Verification of Computer Simulation Models

TLDR

The validation of computer simulation models for industrial systems has received limited attention in management science literature. This paper examines how contemporary philosophy of science, economic theory, and statistics inform the verification of computer models, addressing questions about meaning, differences from other models, and implications. The authors synthesize insights from philosophers, economists, statisticians, and simulation practitioners, focusing on economists’ views of model testing and evaluating goodness‑of‑fit measures for time‑series outputs against historical data.

Abstract

The problem of validating computer simulation models of industrial systems has received only limited attention in the management science literature. The purpose of this paper is to consider the problem of validating computer models in the light of contemporary thought in the fields of philosophy of science, economic theory, and statistics. In order to achieve this goal we have attempted to gather together and present some of the ideas of scientific philosophers, economists, statisticians, and practitioners in the field of simulation which are relevant to the problem of verifying simulation models. We have paid particular attention to the writings of economists who have been concerned with testing the validity of economic models. Among the questions which we shall consider are included: What does it mean to verify a computer model of an industrial system? Are there any differences between the verification of computer models and the verification of other types of models? If so, what are some of these differences? Also considered are a number of measures and techniques for testing the “goodness of fit” of time series generated by computer models to observed historical series.