Forward and reverse logistics network and route planning under the environment of low-carbon emissions: A case study of Shanghai fresh food E-commerce enterprises

2017 ◽  
Vol 106 ◽  
pp. 351-360 ◽  
Author(s):  
Jianquan Guo ◽  
Xinyue Wang ◽  
Siyuan Fan ◽  
Mitsuo Gen

2021 ◽  
pp. 0734242X2110452
Author(s):  
Masoud Amirdadi ◽  
Farzad Dehghanian ◽  
Jamal Nahofti Kohneh

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.





2019 ◽  
Vol 32 (7) ◽  
pp. 2005-2025 ◽  
Author(s):  
Yangjun Ren ◽  
Chuanxu Wang ◽  
Botang Li ◽  
Chao Yu ◽  
Suyong Zhang


2021 ◽  
Vol 11 (14) ◽  
pp. 6466
Author(s):  
Lijun Chang ◽  
Honghao Zhang ◽  
Guoquan Xie ◽  
Zhenzhong Yu ◽  
Menghao Zhang ◽  
...  

The low-carbon economy, as a major trend of global economic development, has been a widespread concern, which is a rare opportunity to realize the transformation of the economic way in China. The realization of a low-carbon economy requires improved resource utilization efficiency and reduced carbon emissions. The reasonable location of logistics nodes is of great significance in the optimization of a logistics network. This study formulates a double objective function optimization model of reverse logistics facility location considering the balance between the functional objectives of the carbon emissions and the benefits. A hybrid multi-objective optimization algorithm that combines a gravitation algorithm and a particle swarm optimization algorithm is proposed to solve this reverse logistics facility location model. The mobile phone recycling logistics network in Jilin Province is applied as the case study to verify the feasibility of the proposed reverse logistics facility location model and solution method. Analysis and discussion are conducted to monitor the robustness of the results. The results prove that this approach provides an effective tool to solve the multi-objective optimization problem of reverse logistics location.





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