基于OT-GM模型的物流企业安全投入预测与优化研究

发布时间：2019-05-13 18:28

【摘要】：摘要：安全生产一直是一个全民关注的话题,尤其是当前日益兴起的物流业,安全管理不容忽视。现阶段随着物流业的迅速发展,我国物流企业数量逐渐增多,缺乏有序监管,物流企业安全生产形势不容乐观,尤其是在危险品储存及运输等环节,重特大事故时有发生。企业安全投入虽然有所加大,但安全生产现状仍没有大的改观,究其根本原因是企业前期安全防范不到位,安全投入缺乏理论与实践相结合,安全投入决策不够科学导致效益不高。目前,我国对物流安全投入的研究还不甚完善,继续深入安全投入的预测和优化研究可以为企业安全投入决策提供依据。企业安全投入工作具有一定的复杂性和长期性,基于安全投入具有一定的时间节点,本文采用灰色系统理论建立灰色微分预测模型,对企业安全费用的支出规律做出模糊性的长期描述,对企业未来的安全投入总额进行预测；在安全投入的优化环节,考虑风险的“贡献”程度是衡量风险重要度的指标,本文在事故分析、专家问卷方法的基础之上,采用贡献率权重模型对风险因素作用于物流生产事故的贡献程度进行描述,获取贡献率权重,对安全投入优化分配进行指导。本文在分析研究安全投入理论的基础上,基于GM(1,1)灰色预测模型预测企业安全投入总额；通过物流行业风险因素辨识和贡献率权重测算获取安全投入方向,结合企业自身安全生产的需求,基于最优化理论(Optimality Theory)建立线性规划模型进行安全资源分配。通过两种理论结合而成的OT-GM (Optimality Theory-Grey Model)模型进行安全投入的优化研究,同时提出相应的合理化建议。
[Abstract]:Abstract: safety in production has always been a topic of concern to the whole people, especially the rising logistics industry, safety management can not be ignored. At present, with the rapid development of logistics industry, the number of logistics enterprises in China is gradually increasing, lack of orderly supervision, the situation of production safety in logistics enterprises is not optimistic, especially in the storage and transportation of dangerous goods, serious accidents occur from time to time. Although the investment in safety of enterprises has increased, the present situation of safety in production has not improved greatly. The fundamental reason is that the safety prevention in the early stage of the enterprise is not in place, and the safety investment is lack of the combination of theory and practice. Safety investment decision-making is not scientific enough to lead to low efficiency. At present, the research on logistics safety input in our country is not very perfect, and the further research on the prediction and optimization of safety input can provide the basis for the decision-making of enterprise safety input. The safety input of enterprises has certain complexity and long-term nature. Based on the fact that the safety investment has a certain time node, this paper uses the grey system theory to establish the grey differential prediction model. This paper makes a fuzzy long-term description of the expenditure law of the enterprise safety cost, and forecasts the total safety investment of the enterprise in the future. In the optimization of safety input, considering the "contribution" of risk is an index to measure the importance of risk. This paper is based on accident analysis and expert questionnaire method. The contribution rate weight model is used to describe the contribution degree of risk factors on logistics production accidents, to obtain the contribution rate weight, and to guide the optimal distribution of safety input. On the basis of analyzing and studying the theory of safety investment, this paper forecasts the total amount of enterprise safety investment based on GM (1, 1) grey prediction model. Through the identification of risk factors and the calculation of contribution rate weight in logistics industry, the direction of safety input is obtained, and the linear programming model is established based on optimization theory (Optimality Theory) to allocate safety resources according to the demand of enterprise safety in production. The OT-GM (Optimality Theory-Grey Model) model, which is a combination of the two theories, is used to optimize the safety input, and the corresponding rationalization suggestions are put forward at the same time.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：F259.2

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