Cost Optimization for Electronic Waste Recovery in a Reverse Logistics Network

Abstract

INTRODUCTION: The rapid advancement of science and technology has fueled the widespread adoption of electronic devices, ranging from semiconductors to complex electronic circuits. These devices, typically classified into large household appliances, IT and telecommunications equipment, and consumer electronics, have significantly enhanced both the quality of life and operational efficiency in businesses. However, the increasing volume of these electronics has introduced a major challenge: the effective management of electronic waste (e - waste). Without a well - designed system, the accumulation of e - waste can lead to severe environmental and public health consequences.

OBJECTIVES: This study aims to address the pressing issue of e-waste by analyzing the costs associated with its processing and proposing an optimized reverse logistics network. Specifically, the primary goal is to design a system that not only reduces operational costs but also minimizes the environmental footprint associated with e - waste management. By leveraging advanced modeling techniques, the research seeks to provide a practical framework that can be adopted in both industrial and municipal settings.

METHODS: To achieve these objectives, a Mixed - Integer Linear Programming (MILP) model was developed to represent the cost optimization problem associated with e - waste collection and recycling. The model incorporates various stages of the reverse logistics process, including collection, sorting, transportation, and final processing. Its solution was derived using CPLEX optimization software, which allowed for the identification of the most cost - effective network configuration. Sensitivity analyses were conducted to ensure the robustness of the proposed framework, enabling stakeholders to make informed decisions based on different scenarios and constraints.

RESULTS: The MILP model produced an optimized solution that minimizes recovery costs while maximizing the retrieval of reusable components and materials. In addition, the study found that incorporating sustainability factors into the model significantly improved the overall efficiency of the reverse logistics network. The optimized configuration demonstrates the potential of a well - structured reverse logistics system to reduce processing expenses, improve resource efficiency, and encourage the reuse of valuable materials, ultimately contributing to a more circular economy.

CONCLUSION: Improper disposal of electronic waste presents significant environmental and health risks, particularly during the mechanical and chemical treatment of circuit boards. By introducing an optimized reverse logistics model, this study offers a practical solution that reduces processing costs, promotes resource conservation, and supports long - term environmental sustainability. Moreover, the findings underscore the importance of integrating advanced optimization techniques into the design of e - waste management systems, paving the way for more sustainable and cost - effective practices.