Exploring the relationship between simulation model accuracy and complexity
通过对三个仿真模型进行逐步简化并测量输出准确性，发现模型复杂性增加并不总是提高准确性，且回报可能递减、不变或递增，因此常见假设不成立，但可作为建模时的启发式指导。
Little is known about the relationship between the accuracy of a discrete-event simulation model and its complexity. Despite this, authors propose that increasing model complexity leads to improved accuracy with diminishing returns. In this paper we explore whether this proposition is correct by applying successive simplifications, some in different sequences, to three simulation models and measuring the impact on the accuracy of the model output. The results show that while increased complexity often leads to improved accuracy, this is not always the case. Also, we see that even when there is a positive correlation between complexity and accuracy, the returns to accuracy from greater complexity can be diminishing, constant or increasing. So, we conclude that the proposition about the relationship between accuracy and complexity is not correct. However, it does remain a useful heuristic for guiding modellers when considering the scope and level of detail at which to model a system.