Pharmaceutical Supply Chain Routing Model Parameters

A novel mixed integer linear programming model enhances pharmaceutical supply chains by routing vehicles to patients and automated medicine lockers. The model, solved using an improved non-dominated sorting genetic algorithm-II, was verified through real-world applications and achieved cost reductions of 14.74% and 13.511% in two scenarios. It was authored by Zahra Samadi Bahrami and last updated on 2026-05-29.

Use Cases

• Optimizing vehicle routing for pharmaceutical delivery based on the proposed mixed integer linear programming model.
• Evaluating trade-offs between cost, greenhouse gas emissions, and patient satisfaction in healthcare logistics.
• Simulating the impact of automated medicine lockers on supply chain costs and service performance.
• Applying triage concepts to prioritize urgent patient deliveries over locker assignments.

Strengths

• Model verified through real-world applications, suggesting practical validation.
• Achieved specific cost reductions: 14.74% for one scenario and 13.511% for another.
• Includes a three-objective function covering costs, emissions, and patient satisfaction.

Limitations

• Dataset is very small at 5.5 KB, indicating limited scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Likely contains parameters and results from an optimization model for pharmaceutical logistics.

Freshness

Last updated 2026-05-29 17:48:44; freshness should be verified.