【摘要】：摘要：安全生產一直是一個全民關注的話題,尤其是當前日益興起的物流業(yè),安全管理不容忽視�，F(xiàn)階段隨著物流業(yè)的迅速發(fā)展,我國物流企業(yè)數(shù)量逐漸增多,缺乏有序監(jiān)管,物流企業(yè)安全生產形勢不容樂觀,尤其是在危險品儲存及運輸?shù)拳h(huán)節(jié),重特大事故時有發(fā)生。企業(yè)安全投入雖然有所加大,但安全生產現(xiàn)狀仍沒有大的改觀,究其根本原因是企業(yè)前期安全防范不到位,安全投入缺乏理論與實踐相結合,安全投入決策不夠科學導致效益不高。目前,我國對物流安全投入的研究還不甚完善,繼續(xù)深入安全投入的預測和優(yōu)化研究可以為企業(yè)安全投入決策提供依據(jù)。 企業(yè)安全投入工作具有一定的復雜性和長期性,基于安全投入具有一定的時間節(jié)點,本文采用灰色系統(tǒng)理論建立灰色微分預測模型,對企業(yè)安全費用的支出規(guī)律做出模糊性的長期描述,對企業(yè)未來的安全投入總額進行預測；在安全投入的優(yōu)化環(huán)節(jié),考慮風險的“貢獻”程度是衡量風險重要度的指標,本文在事故分析、專家問卷方法的基礎之上,采用貢獻率權重模型對風險因素作用于物流生產事故的貢獻程度進行描述,獲取貢獻率權重,對安全投入優(yōu)化分配進行指導。 本文在分析研究安全投入理論的基礎上,基于GM(1,1)灰色預測模型預測企業(yè)安全投入總額；通過物流行業(yè)風險因素辨識和貢獻率權重測算獲取安全投入方向,結合企業(yè)自身安全生產的需求,基于最優(yōu)化理論(Optimality Theory)建立線性規(guī)劃模型進行安全資源分配。通過兩種理論結合而成的OT-GM (Optimality Theory-Grey Model)模型進行安全投入的優(yōu)化研究,同時提出相應的合理化建議。
[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.
【學位授予單位】：北京交通大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：F259.2

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