The ever-growing stream of waste production has become a critical issue for many metropolitan areas. An effective strategy to address this problem has been the concept of reverse logistics (RL). This paper seeks to develop an appropriate product recovery approach for electronic waste generated in an urban area. Consequently, we have proposed an integrated fuzzy RL model with buyback (BB) offers based on the condition of used-products (UPs) at the time of return. However, this strategy contains a significant challenge, which derives from unpredictability surrounding the return rate of UPs due to its dependency on multiple external factors. Hence, a novel fuzzy probability function is developed to approximate UPs’ chance of return. Besides that, the mathematical RL network’s inherent uncertainty prompted us to employ the fuzzy credibility-based method in the model. Afterward, the model’s objectives are locating and allocating collection centres to customer zones, determining flow between facilities and finding the optimal amount of gathered UPs and BB offers. Finally, we applied the model to a case study concerning product recovery in Mashhad city, Iran, and the results have proven its validity and utility.
Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data