Simulation models verification and validation: Recent development and challenges: A review

摘要

Nowadays, verification and validation activities have become the prominent parameters to check the acceptability of a simulation model by the users for the intended purpose. This review paper aims to identify and analyze the recent development and challenges of simulation model verification and validation. To achieve this objective, a systematic review of the literature was carried out which mainly consisted of the methodological development of verification and validation process paralleled with simulation model development. Initially, a cumulative total of 980 records was found sourced from Google Scholar via an advanced search method, Science Direct, Web of science and from Scopus. Through a rigorous screening process about 72 sources or publications were included for analysis. The verification and validation techniques that have been developed so far were classified into five categories methodologically. From intensive analysis, it is found that researchers extensively scrutinize the traditional methods and graphical/ statistical tools, escalating interest in data-driven and automation techniques, and limited focus on agent-based and hybrid models. Though agent-based and hybrid models are increasingly vital in the realm of complex system simulations, their verification and validation processes remain relatively under-explored. Though reasonable efforts have been exerted on the verification and validation methods development, still academicians and researchers agreed on the lack of verification and validation methodology for the recently developed simulation model paradigms such as agent-based and hybrid models, autonomous robotics models, high fidelity and data-driven models, and real-time prediction models such as digital twins. As a challenge of verification and validation processes, lack of universal methodologies, lack of reliable real-world data for validation, inaccuracy of real-world data for the intended purpose, different world views by different individuals, and the rapid growth and complexity of simulation modeling are identified as the hindering factors of verification and validation process.