Optimal Design of Reverse Supply Chain Network for Waste Mobile Phones under Uncertainty

• Published in: 2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA) pp. 898 - 908
• Main Authors: Song, Zuoling, Sun, Hui, Liu, Xinmin, Wang, Manfei
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-06-2020
• Subjects: Adaptation models; fuzzy chance constrained; Mobile handsets; network configuration; particle swarm algorithm; Recycling; reverse supply chain network; Supply chains; Transportation; Uncertainty; Waste disposal; waste mobile phone
• DOI: 10.1109/ICAICA50127.2020.9181931

The enormous growth and updating speed in mobile phone consumption have brought tremendous pressure on resources and the environment, so enterprises in supply chain of mobile phones are driven by internal and external forces to develop circular economy (CE). This study aims to optimize reverse supply chain network (RSCN) configuration and effectiveness, which consists of multiple recycling sites, recycling centers, pretreatment centers, detection and reprocessing centers and waste disposal centers, considering uncertainty of the recovery quantity and quality in recycling processes. To achieve this goal, the study establishes an optimization model of RSCN for waste mobile phones to maximize the expected profit. First, through the equivalent transformation of fuzzy chance constrained programming, the study transforms fuzzy variables into clear equivalent forms. Then, the study proposed an optimal particle swarm optimization (PSO) algorithm with adaptive dynamic changing inertia weights as a model solving tool. Finally the study gets the optimal layout of facility nodes and transportation path for a province of China, by programming of MATLAB. Though comparison and robust analysis, the model is verified to be valid and feasibility. The study contributes to provide cycling firms or policy-makers with theoretical and practical directions to configure RSCN of waste phones under uncertainty.