Abstract:
Verification and validation (V&V) are integral parts of any simulation study. Validation assesses how accurately conceptual models represent the real system, while verification ensures correct implementation in software. V&V plays a critical role in business and manufacturing, where simulation models imitate complex real-world systems. However, comprehensive statistically grounded literature reviews on V&V of simulation models, particularly from a business management and manufacturing domain standpoint, are scarce. This study addresses that gap by performing topic modeling to identify prominent research themes, then reviewing all important research articles to outline the evolution of quantitative methodologies and algorithms on V&V. We also highlight various research gaps and potential directions for future work. For this study, we reviewed the abstracts of more than 6,000 articles indexed in Scopus and Web of Science, along with a comprehensive analysis of 300 research articles.
