Preface to the Special Issue on Decision Support: Combining Technology and Algorithms to Solve Complex Problems.

This special issue is based on the program area “Decision support” of the EURO 2021 conference held online and on-site in Athens, Greece, on July 11–14, 2021. It contains papers presented at the conference and later submitted for this special issue, as well as additional papers submitted in response to an open call for papers after the conference. More than 30 papers were submitted for this special issue and were processed following the regular review procedures of ITOR thanks to a large international committee. Finally, we were able to accept the 14 papers collected in this special issue. This special issue focuses on the new possibilities that recent developments in information technology and algorithms offer for decision support. The papers collected in this special issue give a comprehensive overview of different areas in which the availability of rich data improved processing capabilities and algorithms, and the possibility to connect and involve a large number of stakeholders and users in decision processes have changed and enhanced the possibilities of decision support. We have grouped the papers of this special issue into four topic groups. The first group contains two papers using large-scale data sets that have become available through information technology for forecasting problems with a focus on healthcare applications. These papers show that both statistical methods and machine learning can be useful tools for predicting demand for healthcare facilities and how these forecasts can be used for better planning of capacities. The next group of papers focuses on computational methods and algorithms to solve complex decision problems. The focus is on applications in production and logistics, but the methods presented here could also be useful for other decision problems. This group of five papers contains both general algorithmic contributions for the design of complex systems as well as papers that focus on specific scheduling and resource allocation problems. A common characteristic of these papers is that they consider multiple objectives, such as idle time, the number of workstations needed, or the costs of adjusting machines to tasks. The applications covered in these papers also show the importance of recent trends such as the circular economy and the increased use of sharing platforms to use resources jointly and thus more efficiently. The third group in this special issue contains papers related to supply chain management. Complex supply chains involve the coordination of multiple actors and are another digital age phenomenon because only elaborate communication technology and algorithms enable such coordination. The papers in this group combine methods from game theory with other concepts to support decision-makers in a complex and rapidly changing environment. The last group of papers deals with managing large-scale projects in contexts such as big IT development projects or projects in the public sector involving multiple stakeholders. These papers provide frameworks that enable multiple stakeholders to meaningfully contribute to decision-making in large-scale projects. They also illustrate the difficulties that real-life large-scale projects face in terms of availability and quality of data, and they provide suggestions for how to make complex decision-making methods accessible to stakeholders with varying backgrounds by using concepts of gamification. All these papers are not just conceptual developments, but the methods and tools presented here were used in actual applications. The papers collected in this issue span various application areas and methods. Still, they share some common elements. For example, they employ state-of-the-art methods for forecasting, solving complex optimization problems, or connecting various actors. Moreover, many are based on real applications to problems in organizations and society. They thus show that essential developments in Operations Research do not take place in isolation but, as it has always been the tradition of the field, are driven by the actual needs and requirements of decision-makers in solving complex problems. Thus, the papers in this special issue show many aspects of the valuable contributions that OR can make in solving today's manifold problems.