Data & Code for "Navigating trade-offs in structural design for resilient industrial symbiosis networks"

Overview: This archive contains the complete computational capsule. It integrates the raw datasets, Jupyter Notebooks, and the computational environment required to reproduce the study's findings. Archive Structure & Contents: The archive follows the standard directory structure: 1. /code (Analysis Workflows) Contains the Jupyter Notebooks used for network simulation and analysis, organized into four sub-directories corresponding to the resilience phases: 1. Preparedness/: Scripts for initial network topology analysis. 2. Absorption/: Scripts simulating the network's response to shock events. 3. Recovery/: Scripts modeling the recovery possibility. 4. Adaptation/: Scripts for structural optimization. 2. /data (Input Datasets) Contains the structural data used in the analysis, organized as follows: 35 cases (Initial data before adaptation and optimized data after adaptation)/: Contains the adjacency matrices/edge lists for the 35 empirical ISNs (both baseline and optimized). Datasets for RRM/: Data prepared for the Ridge Regression Model (RRM) analysis. Network structure data for VIF/: Data used for Variance Inflation Factor (VIF) analysis. 3. /environment (Reproducibility Specs) Defines the computational environment to ensure consistent execution. Platform: Python and R (Jupyterlab/RStudio). Base Environment: Python 3.12.8, R 4.4.2, JupyterLab 4.3.5. Key Python Packages: networkx 3.5 scikit-learn 1.7.2 numpy 2.3.5 pandas 2.3.3 matplotlib 3.10.7 scipy 1.16.3 openpyxl 3.1.5 4. /metadata Contains the metadata.yml file providing project authorship. Authors: Yufan Chen, Zizhen Xu, Shauhrat S. Chopra