本文選題：便利店 + 選址�。� 參考：《清華大學(xué)》2014年碩士論文

【摘要】：近十年來(lái)，隨著網(wǎng)上購(gòu)物的興起，快遞行業(yè)也得到了迅速的發(fā)展，但快遞行業(yè)一直給大眾留下低端服務(wù)業(yè)的印象，因?yàn)樵诔鞘欣�，我們通常見到的只是騎著電動(dòng)車到處送快件的快遞員。因此建立規(guī)范統(tǒng)一、帶有明顯企業(yè)標(biāo)志的快遞服務(wù)便利店，可以提高快遞企業(yè)形象，增強(qiáng)人們對(duì)快遞業(yè)的認(rèn)同感，同時(shí)快遞企業(yè)還可開拓附加服務(wù)來(lái)增加營(yíng)收，如自寄自取、快件包裝等。 零售選址方法主要分為綜合分析法和數(shù)學(xué)模型法。綜合分析法即綜合分析候選位置點(diǎn)經(jīng)濟(jì)、交通、需求量、建設(shè)費(fèi)用等信息，，并應(yīng)用層次分析法對(duì)候選位置點(diǎn)綜合評(píng)價(jià)，最終選出符合公司各項(xiàng)目標(biāo)的位置點(diǎn)；這種方法得出來(lái)的結(jié)果一般更加合理，但同時(shí)這種方法也非常耗費(fèi)人力、物力，且費(fèi)時(shí)較長(zhǎng)。由于本文所研究選址問題需設(shè)立便利店數(shù)目較多，單個(gè)便利店設(shè)立成本相對(duì)較低，因此基于點(diǎn)需求和面需求，本文建立兩個(gè)多目標(biāo)選址模型來(lái)解決快遞服務(wù)便利店選址問題。 在基于點(diǎn)需求的多目標(biāo)選址模型中，本文將客戶需求點(diǎn)分為寄件業(yè)務(wù)需求點(diǎn)和取件業(yè)務(wù)需求點(diǎn)，針對(duì)兩種業(yè)務(wù)不同特性在模型中做不同假設(shè)和處理，然后將市場(chǎng)份額與選址費(fèi)用作為模型目標(biāo)，并考慮門檻約束建立模型。利用某快遞公司在上海徐匯區(qū)一周內(nèi)收發(fā)快遞數(shù)據(jù)作為模型的輸入數(shù)據(jù)，利用多目標(biāo)進(jìn)化算法MNSGA-II和NSGA-II進(jìn)行求解，分別得到一組帕累托非支配解集。根據(jù)本文采用的四個(gè)多目標(biāo)優(yōu)化評(píng)價(jià)指標(biāo)對(duì)這兩種算法進(jìn)行比較，結(jié)果顯示MNSGA-II求解的質(zhì)量略優(yōu)于NSGA-II,但NSGA-II和MNSGA-II得到的非支配解集均很好地逼近了帕累托最優(yōu)解集。 在基于面需求的多目標(biāo)選址模型中，利用軟件工具ArcGIS根據(jù)道路和水系將需求區(qū)域切分成多個(gè)子區(qū)域，并計(jì)算這些子區(qū)域的需求密度。以各子區(qū)域中心點(diǎn)為便利店候選位置點(diǎn)，考慮道路、水系的阻隔因素計(jì)算各候選點(diǎn)覆蓋需求總量�？紤]門檻約束和便利店之間距離限制，以市場(chǎng)份額和選址費(fèi)用為目標(biāo)建立模型。模型利用NSGA-II算法進(jìn)行求解，在求解質(zhì)量和求解速度方面均達(dá)到很好效果。 在基于點(diǎn)需求的多目標(biāo)選址模型和基于面需求的多目標(biāo)選址模型得到帕累托非支配解集后，均采用一種基于逼近理想解排序的方法（TOPSIS）給出最合理解，以供決策者參考。另外，在實(shí)際選址決策時(shí)，決策者可根據(jù)自身?xiàng)l件在帕累托非支配解集中選擇合適的選址方案。
[Abstract]:Over the past decade, with the rise of online shopping, express delivery industry has also been rapid development, but the express industry has been leaving the impression of low-end services to the public, because in the city, What we usually see is the courier who rides an electric car everywhere to deliver express mail. Therefore, the establishment of a standardized and unified express service convenience store with a clear enterprise logo can enhance the image of express delivery enterprises and enhance people's identity with the express delivery industry. At the same time, express delivery enterprises can also develop additional services to increase revenue, such as self-posting. Express package, etc. Retail location method is mainly divided into comprehensive analysis method and mathematical model method. The synthetic analysis method is to analyze the information of economy, transportation, demand, construction cost and so on of the candidate location point synthetically, and to evaluate the candidate position point synthetically by using the analytic hierarchy process (AHP), and finally to select the position point which accords with the company's each target. The results obtained by this method are generally more reasonable, but at the same time, the method also consumes manpower, material resources and takes a long time. Because the number of convenience stores needed to be set up and the cost of setting up a single convenience store is relatively low in this paper, two multi-objective location models are established to solve the location problem of express service convenience store based on point demand and surface demand. In the multi-objective location model based on point requirement, this paper divides the customer demand point into send business requirement point and pick up business requirement point, and make different hypotheses and processing in the model for different characteristics of two kinds of business. Then the market share and location cost are taken as the model objectives, and the threshold constraints are considered to establish the model. Using a delivery company to send and receive express data within one week in Xuhui district as input data of the model, a set of Pareto non-dominated solution sets is obtained by using multi-objective evolutionary algorithms MNSGA-II and NSGA-II to solve the problem. The results show that the quality of MNSGA-II is slightly better than that of NSGA-II.However, the set of non-dominated solutions obtained by NSGA-II and MNSGA-II are all close to the Pareto optimal solution set. In the multi-objective location model based on surface requirements, the requirement area is divided into several sub-regions by using the software tool ArcGIS, and the demand density of these sub-regions is calculated according to the road and water system. Taking the center of each sub-region as the candidate location of convenience store, the total coverage demand of each candidate point is calculated by considering the blocking factors of road and water system. Considering the threshold constraint and the distance between convenience stores, the model is established with the aim of market share and location cost. NSGA-II algorithm is used to solve the model, which achieves good results in both quality and speed. After the multi-objective location model based on the point requirement and the multi-objective location model based on the surface requirement get the Pareto non-dominant solution set, the most reasonable solution is given by using a method based on the ranking of approximate ideal solutions, which is for the reference of the decision makers. In addition, in the actual location decision, the decision maker can choose the appropriate location scheme in the Pareto non-dominant solution set according to his own conditions.
【學(xué)位授予單位】：清華大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：F259.2

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