A decision support system for the operational planning of solid waste collection

Area of Science:

• Operations Research
• Environmental Engineering
• Computer Science

Background:

• Operational planning for solid waste collection faces challenges in optimizing vehicle routes and sorting unit allocation.
• Inefficient planning leads to wasted labor and increased landfill burden.
• Effective decision support systems are crucial for sustainable waste management.

Purpose of the Study:

• To develop and implement a decision support system (SCOLDSS) for optimizing solid waste collection operations.
• To generate optimal alternatives for vehicle allocation, routing, and waste sorting.
• To reduce labor waste and minimize the amount of solid waste sent to landfills.

Main Methods:

• Utilized a combination of quantitative techniques, including discrete event simulation and algorithms/heuristics.
• Developed the SCOLDSS using Borland Delphi and integrated commercial software Arena for simulations.
• Applied the system to real-life solid waste collection data from Porto Alegre, Brazil.

Main Results:

• The SCOLDSS successfully generated optimized alternatives for vehicle routing and sorting unit allocation.
• Computational studies demonstrated superior performance compared to existing operational planning methods.
• The system effectively addressed the dual goals of labor efficiency and landfill waste reduction.

Conclusions:

• The developed SCOLDSS is a viable and effective tool for enhancing solid waste collection operational planning.
• The integration of simulation and optimization techniques provides significant advantages over traditional methods.
• The system offers a scalable solution for improving waste management efficiency and environmental sustainability.