Comparison of Reverse Logistics Networks in Centralized and Decentralized Areas = Genetic Algorithm Approach

다국어 초록 (Multilingual Abstract)

In this paper, we propose two types of reverse logistics (RL) networks: reverse logistics network in centralized area (RLC) and reverse logistics network in decentralized area (RLD). For the RLC, the used products taken from all customers are sent to one of the centralized integration centers, which performs the functions of collection center, recovery center, and redistribution center simultaneously, after treating them in it, they are all sent to one of the centralized secondary markets. For the RLD, the used products taken from all customers are sent to the regionally decentralized integration centers, and after treating them in each integration center, they are sent to regionally decentralized secondary markets. The mathematical models for effectively representing the RLC and RLD are proposed and they are solved in a genetic algorithm approach. In numerical experiment, two types of RL networks are presented for comparing the performances of the RLC and RLD using various measures of performance. Finally, we can conclude that the RLC significantly outperforms the RLD.

목차 (Table of Contents)

• 1. Introduction
• 2. Structure of RLC and RLD
• 3. Mathematical Formulation
• 4. GA Approaches
• 5. Numerical Experiment
• 6. Conclusion
• REFERENCES