A method for optimizing waste collection using mathematical programming: a Buenos Aires case study.

Area of Science:

• Operations Research
• Transportation Logistics
• Environmental Engineering

Background:

• Waste collection route optimization is a complex logistical challenge.
• Existing routes may not be efficient, leading to increased costs and environmental impact.
• Minimizing vehicle wear and tear is crucial for operational sustainability.

Purpose of the Study:

• To develop and apply an operations research method for optimizing waste collection routes.
• To incorporate vehicle wear and tear, measured by mechanical work, into the optimization criteria.
• To demonstrate the method's effectiveness through a case study in Buenos Aires.

Main Methods:

• Reducing the waste collection problem to the Traveling Salesman Problem (TSP).
• Solving the TSP using the Concorde solver program.
• Employing graph theory and mathematical programming, including data correction.

Main Results:

• Achieved route distance reductions of 10-40% in the studied areas.
• Demonstrated substantial decreases in mechanical work and vehicle wear and tear.
• Projected annual savings exceeding US $200,000 for Buenos Aires civic authorities.

Conclusions:

• The proposed method effectively optimizes waste collection routes, minimizing distance and vehicle wear.
• Significant financial savings and qualitative benefits (reduced pollution, traffic, driver fatigue) are achievable.
• The approach offers a scalable solution for municipal waste management systems.