本文關(guān)鍵詞：考慮服務(wù)半徑約束的帶預(yù)見性競爭選址問題研究　出處：《清華大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 競爭設(shè)施選址 服務(wù)半徑 禁忌搜索 重力模型 雙層非線性整數(shù)規(guī)劃

【摘要】：在過去這些年,伴隨著持續(xù)高速增長,中國物流快遞行業(yè)市場規(guī)模已經(jīng)躍居世界第一位。隨著市場的繁盛,每個物流公司都想擴大自己的市場份額,增加公司利潤。為了增加企業(yè)的市場占有率,給顧客更好的服務(wù)感受,增加企業(yè)競爭力,某物流快遞企業(yè)計劃建立自營的快遞服務(wù)便利店,然而其在進行選址決策時知道其它快遞企業(yè)會在將來不久也進入目標(biāo)市場,這就是本文將要研究的帶預(yù)見性競爭設(shè)施選址問題。競爭設(shè)施選址問題明確地考慮到競爭對手的存在,他們已經(jīng)(或?qū)⒁?進入目標(biāo)市場,而新建設(shè)施將與他們競爭獲得市場份額。本文將要研究的帶預(yù)見性競爭設(shè)施選址是兩階段設(shè)施選址問題,即領(lǐng)導(dǎo)者決策時會考慮到跟隨者將來的行為。第一階段,領(lǐng)導(dǎo)者進行新設(shè)施選址決策,使得其市場份額最大,而且領(lǐng)導(dǎo)者知道跟隨者的目標(biāo)函數(shù)以及顧客喜好;第二階段,跟隨者已經(jīng)知道領(lǐng)導(dǎo)者新建設(shè)施選址,然后確定其新建設(shè)施選址,使得其市場份額最大,同時跟隨者也知道各位顧客的喜好。本文在帶預(yù)見性競爭設(shè)施選址問題研究的基礎(chǔ)上,結(jié)合便利店選址問題實際情況,將設(shè)施服務(wù)半徑約束納入選址研究范圍。首先,基于經(jīng)典Huff重力模型,考慮服務(wù)半徑約束,構(gòu)造了新的吸引力函數(shù),在其中假設(shè)設(shè)施對顧客吸引力隨著他們之間距離的增加逐漸下降,且設(shè)施與顧客超出一定的距離時,其吸引力降為零。接著設(shè)計出一個相應(yīng)的顧客選擇行為準(zhǔn)則:當(dāng)顧客位于多個設(shè)施的服務(wù)半徑內(nèi)時,采用隨機性模型,即顧客需求在這多個設(shè)施之間按照一定的概率分配;當(dāng)顧客位于單個設(shè)施的服務(wù)半徑內(nèi)時,采用確定性模型,即顧客需求全部分配給該設(shè)施;當(dāng)顧客超出任意設(shè)施服務(wù)半徑內(nèi)時,其需求將不能被服務(wù)。然后,本文以領(lǐng)導(dǎo)者市場份額最大化為目標(biāo)函數(shù),按照提出的顧客選擇行為規(guī)則進行相應(yīng)的競爭需求分配,構(gòu)造出一個雙層非線性整數(shù)規(guī)劃模型。接著,設(shè)計了一種兩階段混合禁忌搜索算法對問題模型進行計算。最后,對設(shè)計算法的性能進行測試,通過對小規(guī)模算例的求解,并將其結(jié)果與最優(yōu)解進行比較;之后,利用算法對大規(guī)模問題進行求解。結(jié)果表明算法可以準(zhǔn)確獲得小規(guī)模問題的最優(yōu)解,而對于大規(guī)模問題算法也可以快速進行求解。
[Abstract]:In the past few years, with the continuous rapid growth, the scale of the Chinese logistics express industry has leapt to the first place in the world. With the prosperity of the market, each logistics company wants to expand its market share. In order to increase the market share of enterprises, give customers a better feeling of service, increase the competitiveness of enterprises, a logistics express enterprise plans to establish a convenience store of express service. However, it knows that other express delivery companies will enter the target market in the near future. This is the prospective competitive facility location problem to be studied in this paper. The competitive facility location problem explicitly considers the existence of competitors and they have (or will) enter the target market. New facilities will compete with them to gain market share. This paper will study the location of facilities with foresight competition is a two-stage facility location problem. In the first stage, the leader makes the new facility location decision, which makes the leader have the largest market share, and the leader knows the objective function of the follower and the customer preference. In the second stage, the follower already knows the leader new facility location, then determines its newly built facility location, makes its market share biggest. At the same time, the follower also knows the preferences of customers. Based on the study of location problem with predictive competitive facilities, this paper combines the actual situation of convenience store location problem. Firstly, based on the classical Huff gravity model, a new attraction function is constructed by considering the service radius constraints. It is assumed that the attractiveness of the facility to the customer decreases gradually with the increase of the distance between them, and the facility exceeds a certain distance from the customer. The attractiveness is reduced to zero. Then a corresponding customer selection code of conduct is designed: when the customer is within the service radius of multiple facilities, the random model is adopted. That is, customer needs are allocated according to a certain probability between these facilities; When the customer is within the service radius of a single facility, the deterministic model is adopted, that is, the customer needs are assigned to the facility. When the customer exceeds the radius of any facility service, the requirement can not be served. Then, this paper takes the market share maximization of the leader as the objective function. According to the proposed rules of customer selection behavior, a bilevel nonlinear integer programming model is constructed. A two-stage hybrid Tabu search algorithm is designed to calculate the problem model. Finally, the performance of the design algorithm is tested, and the results are compared with the optimal solution by solving small scale examples. The results show that the algorithm can obtain the optimal solution of the small scale problem accurately, and the algorithm can also solve the large scale problem quickly.
【學(xué)位授予單位】：清華大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：F259.2

【引證文獻】

相關(guān)碩士學(xué)位論文 前1條

1 高瑩;考慮顧客選擇行為的競爭選址問題研究[D];深圳大學(xué);2017年

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本文編號：1363779