# Optimizing a Reverse Supply Chain Network for Electronic Waste under Risk and Uncertain Factors
## 2 Problem Description  
The quantity of e-waste was nearly 50 million tons in 2018 [57], which has led to serious impacts on the environment and public health. With the designing of an e-waste RSC model, e-waste is classified and treated in proper centers which can recover raw materials and dispose of hazardous materials properly. Figure 1 presents a generic RSC network for e-waste, including four stages:  
At the first stage, the end-of-life (EoL) products or discarded products from customers are gathered at collection centers (C). The customers can come from private households, company, retailers, etc., and they are able to drop-off their EoL products at collection centers. According to [PERSON] [58], there are five common collection models used such as drop-off events, permanent collection points, curbside collection programs, retail collection, and non-profit collection. For example, curbside collection is a popular method to collect e-waste since it is regular, convenient, and available in urban areas to handle bulky waste for residents. On the other hand, drop-off events (one day or some days) can be a common way to collect e-waste, especially from non-urban areas where residents may not have easy to access to collection points. At the collection centers, inspection and sorting are conducted. These products are then transferred to dismantling centers (D) to dismantle them into different components and materials. Items in good condition are directly sent to secondary markets (S), whereas unrecoverable components or toxic waste are delivered to a landfill site (L) for special treatment. Ferrous metals and plastics are sent to recycling centers (R) to be recycled, while non-working parts are transported to repairing centers (E). Lastly, recyclable substances and renewable parts are transferred to main markets (M) and secondary markets, respectively. Note that after processing at the main market, the materials can be returned to the forward supply chain.  
Currently, the flow from (C) to (L) is usually under the operations of companies. Due to the imposing of regulations in several areas, for example, Europe and Japan, companies also must be in charge of handling their end-of-life products. For convenience purposes, users will return their end-of-life products at some specific locations or to company agents. The agents will wait until the quantities reach a certain level, then send them to the collection centers (C).  
Figure 1: The generic e-waste reverse supply chain (RSC) network.  
From the company's perspective, the most challenging issue when designing the RSC is the problem of facility location. This would be one of the strategic variables. These facilities will serve to the end of the planning horizon. In this RSC model, the returned products, cost parameters, the capacity of centers, and a fraction of components reused or recycled are major sources of uncertainties. Strategic solutions must take account of these uncertainties. As a result, it is really challenging for decision-makers to determine a proper solution for this problem. In order to consider the effects of uncertainties in these parameters, fuzzy mixed integer programming approach is adopted in this proposed RSC framework to model and handle uncertainties in the e-waste RSC model. An interactive fuzzy approach is employed to create a balance between the objective value and the satisfaction of constraints of managers. This can support them to achieve the desired solution, while satisfying the company's constraints.