Dual-objective optimization of prefabricated component logistics based on JIT strategy.

Area of Science:

• Logistics and Supply Chain Management
• Sustainable Construction Practices
• Operations Research

Background:

• Prefabricated construction offers efficiency but faces logistical challenges like high carbon emissions and site congestion.
• Current logistics models struggle with the unique demands of large, heavy prefabricated components.
• Uncertainties in delivery and assembly impact project timelines and costs.

Purpose of the Study:

• To develop a dual-objective optimization model for prefabricated component logistics.
• To integrate the Just-In-Time (JIT) strategy for enhanced supply chain management.
• To minimize carbon emissions and maximize customer satisfaction in prefabricated construction logistics.

Main Methods:

• A dual-objective optimization model was formulated for on-site and off-site logistics.
• An improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) was employed for solving the model.
• Case studies and sensitivity analyses were conducted for validation and performance assessment.

Main Results:

• The proposed JIT logistics model effectively reduces carbon emissions and enhances customer satisfaction.
• The model provides robust vehicle scheduling solutions, outperforming traditional logistics approaches.
• Enhanced solution diversity and local search capabilities were achieved using the improved NSGA-II.

Conclusions:

• The JIT logistics model offers scientifically-based decision support for prefabricated construction.
• The model demonstrates significant resilience to logistical uncertainties.
• Optimized vehicle scheduling is crucial for sustainable and efficient prefabricated construction projects.