An Intelligent Solution for E-Waste Collection

Abstract

The E-waste (Management) Amendment Rules 2018 of India had set out targets for authorized stakeholders to collect 10% of waste electrical and electronic equipment (WEEE) that was generated in the market in the year 2018. The rules also stipulated a proportional annual increment of 10% in collection until 2023. It is imperative that this is achieved through the active participation of various stakeholders such as producers, aggregators, recyclers, logistics providers and customers in a formal way. However the capacity of installed formal recycling units in the country lags a long way behind the projected volume of WEEE generated. This is because formal collectors and recyclers in India face several challenges, including business sustainability owing to uncertainty about steady supply, limited business opportunities, absence of robust collection mechanisms, high operational costs, customer attitudes and indifference. In contrast, the informal sector, taking advantage of slack enforcement of labour and environmental regulations, thrives and poses serious challenges to the formal sector. We propose a responsive system to optimize distances for WEEE collection vehicles using state-of-the-art genetic algorithms and ant colony optimization techniques. This will reduce the cost of collection by the formal sector, reducing fuel consumption and service time and providing a sustainable solution, reducing greenhouse gas emissions. An Indian case scenario based on a service provider located in the city of Jaipur is developed. Certain assumptions are made, such as bulk consumers, urban households and online platform. The model can be scaled up for the benefit of WEEE collection service providers in India with a known arrangement of streets and buildings in a defined catchment area of a city.