Hybrid Modeling and Simulation

The unique book advances understanding of modelling complex systems using hybrid approaches that combine discrete-event, agent-based, and system dynamic simulations with research approaches and artefacts from other scientific disciplines.As systems become increasingly large and complex, it is a challenge to capture the intricacies of the underlying system and offer novel forms of analysis using only models that employ a single simulation technique. Thus, a shift towards mixing methods is necessary. The book underscores the importance of both hybrid simulation (employing techniques primarily developed in the field of modelling and simulation) and hybrid modelling (incorporating simulation with methods from wider disciplines such as applied computing, data science, engineering, and soft/qualitative operations research). Furthermore, the text aims to inspire further research and practice of blending disciplinary techniques with computer simulation, fostering the growth of cross-disciplinary hybrid models.Topics and features:Provides a comprehensive overview of hybrid modelling and simulation, including definitions, theoretical foundations and taxonomies, framework developments, methodological extensions, and novel applicationsFeatures case studies and examples demonstrating the synergy realized by applying hybrid methodsDrives innovation in the theory and practice of modelling and simulation by calling for the discipline's growth by incorporating diverse scientific perspectivesEncourages the modelling and simulation community to explore and adopt interdisciplinary methods to engender improved insights from simulation studiesCalls for enhanced interdisciplinary collaboration, pushing modelling and simulation into new research and application areasThis comprehensive volume will appeal to researchers, academics, students, and practitioners who seek to advance their modelling and simulation work through integrative and advanced approaches. The book also serves as an excellent reference point for cross-disciplinary research, informing research communities of the potential of hybrid models that combine simulation with disciplinary research artefacts, methods, and approaches.