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An Optimization Model for Expired Drug Recycling Logistics Networks and Government Subsidy Policy Design Based on Tri-level Programming

机译:基于三级规划的药品回收过期网络优化模型及政府补贴政策设计

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摘要

In order to recycle and dispose of all people’s expired drugs, the government should design a subsidy policy to stimulate users to return their expired drugs, and drug-stores should take the responsibility of recycling expired drugs, in other words, to be recycling stations. For this purpose it is necessary for the government to select the right recycling stations and treatment stations to optimize the expired drug recycling logistics network and minimize the total costs of recycling and disposal. This paper establishes a tri-level programming model to study how the government can optimize an expired drug recycling logistics network and the appropriate subsidy policies. Furthermore, a Hybrid Genetic Simulated Annealing Algorithm (HGSAA) is proposed to search for the optimal solution of the model. An experiment is discussed to illustrate the good quality of the recycling logistics network and government subsides obtained by the HGSAA. The HGSAA is proven to have the ability to converge on the global optimal solution, and to act as an effective algorithm for solving the optimization problem of expired drug recycling logistics network and government subsidies.
机译:为了回收和处置所有人的过期药品,政府应制定一项补贴政策,以鼓励用户退还过期药品,而药店应负责回收过期药品,也就是成为回收站。为此,政府有必要选择合适的回收站和处理站,以优化过期的药品回收物流网络并最大程度地减少回收和处置的总成本。本文建立了一个三级规划模型,以研究政府如何优化过期的药品回收物流网络和适当的补贴政策。此外,提出了一种混合遗传模拟退火算法(HGSAA)来寻找模型的最优解。讨论了一个实验,以说明HGSAA获得的回收物流网络和政府补贴的良好质量。 HGSAA被证明具有收敛于全球最优解决方案的能力,并且可以作为解决过期药品回收物流网络和政府补贴的优化问题的有效算法。

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