A multimodal logistics service network design with time windows and environmental concerns

Area of Science:

• Operations Research
• Supply Chain Management
• Environmental Logistics

Background:

• Designing multimodal logistics networks presents challenges due to customer service time windows and environmental costs.
• Minimizing total logistics costs while addressing environmental concerns is crucial for sustainable operations.

Purpose of the Study:

• To develop a model for optimizing multimodal logistics service network design.
• To incorporate customer service time windows and environmental costs, specifically CO2 emissions, into the network design.
• To determine optimal transportation mode combinations and transfer node investments.

Main Methods:

• A mathematical model was formulated to minimize total logistics costs, considering transport cost, time, carbon emissions, and service time windows.
• Genetic and heuristic algorithms were developed and applied to solve the optimization model.
• A numerical example was used for validation and comparison of the algorithms' performance.

Main Results:

• The proposed model successfully determined optimal transportation modes and transfer node investments.
• The study validated the effectiveness of both genetic and heuristic algorithms in solving the complex logistics design problem.
• Analysis revealed the significant impact of logistics service time windows and CO2 emission taxes on the optimal network design.

Conclusions:

• The developed model provides a robust framework for designing cost-effective and environmentally conscious multimodal logistics networks.
• The findings offer valuable management insights into balancing operational efficiency with environmental sustainability.
• The study highlights the importance of considering time windows and carbon pricing in logistics network optimization.