發(fā)布時(shí)間：2018-06-22 19:19

  本文選題：機(jī)隊(duì)規(guī)劃 + 機(jī)型分配��； 參考：《南京航空航天大學(xué)》2016年博士論文

【摘要】：機(jī)隊(duì)是航空公司進(jìn)行運(yùn)輸生產(chǎn)的載體,機(jī)隊(duì)規(guī)劃是航空公司重要戰(zhàn)略性規(guī)劃內(nèi)容之一,是決定航空公司未來生死存亡的關(guān)鍵性戰(zhàn)略決策,同時(shí)也是航空公司其它管理決策,例如航班計(jì)劃、飛機(jī)排班、收益管理等決策工作的前提,機(jī)隊(duì)規(guī)劃的好壞將從根本上影響航空公司未來運(yùn)輸生產(chǎn)的效益,因此,在滿足航空公司未來擬運(yùn)營生產(chǎn)環(huán)境(航線網(wǎng)絡(luò)結(jié)構(gòu)、航班計(jì)劃、需求與票價(jià)水平等)的基礎(chǔ)上,研究飛機(jī)機(jī)隊(duì)的規(guī)模與結(jié)構(gòu)特征,對于航空公司優(yōu)化運(yùn)輸產(chǎn)品結(jié)構(gòu),提高運(yùn)輸生產(chǎn)效益都具有重要的現(xiàn)實(shí)意義。針對宏觀機(jī)隊(duì)規(guī)劃法無法準(zhǔn)確反映出航班機(jī)型分配技術(shù)經(jīng)濟(jì)性能特點(diǎn)的缺陷,首先,本文針對單基地線形航線網(wǎng)絡(luò)運(yùn)營模式構(gòu)建了基于“航班環(huán)”時(shí)序網(wǎng)絡(luò)的機(jī)隊(duì)規(guī)劃數(shù)學(xué)模型,并設(shè)計(jì)了基于有向路徑隨機(jī)分解的模擬退火算法。算例結(jié)果表明,算法具有求解精度高、且速度快的特點(diǎn)。然后,將“航班環(huán)”時(shí)序網(wǎng)絡(luò)推廣至“航班串”時(shí)空網(wǎng)絡(luò),構(gòu)建基于時(shí)空網(wǎng)絡(luò)的機(jī)隊(duì)規(guī)劃隨機(jī)優(yōu)化數(shù)學(xué)模型,并設(shè)計(jì)了基于情景匯聚的兩階段算法。算例結(jié)果表明,在不確定需求下算法能夠體現(xiàn)出更好的效益優(yōu)勢。最后,將旅客收益網(wǎng)絡(luò)優(yōu)化模型合并入基于航班時(shí)空網(wǎng)絡(luò)的機(jī)隊(duì)規(guī)劃隨機(jī)優(yōu)化模型之中,利用上述兩階段算法進(jìn)行了求解,算例結(jié)果表明該類收益增強(qiáng)型機(jī)隊(duì)規(guī)劃模型與算法能夠更好的適用于樞紐輪輻式航線網(wǎng)絡(luò)運(yùn)營模式。針對基于航班機(jī)型分配微觀機(jī)隊(duì)規(guī)劃法無法準(zhǔn)確模擬航空公司未來航班計(jì)劃的缺陷,本文研究了基于航線運(yùn)力分配的微觀機(jī)隊(duì)規(guī)劃法。首先,在綜合考慮航線最大飛行頻次限制、機(jī)隊(duì)可用飛行時(shí)間限制,以及航線供需平衡限制等因素的基礎(chǔ)上,構(gòu)建基于隨機(jī)需求下以機(jī)隊(duì)運(yùn)營利潤最大化為目標(biāo)的不確定機(jī)隊(duì)規(guī)劃數(shù)學(xué)模型,通過產(chǎn)生期望收益非線性函數(shù)的近似線性函數(shù)后,將旅客期望收益網(wǎng)絡(luò)優(yōu)化模型從不確定機(jī)隊(duì)規(guī)劃數(shù)學(xué)模型中分離,并設(shè)計(jì)了兩個(gè)子模型迭代求解的算法。采用航空公司實(shí)際數(shù)據(jù)對模型與算法進(jìn)行測試,通過與遺傳算法計(jì)算結(jié)果進(jìn)行比較,說明該分解算法的優(yōu)勢。在此基礎(chǔ)上針對樞紐網(wǎng)絡(luò)運(yùn)營模式,將旅客收益網(wǎng)絡(luò)優(yōu)化模型并入該機(jī)隊(duì)規(guī)劃數(shù)學(xué)模型之中,利用上述分解算法再次進(jìn)行求解,并采用算例驗(yàn)證該類機(jī)隊(duì)規(guī)劃模型在樞紐輪輻式航線網(wǎng)絡(luò)運(yùn)營模式下進(jìn)行機(jī)隊(duì)規(guī)劃決策的優(yōu)勢。針對現(xiàn)有基于航線運(yùn)力分配的微觀機(jī)隊(duì)規(guī)劃法無法準(zhǔn)確反映旅客需求波動動態(tài)性以及微觀機(jī)隊(duì)規(guī)劃環(huán)境非壟斷性的問題,本文提出了基于離散時(shí)間航線運(yùn)力分配的機(jī)隊(duì)規(guī)劃模型,并設(shè)計(jì)了求解該模型的拉格朗日松弛解法。算例結(jié)果表明,該方法比基于航班機(jī)型分配機(jī)隊(duì)規(guī)劃法更加穩(wěn)定、比基于航線運(yùn)力分配機(jī)隊(duì)規(guī)劃法更能反映出旅客需求隨時(shí)間動態(tài)波動過程中所需機(jī)隊(duì)運(yùn)力的差異性;另一方面,本文在現(xiàn)有基于航線運(yùn)力分配的機(jī)隊(duì)規(guī)劃模型中考慮了競爭航空公司航線運(yùn)力分配方案對于本航空公司的影響,構(gòu)建了多航空公司競爭型機(jī)隊(duì)規(guī)劃數(shù)學(xué)模型,并基于均衡最優(yōu)理論設(shè)計(jì)了啟發(fā)式算法進(jìn)行求解。算例結(jié)果表明,算法能夠獲取機(jī)隊(duì)規(guī)劃均衡解,且通過Monte Carlo模擬法驗(yàn)證了該競爭型微觀機(jī)隊(duì)規(guī)劃法的優(yōu)勢。
[Abstract]:The fleet is the carrier for the airline to carry out the transportation, and the fleet planning is one of the important strategic planning contents of the airline. It is the key strategic decision to determine the future life and death of the airline. It is also the prerequisite for other decision making of the airline management, such as flight plans, aircraft scheduling, and revenue management. The good or bad will fundamentally affect the efficiency of the future transportation and production of the airline. Therefore, on the basis of meeting the future operating production environment of the airline (airline network structure, flight plan, demand and fare level, etc.), the scale and structure characteristics of aircraft fleet are studied, the structure of transport products is optimized for the airlines and the transport students are improved. The production benefit has important practical significance. In view of the defect that the macro fleet planning method can not accurately reflect the technical and economic performance characteristics of