本文選題：城市公交線網(wǎng)　切入點：變異PSO算法　出處：《蘭州交通大學(xué)》2014年碩士論文

【摘要】：隨著經(jīng)濟(jì)和社會的發(fā)展，在我國，城市公共交通的發(fā)展相對緩慢，交通堵塞越來越嚴(yán)重，給居民出行帶來不便，尤其是常規(guī)公交存在著線路布設(shè)的不合理，線路分布的不均衡、比較零散等問題，，不但降低了常規(guī)公交線網(wǎng)的運(yùn)營效率，而且嚴(yán)重影響了公交線網(wǎng)的服務(wù)水平。目前大多數(shù)城市采用不分層法實現(xiàn)常規(guī)公交線網(wǎng)的優(yōu)化布設(shè)，由于布設(shè)的線路分工不明確，銜接性差，缺乏整體性，甚至存在較多的交通盲區(qū)，因此，無法改善常規(guī)公交線網(wǎng)布設(shè)不合理的現(xiàn)狀�；谝陨瞎痪�網(wǎng)優(yōu)化所面臨的問題，采用分層法對公交線網(wǎng)進(jìn)行優(yōu)化有著現(xiàn)實和重要的意義。 本文主要將改進(jìn)后的PSO(Particle Swarm Optimization,粒子群優(yōu)化)算法與灰色預(yù)測法相結(jié)合，實現(xiàn)OD(Orgin-Destination,起點到終點)出行分布量的預(yù)測，在對公交線網(wǎng)分層優(yōu)越性分析的基礎(chǔ)上，建立公交線網(wǎng)的分層模型，并采用改進(jìn)后的PSO算法對各層求解，形成合理的公交線網(wǎng)。 首先，對連續(xù)和離散PSO算法進(jìn)行改進(jìn)。即針對PSO算法極易陷入局部最優(yōu)的缺點，基于動態(tài)指數(shù)改進(jìn)策略和遺傳變異的思想，從改變算法的慣性權(quán)重和加入變異算子兩個方面結(jié)合將算法改進(jìn)為變異PSO算法，并通過具體的測試函數(shù)，分析變異PSO算法與傳統(tǒng)改進(jìn)的PSO算法的收斂性能。通過測試證明變異PSO算法具有良好的收斂性。 其次，對公交線網(wǎng)采用分層法優(yōu)化的優(yōu)越性進(jìn)行分析，并以蘭州市的公交線網(wǎng)為研究對象，將變異PSO算法與灰色預(yù)測法相結(jié)合建立一種灰色變異粒子群組合預(yù)測模型，運(yùn)用此模型在MATLAB軟件中實現(xiàn)OD出行分布量的預(yù)測，通過與傳統(tǒng)的增長計數(shù)法和重力模型法預(yù)測的結(jié)果進(jìn)行比較，證明本文所建立的組合型預(yù)測模型的高精度性和適用性。 最后，本文采用隨機(jī)用戶平衡法實現(xiàn)OD客流量分配，在此基礎(chǔ)上實現(xiàn)主干線、次干線優(yōu)化模型的建立及各層優(yōu)化約束條件的確定；采用變異PSO算法對各層進(jìn)行求解，完成主干線、次干線的優(yōu)化布設(shè)；通過對優(yōu)化后線網(wǎng)的重要指標(biāo)計算分析，再次驗證變異PSO算法具有良好的收斂性和分層法優(yōu)化公交線網(wǎng)的優(yōu)越性。運(yùn)用分層優(yōu)化法優(yōu)化線網(wǎng)不僅能建立合理的公交線網(wǎng)，而且能提高公交線網(wǎng)的運(yùn)營效率和服務(wù)水平。
[Abstract]:Compared with other problems, it not only reduces the operation efficiency of conventional bus network, but also seriously affects the service level of bus network.At present, most cities adopt the method of non-stratification to optimize the layout of conventional public transport network. Because of the unclear division of labor, poor cohesion, lack of integrity and even more traffic blind areas, the layout of the lines is not clear.Can not improve the normal bus network layout unreasonable status quo.Based on the problems faced by the above bus network optimization, it is of practical and important significance to adopt the hierarchical method to optimize the bus network.Firstly, the continuous and discrete PSO algorithms are improved.Aiming at the disadvantage that PSO algorithm is easy to fall into local optimum, based on the idea of dynamic exponent improvement strategy and genetic mutation, the algorithm is improved to mutation PSO algorithm by changing the inertia weight of the algorithm and adding mutation operator.The convergence performance of the mutated PSO algorithm and the traditional improved PSO algorithm is analyzed by testing function.The test results show that the mutation PSO algorithm has good convergence.Secondly, this paper analyzes the advantages of the hierarchical optimization of the bus network, and takes the public transportation network in Lanzhou as the research object, and combines the mutation PSO algorithm with the grey prediction method to establish a kind of grey variation particle swarm combination prediction model.This model is used to predict OD travel distribution in MATLAB software. By comparing with the results of traditional growth counting method and gravity model method, the high accuracy and applicability of the combined forecasting model are proved.Finally, this paper uses random user balance method to realize OD passenger flow distribution, on the basis of which the main trunk line, secondary trunk line optimization model and optimization constraints of each layer are established, and the variant PSO algorithm is used to solve each layer.Through the calculation and analysis of the important indexes of the optimized line network, it is verified that the mutated PSO algorithm has good convergence and the superiority of the hierarchical method to optimize the bus network.The hierarchical optimization method can not only establish a reasonable bus network, but also improve the operation efficiency and service level of the bus network.
【學(xué)位授予單位】：蘭州交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：U491.17

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