Xi Yulong, Tao Fengming, Brooks Schanelle
Chongqing University, School of Management Science and Real Estate, Chongqing, China.
PeerJ Comput Sci. 2023 Aug 24;9:e1519. doi: 10.7717/peerj-cs.1519. eCollection 2023.
With the development of the express delivery industry, how to increase the recycling rate of waste cartons has become a problem that needs to be solved. Recycling enterprises began to provide the new recycling mode, door-to-door recycling services, to residents with waste cartons. In this article, we constructed a site selection model for a carton recycling site with the aim of maximizing total profits. Considering the residents' recycling willingness and the government subsidy earned through the contribution to carbon emission reduction, this model achieves the task of site selection and unit price fixation for carton recycling. We used the particle swarm optimization (PSO) algorithm to solve the model and compared it with the genetic algorithm (GA) for validity testing. PSO algorithm was also used to carry out sensitivity analysis in this model. The proposed model and the results of the sensitivity analysis can be used for decision-making in recycling enterprises as well as for further research on waste recycling and reverse logistics.
随着快递行业的发展，如何提高废纸箱回收率已成为一个亟待解决的问题。回收企业开始向居民提供新的回收模式——上门回收服务，以回收废纸箱。在本文中，我们构建了一个纸箱回收站点选址模型，旨在实现总利润最大化。考虑到居民的回收意愿以及通过对碳排放减少做出贡献而获得的政府补贴，该模型完成了纸箱回收的站点选址和单价确定任务。我们使用粒子群优化（PSO）算法求解该模型，并与遗传算法（GA）进行比较以进行有效性测试。PSO算法还用于该模型的敏感性分析。所提出的模型和敏感性分析结果可用于回收企业的决策，以及对废物回收和逆向物流的进一步研究。
