An algorithm for the optimal collection of wet waste

Area of Science:

• Operations Research
• Environmental Management
• Logistics and Supply Chain Management

Background:

• Metropolitan waste collection planning faces challenges due to varying parameters at different collection points.
• Wet waste collection presents unique combinatorial complexities, demanding significant computational resources for optimal solutions.
• Existing methods often struggle with the scale and specific characteristics of metropolitan wet waste logistics.

Purpose of the Study:

• To develop an efficient heuristic procedure for planning wet waste collection at a metropolitan scale.
• To address the combinatorial challenges inherent in optimizing waste collection routes and schedules.
• To evaluate the performance of the developed approach against established methods and software.

Main Methods:

• Development of a novel heuristic procedure tailored for wet waste collection planning.
• Application of the heuristic to problem instances derived from a real-world case study (Genoa's historical center).
• Comparative analysis of the heuristic's performance against a general-purpose mathematical programming software and common decision rules.

Main Results:

• The developed heuristic procedure demonstrated effective performance in planning wet waste collection.
• The approach successfully managed problem instances with significant dimensionality and parameter variability.
• Performance evaluation indicated advantages over standard mathematical programming software and practical decision rules.

Conclusions:

• The proposed heuristic offers a computationally efficient and effective solution for metropolitan wet waste collection planning.
• This approach provides a valuable tool for optimizing waste management logistics in complex urban environments.
• The study validates the heuristic's applicability and superiority in a real-world case study context.