Combining an artificial intelligence algorithm and a novel vehicle for sustainable e-waste collection

Area of Science:

• Environmental Science
• Computer Science
• Mechanical Engineering

Background:

• Mobile collection of waste electrical and electronic equipment (WEEE) offers convenience for residents and businesses.
• Digital platforms can streamline WEEE pickup requests and collection planning, aiding circular economy initiatives.
• Efficient collection is crucial for recycling and recovering secondary raw materials from WEEE.

Purpose of the Study:

• To present a combined methodology for enhancing the efficiency of e-waste collection.
• To optimize the route planning for waste collection vehicles using artificial intelligence.
• To introduce an innovative vehicle body construction for improved waste loading and packing.

Main Methods:

• Development of an online e-waste collection supporting system.
• Implementation of the Harmony Search algorithm for vehicle route optimization.
• Design of a novel collection vehicle body with enhanced loading and packing capabilities.

Main Results:

• The Harmony Search algorithm-based system outperformed other AI algorithms in route optimization.
• The number of visited collection points increased by 1.2%-6.6% compared to existing methods.
• The new vehicle design increases packing efficiency and allows for greater e-waste volume per collection.

Conclusions:

• The integrated approach of optimized routing and improved vehicle design significantly boosts e-waste collection efficiency.
• The proposed system supports the circular economy by facilitating better recycling of electronic waste.
• The novel vehicle design is particularly suitable for urban environments with space and time constraints.