Planning the e-scrap reverse production system under uncertainty in the state of Georgia: A case study

Abstract

Due to legislative requirements, environmental concerns, and market image, the disposition of end-of-life e-scrap is attracting tremendous attention in many parts of the world today. Effective management of returned used product flows can have a great impact on the profitability and resulting financial viability of associated e-scrap reverse production systems. However, designing efficient e-scrap reverse production systems is complicated by the high degree of uncertainty surrounding several key factors. Very few examples of this complex design problem are documented in the academic literature. This paper contributes as analysis of a new, large-scale application that designs an infrastructure to process used televisions, monitors, and computer central pro- cessing units (CPUs) in the state of Georgia in the U.S. The case study employs a scenario-based robust optimization model for supporting strategic e-scrap reverse production infrastructure design decisions under uncertainty. A mixed integer linear programming (MILP) model is used to maximize the system net profit for specified deterministic parameter values in each scenario, and then a min-max robust optimization methodology finds a robust solution for all of the scenarios.