Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO...

Area of Science:

• Operations Research
• Environmental Science
• Computer Science

Background:

• Waste collection route optimization is crucial for reducing operational costs and environmental impact.
• Existing methods often struggle with efficiency and cost-effectiveness in complex urban environments.
• Significant expenditure is associated with capital, labor, and variable operational costs in waste management.

Purpose of the Study:

• To propose a modified particle swarm optimization (PSO) algorithm integrated into a capacitated vehicle-routing problem (CVRP) model.
• To determine optimal waste collection routes and solutions.
• To reduce socioeconomic and environmental impacts associated with waste collection.

Main Methods:

• A modified particle swarm optimization (PSO) algorithm was developed and applied to a capacitated vehicle-routing problem (CVRP) model.
• Threshold waste level (TWL) and scheduling concepts were incorporated into the PSO-based CVRP model.
• The algorithm was tested using diverse datasets to evaluate its performance.

Main Results:

• The proposed CVRP model achieved optimal waste collection and route optimization at 70-75% of the threshold waste level (TWL).
• For one-week scheduling, 70% TWL outperformed considering all nodes, showing improvements in collected waste, distance, efficiency, fuel consumption, and cost.
• Key performance indicators like travel distance, total waste collected, efficiency, and route tightness were significantly improved.

Conclusions:

• The modified PSO-based CVRP model offers a valuable tool for efficient waste collection and route optimization.
• Achieving optimal results at 70-75% TWL demonstrates a practical and effective strategy for waste management.
• The optimized model contributes to reducing the socioeconomic and environmental footprint of waste collection services.