Pharmaceutical Supply Chain Routing Solutions with Cost and Emissions Analysis

A research dataset by Zahra Samadi Bahrami, last updated in May 2026, presents a model for pharmaceutical logistics. It contains results from a mixed integer linear programming model applied to a green open vehicle routing problem. The model evaluates total costs, greenhouse gas emissions under varying traffic speeds, and patient satisfaction for delivering medicine via home services or automated lockers.

Use Cases

• Optimizing vehicle routing for pharmaceutical delivery based on cost and emissions objectives.
• Evaluating the trade-offs between home delivery and automated locker allocation for patient satisfaction.
• Benchmarking genetic algorithm performance for multi-objective supply chain problems.
• Analyzing the impact of traffic congestion risk on greenhouse gas emissions in logistics.

Strengths

• Model results include specific cost reduction percentages: 14.74% for one scenario and 13.511% for another.
• The model incorporates three concrete objectives: routing costs, greenhouse gas emissions, and patient satisfaction.
• The dataset is verified through real-world applications as stated in the description.

Limitations

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

Provenance

Source

figshare

Collection Method

Results from an improved non-dominated sorting genetic algorithm-II and the LP-metric method applied to a proposed mixed integer linear programming model.

Freshness

Last updated 2026-05-29 17:48:49; freshness should be verified.