The capacitated arc routing problem for on-road anti-dust operations

Area of Science:

• Operations Research
• Environmental Engineering
• Transportation Science

Background:

• Anti-dust operations in traffic networks face challenges due to varying service effectiveness.
• Time-of-service and service types significantly impact dust suppression efficiency.

Purpose of the Study:

• Introduce a new variant of the Capacitated Arc Routing Problem (CARP) named CARP with heterogeneous services and time-dependent profits (CARP-HSTP).
• Develop and evaluate a novel approach for optimizing anti-dust operations.

Main Methods:

• Formulated a nonlinear 0-1 programming model.
• Developed a two-stage metaheuristic combining Variable Neighborhood Search (VNS) and Hybrid Genetic Algorithm (HGA).
• Conducted atmospheric lab experiments and validated with field data from Chengdu, China.

Main Results:

• The proposed CARP-HSTP model and metaheuristic effectively address dust suppression challenges.
• The VNS-enhanced approach demonstrated a significant improvement of 197.8% over current practices.
• Lab experiments confirmed the differential dust suppression effects of various services.

Conclusions:

• The developed CARP-HSTP approach offers practical advantages for anti-dust operations in traffic networks.
• The methodology provides a valuable framework for other CARP variants with time-dependent factors.
• This research contributes to more efficient and effective environmental management in transportation systems.