Operations Research Proceedings 2021

This book gathers a selection of peer-reviewed papers presented at the International Conference on Operations Research (OR 2021), which was hosted online by the University of Bern from August 31 to September 3, 2021, and was jointly organized by the Operations Research Societies of Switzerland (SVOR/ASRO), Germany (GOR e.V.), and Austria (ÖGOR). 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 massive volumes of data to be processed and enable real-time predictive and prescriptive business analytics to drive decisions and actions. Lastly, it presents a selection of problems that are modeled and treated while taking into account uncertainty, risk management, behavioral issues, etc.

This book gathers a selection of peer-reviewed papers presented at the International Conference on Operations Research (OR 2021), which was hosted online by the University of Bern from August 31 to September 3, 2021, and was jointly organized by the Operations Research Societies of Switzerland (SVOR/ASRO), Germany (GOR e.V.), and Austria (ÖGOR). 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 massive volumes of data to be processed and enable real-time predictive and prescriptive business analytics to drive decisions and actions. Lastly, it presents a selection of problems that are modeled and treated while taking into account uncertainty, risk management, behavioral issues, etc.

This book gathers a selection of peer-reviewed papers presented at the International Conference on Operations Research (OR 2022), which was held at Karlsruhe Institute of Technology, Germany, on September 6-9, 2022. KIT’s Institute for Operations Research (IOR) hosted the conference together with the Institute for Industrial Production (IIP), the Institute for Automation and Applied Informatics (IAI), and the Institute for Material Handling and Logistics (IFL). 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.

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.

This book gathers selected high-quality papers presented at the 31st European Conference on Operational Research, which was held in Athens, Greece on June 11-14, 2021. It highlights the latest advances in the application of operations research (OR) to technology-driven areas in business, finance, and economics, covering both theoretical and methodological developments, as well as real-world case studies. It also explores the connections between OR and other analytical disciplines, such as soft computing and computer science, which can promote the development of new decision support technologies.

This book gathers a selection of refereed papers presented at the “International Conference on Operations Research OR2015,” which was held at the University of Vienna, Austria, September 1-4, 2015. Over 900 scientists and students from 50 countries attended this conference and presented more than 600 papers in parallel topic streams as well as special award sessions. Though the guiding theme of the conference was “Optimal Decision and Big Data,” this volume also includes papers addressing practically all aspects of modern Operations Research.

This book gathers a selection of peer-reviewed papers presented at the International Conference on Operations Research (OR 2023), which was held at Universität Hamburg, Germany, August 29–September 1, 2023. More than 700 scientists, practitioners, and students from mathematics, computer science, business/economics, and related fields attended the conference and presented more than 500 papers in plenary presentations, parallel topic streams, as well as special award sessions. The book discusses 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 encompasses addressing problems modeled and treated while considering factors such as uncertainty, risk management, and behavioral issues.