Integrated collection-disassembly-distribution problem under fuzzy demand

This thesis focuses on the increasing problem of electronic waste due to technological developments, rapid urbanization and changing consumption habits. Emphasizing the importance of waste management for sustainable environment and economic gains, the study considers an integrated collection, disassembly and distribution problem model for end-of-life electronic products under fuzzy demand conditions. The main objective of the thesis is to optimize a reverse supply chain network including picking, disassembly and demand centers in an uncertain demand environment. This optimization aims to simultaneously minimize both the workstation costs in the disassembly line and the transportation costs in the logistics processes. A mixed integer mathematical model is developed to provide a solution to the problem. This model examines the Vehicle Routing Problem (VRP) approach for the picking and distribution phases and the principles of Dismantling Line Balancing (DLB) for the disassembly process. The effectiveness of the developed model is tested first on sample problems and then on randomly generated data to determine the limits of the model and to analyze the effects of parameters on the model. The developed model was tested by generating hypothetical data on sample problems and analyzed. Finally, the effectiveness of the parameters on the model is discussed through various analyses. This study aims to make a significant scientific contribution to the literature on uncertainty management in reverse supply chains and electronic waste management.