the flight model allocation, first, this paper constructs a fleet planning mathematical model based on the "flight loop" time series network for the single base line network operation mode, and designs a directed path based on the directed path. The simulated annealing algorithm of random decomposition shows that the algorithm has the characteristics of high accuracy and fast speed. Then, the "flight loop" time series network is popularized to the "flight string" space-time network, and the stochastic optimization mathematical model of fleet planning based on space-time network is constructed, and the two stage algorithm based on scene convergence is designed. The results show that the algorithm can show better benefit advantage under the uncertain demand. Finally, the passenger revenue network optimization model is incorporated into the stochastic optimization model of fleet planning based on flight space-time network, and the two stage algorithm is used to solve the problem. The results show that the model and algorithm of this type of revenue enhancement fleet planning and algorithm can be obtained. In this paper, the micro fleet planning method based on the distribution of airline force is studied in this paper. Firstly, the fleet can be used for the maximum flight frequency limitation, and the fleet is available. On the basis of the limitation of flight time and the balance of supply and demand, a mathematical model of uncertain fleet planning based on the maximum profit of fleet operation is built on the basis of random demand. By producing the approximate linear function of the expected return nonlinear function, the model of the passenger expected return network is never determined. The algorithm is separated from the mathematical model and the algorithm of two sub models is designed. The model and the algorithm are tested with the actual data of the airline. By comparing with the results of the genetic algorithm, the advantages of the decomposition algorithm are illustrated. The team planning mathematical model, using the above decomposition algorithm to solve the problem again, and using an example to verify the advantage of this kind of fleet planning model in the hub spoke airline network operation mode. In view of the existing micro machine team planning method based on the distribution of route capacity, it can not accurately reflect the fluctuation of passenger demand. In this paper, a fleet planning model based on the distribution of discrete time route is proposed, and a Lagrange relaxation method for solving the model is designed. The results show that the method is more stable than the flight model distribution unit planning method, which is based on the distribution of route capacity. The fleet planning method can reflect the difference of the fleet capacity required for the dynamic fluctuation of the passenger demand with time. On the other hand, this paper takes into account the influence of the competitive airline route allocation scheme to the airline in the existing fleet planning model based on the distribution of airline power, and constructs a multi airline competitive machine. The team plans the mathematical model and designs a heuristic algorithm based on the equilibrium optimal theory. The results show that the algorithm can obtain the equilibrium solution of the fleet planning, and the advantage of the competitive micro fleet planning method is verified by the Monte Carlo simulation method.
【學(xué)位授予單位】：南京航空航天大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：V352;F560.6

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