【摘要】：近年來,隨著突發(fā)自然災(zāi)害事故發(fā)生的日益頻繁,其對社會所造成的破壞與影響也呈現(xiàn)出加劇和擴大的趨勢。在無法準(zhǔn)確預(yù)知災(zāi)害發(fā)生時間和地點的情況下,研究如何有效降低災(zāi)害發(fā)生后所造成的損失和影響,已成為災(zāi)害應(yīng)急管理的重要課題。已有的研究表明：同災(zāi)后的救援相比,災(zāi)前的物質(zhì)儲備在時效性和經(jīng)濟性上具有明顯的優(yōu)勢,對于有效降低災(zāi)害的人員和財產(chǎn)損失有重要作用。應(yīng)急服務(wù)設(shè)施的選址問題作為戰(zhàn)略決策,它對災(zāi)害救援效果的影響是持久和深遠的。而在眾多的選址理論中,覆蓋選址模型在應(yīng)急服務(wù)設(shè)施選址問題中具有十分廣泛的應(yīng)用。本文梳理了覆蓋選址模型自其提出以來至今的主要發(fā)展過程,并對其分類進行了闡述。具體來講,按照模型的目標(biāo)函數(shù)劃分,主要分為集合覆蓋和最大覆蓋。按照建模所使用的方法,分為確定性模型,概率模型和應(yīng)用排隊論的模型。為了加深對基本模型的理解和提高對模型的應(yīng)用能力,重點對幾類重要的覆蓋選址模型做了進一步介紹,包括模型的具體表現(xiàn)形式及其重要假設(shè)和不足之處。隨后,重點研究了在假設(shè)條件和處理方法上更加精確的應(yīng)用排隊論的概率覆蓋選址模型。按照排隊系統(tǒng)的不同,分別研究了M/M/s/s損失系統(tǒng)和4/G/s非損失系統(tǒng)條件下的排隊覆蓋選址模型。對于前者,建立了有服務(wù)水平保證的排隊覆蓋選址模型：無法立刻得到服務(wù)的需求因不能排隊等候而損失,但是任何被覆蓋的需求點能夠得到服務(wù)的概率不小于事先給定的服務(wù)水平。并從覆蓋量的角度建立了描述模型MCLP-R1和便于求解的整數(shù)線性規(guī)劃模型MCLP-IR2,設(shè)計了在需求可以部分滿足時的求解算法。結(jié)果表明,該算法可以在較短的時間內(nèi)求得令人滿意的解。對于后者,無法立刻得到服務(wù)的需求將進行排隊等候,但是額外限制了排隊等候的時間。考慮到不同的需求指派方式,分別建立了基于系統(tǒng)指派和顧客選擇兩種指派方式下的模型,QMCLP-SA和QMCLP-NS。對于系統(tǒng)指派方式,設(shè)計了求解問題的算法,結(jié)果表明：該算法可以在較短的時間內(nèi)求得令人滿意的解,因此可以迅速得出問題的下界。同時,對比分析了以上兩種不同指派方式所造成的選址差異,結(jié)果表明：系統(tǒng)指派方式具有較高的效率,但是從顧客的角度來看,則可能存在不公平問題；而顧客最近選擇方式所得到的結(jié)果則恰好相反。最后,對研究的不足和進一步改進的方向做了總結(jié)和建議。
[Abstract]:In recent years, with the increasing frequency of sudden natural disasters, the damage and impact on society has also shown a trend of aggravation and expansion. Under the condition that the time and place of disaster can not be predicted accurately, it has become an important topic of disaster emergency management to study how to effectively reduce the loss and impact caused by disaster. Previous studies have shown that compared with post-disaster rescue, pre-disaster material reserves have obvious advantages in timeliness and economy, and play an important role in effectively reducing the loss of people and property in disasters. As a strategic decision, the location of emergency service facilities has a lasting and far-reaching impact on disaster rescue. Among many location theories, coverage location model is widely used in emergency service facility location problem. This paper combs the main development process of the coverage location model since it was put forward, and expounds its classification. Specifically, according to the objective function of the model, it is mainly divided into set coverage and maximum coverage. According to the method used in modeling, it is divided into deterministic model, probability model and applied queuing theory model. In order to deepen the understanding of the basic model and improve the application ability of the model, several important coverage location models are further introduced, including the specific forms of the model and its important assumptions and shortcomings. Then, the probabilistic coverage location model with more accurate application of queuing theory in hypothetical conditions and processing methods is studied. According to the difference of queuing system, the queuing coverage location model of M/s/s loss system and 4/G/s non-loss system is studied respectively. For the former, a queuing coverage location model with service level guarantee is established: the demand that can not get the service immediately is lost because it can not wait in line. However, the probability that any covered demand point can get a service is not less than the given service level in advance. From the point of view of coverage, the description model MCLP-R1 and the integer linear programming model MCLP-IR2, which is convenient to solve, are established to design an algorithm when the requirements can be partially satisfied. The results show that the algorithm can obtain satisfactory solutions in a short time. For the latter, the need for immediate service will be lined up, but the waiting time is extra limited. Considering different requirements assignment methods, the models based on system assignment and customer selection are established, QMCLP-SA and QMCLP-NS., respectively. For the system assignment mode, an algorithm is designed to solve the problem. The results show that the algorithm can obtain a satisfactory solution in a short time, so the lower bound of the problem can be obtained quickly. At the same time, the location differences caused by the above two different assignment methods are compared and analyzed. The results show that the system assignment mode has higher efficiency, but from the customer's point of view, there may be unfair problems. The results of customers' recent choices are the opposite. Finally, the shortcomings of the research and the direction of further improvement are summarized and suggested.
【學(xué)位授予單位】：南京大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TU984.116;D63

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本文編號：2480707