Neo4j Cypher scripts for knowledge graph construction - reconfigurable supply chain 5.0
Description
This dataset contains the Cypher scripts used to construct and query the Neo4j knowledge graph (KG) supporting the dynamic reconfigurable supply chain 5.0 model presented in the associated article. The KG models suppliers, production sites, distribution centers, retailers, transporters, raw materials, and machines, along with their relationships and attributes (costs, emissions, capacities). Files included: - Case study Reconfiguration.txt: Cypher scripts for the reference case study (3 suppliers, 3 production sites, 3 distribution centers, 7 retailers). - 3EME INSTANCE.txt: Cypher scripts for a larger-scale test instance used to evaluate model scalability. These scripts were used in conjunction with a Mixed-Integer Linear Programming (MILP) model implemented in Python (PuLP) for dynamic supply chain reconfiguration, as described in the paper "A Novel Mixed-Integer Linear Programming Model for Dynamic Reconfiguration Optimization in Reconfigurable Supply Chains 5.0