better solutions can often be found and utilized to facilitate sustainable waste management techniques in various industries.This book provides unique, effective, and quick decision-making strategies for waste management. With the ever-increasing population and continuing human development, the problem of managing waste becomes increasingly essential, and this volume helps lead the way to finding sustainable solutions.