Advances in Best-Worst Method: Proceedings of the Second International Workshop on Best-Worst Method (BWM2021)

This book presents recent advances in the theory and application of the Best-Worst Method (BWM). It includes selected papers from the Second International Workshop on Best-Worst Method (BWM2021), held in Delft, The Netherlands from 10-11 June, 2021, and provides valuable insights on why and how to use BWM in a diverse range of applications including health, energy, supply chain management, and engineering. The book highlights the use of BWM in different settings including single decision-making vs group decision-making, and complete information vs incomplete and uncertain situations. The papers gathered here will benefit academics and practitioners who are involved in multi-criteria decision-making and decision analysis.

Jafar Rezaei is an Associate Professor and Head of the Transport and Logistics Section at the Department of Engineering Systems and Services, Faculty of Technology, Policy and Management, Delft University of Technology, The Netherlands. He completed his PhD at the same university. He has a background in Operations Research, and has published in several peer-reviewed journals. He is the Editor-in-Chief of Journal of Supply Chain Management Science and serves as an editorial board member for several scientific journals. In 2015, he developed the Best-Worst Method (BWM). His main research interests are in multi-criteria decision-making and its applications in different fields. Matteo Brunelli is an Associate Professor of Mathematical Methods at the Department of Industrial Engineering, University of Trento, Italy. He received his Bachelor and Master degrees from the University of Trento, Italy, and his PhD from Åbo Akademi University, Finland. He spent five years as a Postdoctoral Researcher at Aalto University, Finland. His research interests include decision analysis, preference modelling, mathematical representations of uncertainty and fuzzy sets. Majid Mohammadi is a Postdoctoral Researcher at Vrije Universiteit Amsterdam (VU), The Netherlands. Prior to joining VU, he pursued postdoctoral research at Eindhoven University of Technology, and completed his PhD at Delft University of Technology, The Netherlands, earning a cum laude, the highest distinction in the Dutch academic system. His research interests are in methodological contributions to various domains such as multi-criteria decision-making, machine and deep learning, Bayesian statistics, and statistical learning theory.