Simulation and process mining: review and outlook

Abstract

Modeling and simulation of business processes have consistently played a pivotal role in science and industry, increasingly benefiting from process mining algorithms that enable the generation of models and parameter extractions. This paper presents a systematic literature review that explores the integration of simulation with process mining techniques, offering a comprehensive overview of contemporary methodologies, applications, and challenges within this inter-disciplinary field. Special emphasis is placed on how simulation approaches are employed and enhanced through process mining, revealing opportunities for improved accuracy, scalability, and applicability in complex process environments. First, network analysis enables the identification of underlying patterns and relationships within the research landscape, revealing insights that may not be captured by conventional review methods. Second, a structured literature analysis provides a comprehensive framework that delineates key modelling tasks, categorizes application domains, tools, and validation strategies, and identifies This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature's AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx. 1 gaps and opportunities at the intersection of simulation and process mining, discussing future advancements in the field.