Supply Chain Shock Propagation Simulation Framework with Semigroup Modeling

A 5.5 KB Excel file containing a simulation framework for modeling supply-chain state evolution under cascading disruptions and resilience interventions. The framework, developed by Job Agba Opue and last updated in May 2026, uses finite transformation semigroups to encode collapse conditions, equilibria, and redundancy. It is illustrated with examples from manufacturing, agricultural, and e-commerce logistics systems.

Use Cases

• Modeling cascading disruptions in supply networks based on the described semigroup framework.
• Identifying minimal collapse-inducing sets and redundancy in logistics systems using the basis-pruning algorithms.
• Assessing shock containment strategies via measurable resilience indicators derived from semigroup properties.
• Simulating the impact of resilience interventions on supply-chain state evolution.

Strengths

• Framework provides explicit semigroup-theoretic criteria for collapse and stabilization.
• Includes algorithmic procedures for redundancy identification.
• Illustrated with case studies across multiple industry sectors (manufacturing, agriculture, e-commerce).
• Dataset is small (5.5 KB) and likely quick to inspect.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The 5.5 KB size suggests a very limited scope, likely containing model parameters or results rather than extensive simulation data.

Provenance

Source

figshare

Collection Method

Likely contains the analytical framework, algorithms, and case study results described in the associated paper.

Freshness

Last updated 2026-05-28 17:40:00; freshness should be verified.