Design and optimization of sustainable closed-loop supply chain networks under uncertainty

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Most materials from end-of-life (EOL) and end-of-use (EOU) products can be recycled and used to produce new products. A great number of benefits are associated with recycling plans such as reducing the consumption of raw materials, saving energy, and diverting waste from landfills. In this regard, closed-loop supply chain networks (CLSCNs) are designed for creating value over the entire life cycle of products. A CLSCN is an integration of a forward supply chain (i.e., suppliers, producers, retailers, and customer zones) and a reverse logistics network (i.e., collection depots, recovery centers, remanufacturing plants, and disposal centers). Forward supply chains consist of several activities to convert raw materials to finished products, while reverse logistics networks include some activities (e.g., refurbishing and remanufacturing) to recover the EOL and EOU products. Nowadays, CLSCN design is experiencing growing attention due to customer awareness and government policies regarding recovery options to protect the environment. According to the recycling regulations in British Columbia, producers are responsible for the life cycle management (i.e., collection and recycling) of their products. To this aim, producers need to collaborate with other parties involved in reverse logistics networks to manage a sequence of operations (e.g., collection, transportation, refurbishing, and remanufacturing). Although social development and environmental protection should be considered for planning sustainable CLSCNs, most existing studies have focused on economic aspects of recycling plans. Similarly, a very small amount of research has focused on resiliency in CLSCNs. However, there are many uncertain parameters (e.g., quantity and quality of returned products) that affect the performance of the entire network (e.g., higher overtime and transportation costs). My long-term research objective is to advance state-of-the-art methods to support industries and communities to establish efficient recycling mechanism in which several facilities cooperate effectively over the entire life cycle of products. Therefore, over the next five years, optimal CLSCNs will be designed for products containing non-biodegradable substances (e.g., e-waste and plastics) in Canada by focusing on three short-term objectives:(1) To develop data-driven decision-making processes using big data analytics in the configuration of CLSCNs, (2) To design sustainable CLSCNs using multi-objective models (i.e., social development, environmental protection, and economic benefits), (3) To propose novel optimization models to configure CLSCNs that are resilient against the impact of operational and disruption risks. In this research program, CLSCNs will be configured to improve the performance of existing recycling plans related to e-waste and plastics. This research will have significant outcomes, such as saving costs, conserving natural resources, and protecting the environment in Canada.