Illicit supply chain networks are not well mapped. Regulators do not know how goods flow from supplier to retailer. There is uncertainty about whom is involved, where goods originate from, and what quantities are being shipped. Simulation models are effective tools to find measures against the distribution of illicit goods such as personal protective equipment. However, simulation models often solely handle uncertainty through the variation of parameters. Structural uncertainty, which is uncertainty in the structure of the model, is often neglected. This study focuses on accounting efficaciously for structural
uncertainty in supply chain simulation models using model-driven exploratory modelling.
Model composability, which is a specific form of model driven exploratory modelling, is used in this study. The methodology is applied to a supply chain of illicit personal protective equipment. Using a model composer, many plausible models are generated of this supply chain. A model composer works by coupling model components in different configurations, while complying to preset constraints. Model components are submodels of a supply chain actors, for example, a retailer. Constraints help to restrict the way the model components can be coupled, making sure that every model generated by the model composer is plausible.
A ground truth is established to test the model composer on its efficacy to account for structural uncertainty. A ground truth is a simulation model of an illicit supply chain that functions as a benchmark. Five sets of 100 models are generated by the model composer to estimate the ground truth. Each set of models is generated with a different set of constraints. A constraint set consists of elements such as the maximum number of suppliers, the locations of supply chain actors, and the maximum number of customers of a supplier. These sets reflect different perspectives on an illicit supply chain.
Results show that structural uncertainty can result in significantly different simulation outcomes. The time in system, the production time, and the international transport time depend the most on changes in the constraints of the model composer. The time in system, the production time, and the international transport time of the models generated by the model composer are significantly different from the ground truth. The distributions of these outcomes have a different shape and have a wider range of possible values. Therefore, this study shows that model composability, a specific form of model-driven exploratory modelling, is efficacious in accounting for structural uncertainty in supply chain simulation models.
In the future, the methodology shown in this study can be used to model structural uncertainty in other fields such as water pipes networks, gas pipes networks, and telecom networks. Furthermore, the methodology can be used to identify robust measures to tackle the problem of illicit supply chains. Another recommendation is to use model composability for the individual components of the model. For example, a component such as a retailer can be build from several components: a cash register, a shelf, and a distribution area.