Decision-Making Models and Applications in Manufacturing Environments

Pushpdant Jain, PhD, is an Assistant Professor in the School of Mechanical Engineering at VIT Bhopal University, India. Prior to academia, he served in industry for six years. He has published research papers in international peer-reviewed journals and has published several book chapters. Dr. Jain has participated in international conferences, is an active member of the European Society of Bio-Mechanics and life member of the International Association of Engineers, Indian Institution of Industrial Engineering, and Indian Society for Technical Education. He was named Research Scholar of the Year (2018) by NIT Rourkela for his PhD work.

Kumar Abhishek, PhD, is an Assistant Professor in the Mechanical and Aero-Space Engineering Department at the National Institute of Infrastructure, Technology, Research and Management, Ahmedabad, India. His area of research mainly focuses on manufacturing and industrial engineering, modeling and optimization of production processes, and composite machining. He has many publications in reputed journals and international conference publications to his credit. He organizes a workshop every consecutive year titled MOOMESA―Multi Objective Optimization Methods for Engineering and Scientific Applications.

Prasenjit Chatterjee, PhD, is Dean (Research and Consultancy) at the MCKV Institute of Engineering, West Bengal, India. He has over 100 research papers published in international journals and peer-reviewed conferences. He has authored and edited more than 15 books on intelligent decision-making, supply chain management, optimization techniques, risk, and sustainability modelling. Dr. Chatterjee is the Editor-in-Chief of the Journal of Decision Analytics and Intelligent Computing as well as a series editor for several book series. Dr. Chatterjee is one of the developers of two multiple-criteria decision-making methods: Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) and Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (RAFSI).