ASEE NCS Conference 2019

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Modeling and Optimization of Electronic Waste Collection System

Accelerated and advanced development of the electronics industry in the 21st century is creating the rapid obsolescence of electrical and electronic equipment, which causes one of the largest and unstoppable waste streams called electronic waste (e-waste). There have been lots of obstacles in e-waste recycling, including the lack of government regulation, the existence of the informal sector and the insufficiency of consumer awareness. The ideal e-waste recycling system would be able to overcome these obstacles. To establish an effective e-waste recycling system, the first important step is to implement a powerful e-waste collection system. Many research studies have only focused on solving one aspect of the e-waste collection problem, such as estimating/predicting of the e-waste amount generated, identifying the e-waste drop-off points allocation, determining the e-waste processing facilities’ locations, or calculating the shortest route for the collection vehicles. This paper is to propose the multi-stage model, which can solve the household e-waste collection problem completely at three stages. These three stages consist of the prediction of the amount of electronic waste that would be recycled, the drop-off points/containers allocation, the e-waste processing facilities’ locations, and the collection vehicles routing. For this purpose, the existing studies on the e-waste collection system was reviewed. Additionally, the methods that was used in these studies were improved. Specifically, the existing formulations for estimating the amount of e-waste that would be recycled, allocating e-waste processing facilities and drop-off points/containers, and determining the collection vehicles’ shortest routes were modified and improved to fit correctly into the proposed e-waste collection model. Moreover, these formulations and methods were combined to create the complete framework for the household e-waste collection system.

Quang Nguyen
Grand Valley State University
United States

Huihui Qi
Grand Valley State University
United States


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