This repository is part of the Ph.D. thesis of Isabelle M. van Schilt, Delft University of Technology.
This repository is used to calibrate the underlying structure and parameters of a stylized supply chain simulation model of counterfeit Personal Protective Equipment (PPE) using the quality diversity algorithm. For this, we use the pyribs library for the quality diversity algorithm, and pydsol-core and pydsol-model for the discrete event simulation model. The calibration is done with sparse data, which is generated by degrading the ground truth data on noise, bias, and missing values. We define the structure of a supply chain simulation model as a key value of a dictionary (sorted on graph density), which is a set of possible supply chain models. The integer is, thus, a decision variable of the calibration, next to other parameters in the simulation model.
To use this repository, we need a simulation model developed in pydsol-core and pydsol-model . Additionally, we need a dictionary with various different simulation structures as input, as well as the ground truth data. For this project, we use the repository complex_stylized_supply_chain_model_generator as simulation model.
" authors: - family-names: van Schilt given-names: Isabelle orcid: "https://orcid.org/0000-0003-3862-1278" title: "Code: Quality Diversity Algorithms for Calibrating a Supply Chain Simulation Model with Sparse Data" keywords: version: 1 identifiers: - type: doi value: 10.4121/766f4e89-fa03-47c6-a9f2-fa41f241984b.v1 license: CC BY-NC-ND 4.0 date-released: 2024-07-22