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

Area of Science:

• Operations Research
• Environmental Engineering
• Computer Science

Background:

• Inefficient solid waste collection leads to increased costs and environmental impact.
• Current operational planning methods often lack optimization for vehicle routing and sorting allocation.
• Effective management of solid waste is crucial for sustainable urban development.

Purpose of the Study:

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

Main Methods:

• Utilized quantitative techniques including discrete event simulation and algorithms/heuristics.
• Developed the SCOLDSS using Borland Delphi and the Arena software 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 allocation and routing.
• The system determined efficient daily solid waste amounts for sorting units.
• Computational studies demonstrated superior performance compared to existing operational planning methods.

Conclusions:

• The developed decision support system (SCOLDSS) offers a significant improvement in solid waste collection operational planning.
• Implementing SCOLDSS can lead to substantial cost savings and environmental benefits.
• The system provides a viable and effective tool for municipal waste management.