摘要
本文以国家药品带量集中采购为背景。为提高药品配送安全和时效,降低药品配送成本。基于大数据思想,根据备选药品物流中心所在地近20年遭受自然灾害的数据,构建备选药品物流中心未来遭受自然灾害的预测模型,在综合考虑药品配送安全性、配送成本、环保成本、时间满意度和实时路况下,构建动态不确定性-药品物流多中心选址-路径优化模型。根据所研究问题的特点,为提高算法的效能,本文充分利用模糊C均值聚类算法(FCM),粒子群算法(PSO)和禁忌搜索算法(TS)等各自优点,设计了PSO-FCM-TS混合算法。最后,根据国家药品集中带量采购招标结果数据,对模型和算法进行了验证、对比和分析,研究结论为药品物流企业决策提供了科学依据。
In order to reduce the burden of patients’medication costs,improve the quality of clinical medication,fundamentally improve the ecological environment of the pharmaceutical industry,promote the transformation of the pharmaceutical industry from market-driven to innovation-driven,and promote the solution of deep-seated institutional problems in the field of medical service system,in 2018,with the approval of the Central Comprehensive Deepening Reform Commission,the state organized the implementation of centralized and volume procurement of drugs.In 2020,the scale of the third batch of national organized centralized drug procurement reached tens of billions of yuan,with a total of 189 enterprises participating in the bidding process.Among them,125 enterprises were selected,and 191 drug product specifications were selected,with an average price reduction of 53%.How to utilize the data of natural disasters in various regions over the past two decades,based on the concept of big data,scientifically and reasonably laying out drug logistics centers and drug delivery routes,minimizing drug delivery risks,and safely and efficiently distributing multi enterprise,multi type,large batch,national,and high time efficient national centralized procurement drugs to demand cities,have become a new problem that drug logistics enterprises urgently need to solve.This article starts from the actual needs of the country and enterprises,and focuses on solving new problems that arise in reality.It provides a new solution for the multi type,large batch,national,and high time efficient drug distribution problem after the national drug centralized procurement.It further improves the scientific nature and safety of the drug logistics center location distribution path,and provides a scientific theoretical basis for drug logistics decision-making.In order to improve the timeliness and safety of drug distribution,we aim to address the problem of multiple types,large quantities,nationwide,and high timeliness of drug distribution.This article i
作者
袁志远
高杰
杨才君
YUAN Zhiyuan;GAO Jie;YANG Caijun(School of Management,Xi’an Jiaotong University,Xi’an 710049,China;School of Pharmacy,Xi’an Jiaotong University,Xi’an 710061,China)
出处
《运筹与管理》
CSSCI
CSCD
北大核心
2023年第8期32-37,共6页
Operations Research and Management Science
