本文關(guān)鍵詞： 供需關(guān)系 旅客轉(zhuǎn)移行為 收益管理 聯(lián)合優(yōu)化 期望總收益　出處：《西南交通大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著鐵路網(wǎng)的進(jìn)一步完善,我國(guó)鐵路客運(yùn)能力將進(jìn)一步得到釋放,如何更加有效的利用鐵路客運(yùn)產(chǎn)品的運(yùn)輸能力,將是鐵路企業(yè)亟待解決的問(wèn)題。另一方面,我國(guó)客運(yùn)市場(chǎng)競(jìng)爭(zhēng)態(tài)勢(shì)日趨激烈,鐵路部門若要占據(jù)優(yōu)勢(shì)地位,就必須促使其營(yíng)銷管理向精細(xì)化、效益化轉(zhuǎn)變,以提高我國(guó)鐵路客運(yùn)行業(yè)的整體收益水平。在當(dāng)前背景下,收益管理成了我國(guó)鐵路客運(yùn)行業(yè)有效利用各種運(yùn)輸資源、提高行業(yè)競(jìng)爭(zhēng)力的創(chuàng)新型途徑。以供需關(guān)系下受旅客轉(zhuǎn)移行為影響的鐵路客票收益管理為研究對(duì)象,以促使期望總收益最大為目標(biāo),本文主要在以下兩個(gè)方向展開研究:(1)對(duì)在供需不匹配下的旅客轉(zhuǎn)移行為進(jìn)行定量描述和分析;(2)分別基于不同客運(yùn)產(chǎn)品和不同票價(jià)等級(jí)供需關(guān)系下旅客的轉(zhuǎn)移行為通過(guò)對(duì)多區(qū)間客票優(yōu)化的研究制定相關(guān)收益管理模型,以主動(dòng)引導(dǎo)旅客在供需不匹配下選擇行為的變化促使整體收益最大化。本文首先在對(duì)收益管理發(fā)展及定義進(jìn)行概述的基礎(chǔ)上,結(jié)合近些年收益管理的研究成果,指出了未來(lái)收益管理研究的主要難點(diǎn)和趨勢(shì),并對(duì)我國(guó)鐵路客運(yùn)行業(yè)實(shí)施收益管理的適應(yīng)性與特殊性進(jìn)行了分析,對(duì)以后有關(guān)我國(guó)鐵路客票收益管理相關(guān)理論和方法的研究具有重要的借鑒意義,然后總結(jié)了與本文相關(guān)的收益管理基礎(chǔ)模型。其次,在鐵路客票收益管理需求預(yù)測(cè)方面,本文首先分析了歷史售票數(shù)據(jù)不能直接反應(yīng)出旅客真實(shí)需求的原因,進(jìn)而將無(wú)約束需求預(yù)測(cè)的概念引入鐵路客票收益管理研究領(lǐng)域,并從單維和多維的角度對(duì)無(wú)約束需求估計(jì)的相關(guān)方法進(jìn)行了詳細(xì)概述。然后,在鐵路旅客選擇行為方面,相比之前的以旅客主動(dòng)意愿選擇行為為主要研究對(duì)象,本文進(jìn)一步對(duì)供需不匹配下旅客的轉(zhuǎn)移行為展開研究。首先以廣義出行費(fèi)用代替效用函數(shù)建立了初始客流分擔(dān)率模型,然后進(jìn)一步設(shè)計(jì)了在供需不匹配下旅客在不同客運(yùn)產(chǎn)品間轉(zhuǎn)移概率的計(jì)算方法,不僅反映了鐵路旅客對(duì)各種客運(yùn)產(chǎn)品的需求意愿,同時(shí),可以定量描述出在實(shí)際受運(yùn)輸能力或控制策略限制下旅客的轉(zhuǎn)移行為。最后,在鐵路客票收益管理模型方面,圍繞收益管理的研究趨勢(shì),一方面,針對(duì)我國(guó)目前鐵路客票單一票價(jià)的特點(diǎn),基于兩種不同客運(yùn)產(chǎn)品供需關(guān)系下的旅客選擇行為,并將其嵌入網(wǎng)絡(luò)收益管理模型中,建立了一個(gè)非線性整數(shù)規(guī)劃模型同時(shí)實(shí)現(xiàn)對(duì)兩種不同客運(yùn)產(chǎn)品多區(qū)間客票的聯(lián)合優(yōu)化(第四章);另一方面,在對(duì)未來(lái)票價(jià)體制發(fā)展趨勢(shì)分析下,以收益管理差別定價(jià)為背景,基于旅客向上購(gòu)買行為,利用嵌套型席位控制方法建立了單一席位類型兩種不同價(jià)格等級(jí)客票的多區(qū)間優(yōu)化模型(第五章)。利用改進(jìn)的粒子群算法對(duì)上述兩個(gè)模型進(jìn)行求解,并分別通過(guò)算例對(duì)模型進(jìn)行數(shù)值分析,以觀察旅客選擇行為對(duì)席位控制決策及整體收益的影響。
[Abstract]:With the further improvement of railway network, China's railway passenger transport capacity will be further released, how to make more effective use of the transport capacity of railway passenger transport products, will be a problem to be solved urgently by railway enterprises on the other hand. Our country passenger transport market competition situation day by day intense, if the railroad department wants to occupy the superiority position, must urge its marketing management to be refined, the benefit transformation. In order to improve the overall income level of China's railway passenger transport industry. Under the current background, revenue management has become the effective use of various transport resources in China's railway passenger transport industry. To improve the competitiveness of the industry innovative approaches. Under the relationship between supply and demand affected by passenger transfer behavior of railway ticket revenue management as the research object, in order to promote the maximum expected total income as the goal. This paper mainly focuses on the following two directions: 1) quantitative description and analysis of the behavior of passenger transfer under the mismatch of supply and demand; Based on different passenger transport products and different fare levels of the relationship between supply and demand passenger transfer behavior