Springer Operations Research Proceedings 2019: Selected Papers of the Annual International Conference of the German Operations Research Society (GOR), Dresden, Germany, September 4-6, 2019

This book gathers a selection of peer-reviewed papers presented at the International Conference on Operations Research (OR 2019), which was held at Technische Universität Dresden, Germany, on September 4-6, 2019, and was jointly organized by the German Operations Research Society (GOR) the Austrian Operations Research Society (ÖGOR), and the Swiss Operational Research Society (SOR/ASRO). More than 600 scientists, practitioners and students from mathematics, computer science, business/economics and related fields attended the conference and presented more than 400 papers in plenary presentations, parallel topic streams, as well as special award sessions. The respective papers discuss classical mathematical optimization, statistics and simulation techniques. These are complemented by computer science methods, and by tools for processing data, designing and implementing information systems. The book also examines recent advances in information technology, which allow big data volumes to be processed and enable real-time predictive and prescriptive business analytics to drive decisions and actions. Lastly, it includes problems modeled and treated while taking into account uncertainty, risk management, behavioral issues, etc. From the Back Cover This book gathers a selection of peer-reviewed papers presented at the International Conference on Operations Research (OR 2019), which was held at Technische Universität Dresden, Germany, on September 4-6, 2019, and was jointly organized by the German Operations Research Society (GOR) the Austrian Operations Research Society (ÖGOR), and the Swiss Operational Research Society (SOR/ASRO). More than 600 scientists, practitioners and students from mathematics, computer science, business/economics and related fields attended the conference and presented more than 400 papers in plenary presentations, parallel topic streams, as well as special award sessions. The respective papers discuss classical mathematical optimization, statistics and simulation techniques. These are complemented by computer science methods, and by tools for processing data, designing and implementing information systems. The book also examines recent advances in information technology, which allow big data volumes to be processed and enable real-time predictive and prescriptive business analytics to drive decisions and actions. Lastly, it includes problems modeled and treated while taking into account uncertainty, risk management, behavioral issues, etc. About the Author Dr. Janis S. Neufeld is senior researcher at the Chair of Industrial Management and leader of the research group Operations Management at Technische Universität Dresden, Germany, where he also received his PhD on scheduling in cellular manufacturing. His major research interests are the development and application of optimization methods to complex planning problems in manufacturing and logistics. He has worked on several operations research projects with partners from industry, which covered topics such as railway crew scheduling, predictive maintenance and lot sizing. Professor Udo Buscher is full professor for Industrial Management at Technische Universität Dresden, Germany, where he teaches courses on operations management and operations research. He studied at the University of Göttingen, Germany, received a PhD from Technische Universität Dresden, and finished his habilitation at the University of Würzburg, Germany. His research interests include production planning and control, supply chain management and scheduling with a strong focus on operations research, decision science, applied algorithms and game theory. He carried out a large number of projects with companies in which the application of OR methods plays a central role. His research results are published in leading international academic journals. Prof. Dr. habil. Rainer Lasch holds the Chair of Business Administration,