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航空貨運艙位存量控制方法研究

發(fā)布時間:2018-06-24 08:34

  本文選題:收益管理 + 貨運艙位存量控制 ; 參考:《南京航空航天大學》2013年碩士論文


【摘要】:在國際貿(mào)易快速增長、全球一體化進程不斷深化的大環(huán)境下,我國民航貨運行業(yè)獲得蓬勃發(fā)展。國家“天空開放”政策的推動給我國民航企業(yè)的貨運部門創(chuàng)造了巨大的發(fā)展良機,同時也使其面臨著嚴峻的挑戰(zhàn)。那么,如何提升民航企業(yè)貨運部門管理水平,增加營業(yè)收入,成為了我國航空公司亟待解決的重要課題。 本文在充分借鑒國內(nèi)外航空貨運收益管理相關(guān)研究成果的前提下,著重研究我國航空貨運的艙位存量控制方法。文章的主要內(nèi)容如下: 首先在充分研究灰色模型和多元回歸模型優(yōu)缺點的基礎(chǔ)上,將二者分別基于最小二乘原理及有效度原理,進行組合建立了兩種灰色多元回歸模型,并將其應(yīng)用于我國貨運吞吐量的預(yù)測。 其次,在研究航空貨運產(chǎn)品特性和航空公司貨運實際銷售流程的基礎(chǔ)上,研究了貨運艙位銷售合同對航空貨運收益的影響,建立了以航空公司利潤最大化為目標的艙位存量控制模型,針對模型中艙位需求的不確定性,采用隨機機會約束方法對其進行求解,,確定了航空公司艙位分配策略。通過算例分析,表明航空公司與協(xié)議客戶簽訂艙位銷售合同,可以更加準確的掌握市場需求信息,增加貨運收益。 最后,本文通過研究發(fā)現(xiàn)代理人與航空公司簽訂協(xié)議時通常傾向于簽訂市場區(qū)域的一攬子協(xié)議,針對市場需求的這一特征,航空公司需要考慮在一個區(qū)域上協(xié)議銷售的貨運艙位如何在各個代理人之間進行分配。以往收益管理的目標只有一個,即收益最大,但是在實踐中,決策者往往要考慮多個目標的實現(xiàn)。由此,本文建立了一個考慮銷售收入、銷售艙位數(shù)目和客戶關(guān)系管理這三個指標的多目標規(guī)劃模型,利用“序貫算法”結(jié)合LINGO軟件對模型進行了求解,通過算例分析,驗證了模型的有效性,為航空公司貨運艙位存量控制提供了一種新的方法。 后面兩個艙位存量控制的模型均在符合配載要求的情況下,選取了收益最大的艙位控制方案,以此來增加航空公司收益。通過算例分析來驗證模型的有效性,為航空公司提供更為科學的艙位存量控制方法。
[Abstract]:With the rapid growth of international trade and the deepening of the process of global integration, China's civil aviation freight industry has developed vigorously. The promotion of China's "Sky opening" policy has created a great opportunity for the development of the freight transport sector of China's civil aviation enterprises, and at the same time has made it face severe challenges. Therefore, how to improve the management level and increase the operating income of civil aviation enterprises has become an important issue to be solved urgently by Chinese airlines. Based on the research results of domestic and foreign air cargo revenue management, this paper focuses on the control method of air cargo space stock in China. The main contents of this paper are as follows: firstly, on the basis of studying the advantages and disadvantages of grey model and multivariate regression model, the two models are based on the least square principle and the validity principle, respectively. Two grey multivariate regression models are established and applied to the prediction of freight throughput in China. Secondly, on the basis of studying the characteristics of air cargo products and the actual sales process of air cargo, the influence of cargo space sales contract on air cargo revenue is studied. A space inventory control model with the aim of maximizing the profit of airlines is established. In view of the uncertainty of space demand in the model, the stochastic opportunity constraint method is used to solve the problem, and the allocation strategy of space is determined. Through the example analysis, it shows that the airline and the agreement customer sign the cabin space sale contract, can grasp the market demand information more accurately, increases the freight transport income. Finally, through the research, we find that when the agent signs the agreement with the airline, he usually tends to sign the package agreement in the market area, aiming at this characteristic of the market demand. Airlines need to consider how cargo space agreed to be sold in a region is allocated among agents. In the past, there was only one goal of revenue management, that is, the maximum revenue, but in practice, decision makers often consider the realization of multiple objectives. Therefore, this paper establishes a multi-objective programming model which considers the sales revenue, the number of space and the customer relationship management. The model is solved by "sequential algorithm" and lingo software. The validity of the model is verified and a new method for cargo space inventory control of airlines is provided. The latter two models of space inventory control are in accordance with the requirements of stowage, and select the most profitable cabin space control scheme to increase the airline revenue. The validity of the model is verified by the example analysis, which provides a more scientific method for the control of space stock for airlines.
【學位授予單位】:南京航空航天大學
【學位級別】:碩士
【學位授予年份】:2013
【分類號】:F562.1

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