through the study of multi-interval ticket optimization to develop the relevant revenue management model. In order to guide passengers to change their choice behavior under the mismatch of supply and demand, the overall income is maximized. Firstly, this paper summarizes the development and definition of revenue management, and combines the research results of revenue management in recent years. This paper points out the main difficulties and trends of the future revenue management research, and analyzes the adaptability and particularity of the revenue management in China's railway passenger transport industry. It is of great significance to study the related theories and methods of railway ticket revenue management in China, and then summarize the basic model of revenue management related to this paper. Secondly. In the railway ticket revenue management demand prediction, this paper first analyzes the historical ticket sales data can not directly reflect the real demand of passengers. Then the concept of unconstrained demand forecasting is introduced into the research field of railway ticket revenue management, and the relevant methods of unconstrained demand estimation are summarized in detail from the perspective of single and multidimensional. Then. In the aspect of railway passenger choice behavior, compared with the previous one, the main research object is the passenger's initiative choice behavior. In this paper, the transfer behavior of passengers under the mismatch of supply and demand is further studied. Firstly, the initial passenger flow sharing rate model is established with generalized travel cost instead of utility function. Then the paper further designs the calculation method of passenger transfer probability between different passenger products under the mismatch of supply and demand, which not only reflects the desire of railway passengers for various passenger transport products, but also. We can quantitatively describe the transfer behavior of passengers under the constraints of actual transportation capacity or control strategy. Finally, in the railway ticket revenue management model, around the research trend of revenue management, on the one hand. According to the characteristics of single ticket price of railway ticket in our country, based on the passenger choice behavior under the relationship between supply and demand of two different passenger transport products, it is embedded in the network revenue management model. A nonlinear integer programming model is established to realize the joint optimization of two different passenger products with multi-interval ticket simultaneously (Chapter 4th). On the other hand, under the analysis of the development trend of the future fare system, taking the income management differential pricing as the background, based on the upward purchase behavior of passengers. The multi-interval optimization model of single seat type and two different price grades is established by using nested seat control method (Chapter 5th). The improved particle swarm optimization algorithm is used to solve the above two models. Numerical analysis of the model is carried out through numerical examples to observe the influence of passenger selection behavior on seat control decision and overall income.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F532;F274

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