A Vehicle Routing Optimization Problem for Cold Chain Logistics Considering Customer Satisfaction and Carbon...

Area of Science:

• Operations Research
• Supply Chain Management
• Environmental Economics

Background:

• Cold chain logistics face intense competition and pressure for low-carbon operations.
• Balancing cost, customer satisfaction, and carbon emissions is crucial for sustainable development.
• Punctual delivery and carbon trading mechanisms are key considerations.

Purpose of the Study:

• To develop a comprehensive cold chain vehicle routing problem optimization model.
• To minimize the cost per unit of satisfied customer, integrating cost, satisfaction, and emissions.
• To analyze the impact of carbon price on operational outcomes.

Main Methods:

• A cost-benefit approach was used to formulate the optimization model.
• Punctuality defined customer satisfaction; carbon trading determined emissions costs.
• A cycle evolutionary genetic algorithm was employed for computational experiments.

Main Results:

• The model demonstrated that a slight increase in total cost can significantly enhance customer satisfaction, yielding cost-effective solutions.
• Increasing carbon prices can reduce emissions but may decrease customer satisfaction, highlighting a trade-off.
• Total costs exhibit varied trends with rising carbon prices, depending on carbon quota availability.

Conclusions:

• The proposed model effectively optimizes cold chain logistics by integrating cost, customer satisfaction, and carbon emissions.
• Findings provide insights into the complex relationship between carbon price, emissions, and customer satisfaction.
• The study offers practical implications for businesses and policymakers in cold chain management.