Logistics Path Decision Optimization Method of Fresh Product Export Cold Chain Considering Transportation Risk

Area of Science:

• Logistics and Supply Chain Management
• Operations Research
• Risk Management

Background:

• Fresh product export cold chain logistics involves large volumes and complexity, leading to significant transportation risks.
• Existing cold chain logistics route planning methods are often inadequate, impacting decision-making effectiveness and delivery times.

Purpose of the Study:

• To enhance cold chain logistics route planning capabilities for fresh product exports.
• To minimize transportation risks and shorten delivery times through an optimized decision-making process.

Main Methods:

• Risk quantification and classification of cold chain logistics.
• K-nearest neighbor algorithm for traffic congestion risk prediction.
• Analytic Hierarchy Process (AHP) for risk factor weighting.
• Genetic algorithm for optimal cold chain logistics route decision function construction.

Main Results:

• The proposed method significantly improves cold chain logistics route decision-making effectiveness.
• Achieved a route decision-making accuracy of 90%.
• Reduced transportation time to 31.45 minutes, selecting the shortest and smoothest paths.

Conclusions:

• The developed optimization method offers a feasible and applicable solution for fresh product export cold chain logistics.
• Integrating risk assessment and advanced algorithms enhances route planning efficiency and reliability.
• The study demonstrates the potential for substantial improvements in logistics operations through intelligent route optimization.