The recent global pandemic highlighted the need for comprehensive strategies to tackle problems that transcend geographical and cultural boundaries. The size, scope, and complexity of current societal issues require the generation of new useful insights through more radical and robust collaboration within transdisciplinary teams of experts from the social sciences, engineering and computational sciences, and other fields.

The complex interactions between humans, technology, and the environment in a globally connected world make it challenging to build coherent models or rely on analyses derived from datasets collected often without context. There is an urgent need for complexity scientists in simulation, data science, and operations research to imagine new approaches where the strength of each discipline can be effectively leveraged to study large complex non-linear systems, such as pandemics, climate change, integration, or extremism. Anecdotal evidence suggests that such multidisciplinary collaborations are increasingly common but are not recognized as a novel approach to study complexity.

The goal of this Special Issue is to collect findings and lessons learned from research that tackles major societal issues (migration, pandemics, climate, religion, etc.) using a combination of computational simulation, data science, and operations research. These three fields have historically contributed to provide analytical solutions to complex problems and there is a renewed interest in using them in combination to address large complex non-linear systems. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

• Methodologies or frameworks (combinations of agent-based, system dynamics, and statistical modeling) to effectively address complex non-linear social systems in a collaborative environment
• Theoretical contributions that seek to unify modeling and simulation, data science, and operations research to solve large complex non-linear social systems
• Applications that combine modeling and simulation, data science, and operations research to address issues such as pandemics, cultural conflict, or climate change
• Discussions of the challenges and opportunities associated with engaging stakeholders when doing policy-relevant research on societal problems
• Contributions that contextualize these challenges within wider debates in the philosophy of science