Cold Chain Logistics Management of Medicine with an Integrated Multi-Criteria Decision-Making Method.

Area of Science:

• Logistics and Supply Chain Management
• Pharmaceutical Sciences
• Decision Science

Background:

• Maintaining pharmaceutical integrity during transport is critical for patient safety and reducing cancer mortality.
• Drug cold chain logistics requires specialized handling to prevent temperature excursions and ensure medication efficacy.
• Selecting reliable cold chain logistics suppliers is a complex multi-criteria decision-making challenge.

Purpose of the Study:

• To propose an integrated multi-criteria decision-making (MCDM) model for selecting drug cold chain logistics suppliers.
• To enhance supplier selection by incorporating probabilistic linguistic terms for uncertainty.
• To improve the accuracy and reliability of cold chain logistics supplier evaluation.

Main Methods:

• Development of an integrated model combining SWARA (stepwise weight assessment ratio analysis) and CoCoSo (combined compromise solution) methods.
• Extension of SWARA and CoCoSo methods to a probabilistic linguistic environment to handle uncertain data.
• Introduction of an adjustment coefficient within the SWARA method for precise criteria weighting.

Main Results:

• The proposed integrated MCDM model effectively ranks drug cold chain logistics suppliers.
• The probabilistic linguistic approach enhances the model's applicability in real-world scenarios with uncertainty.
• A case study demonstrates the model's practical utility and advantages over traditional methods.

Conclusions:

• The integrated SWARA-CoCoSo model provides a robust framework for selecting drug cold chain logistics suppliers.
• This approach ensures the quality and safety of temperature-sensitive pharmaceuticals during transit.
• The methodology offers significant advantages for optimizing cold chain logistics decisions.