本文選題：車(chē)輛路徑問(wèn)題 + 時(shí)間窗　； 參考：《北京交通大學(xué)》2015年碩士論文

【摘要】：近年來(lái),物流業(yè)在社會(huì)經(jīng)濟(jì)發(fā)展中發(fā)揮著越來(lái)越重要的作用,同時(shí)也帶來(lái)了嚴(yán)重的能源和環(huán)境問(wèn)題。合理規(guī)劃物流車(chē)輛的配送路徑被視為降低物流企業(yè)運(yùn)營(yíng)成本、緩解能源短缺和環(huán)境污染的重要途徑之一。本文以物流車(chē)輛節(jié)能配送路徑優(yōu)化問(wèn)題為研究對(duì)象,綜合考慮配送時(shí)間窗要求、車(chē)輛配載約束、載重和速度對(duì)車(chē)輛能耗因子的影響,構(gòu)建整數(shù)規(guī)劃模型,并利用改進(jìn)的蟻群算法進(jìn)行求解,以最少的能源消耗實(shí)現(xiàn)節(jié)能配送。本文的主要研究?jī)?nèi)容如下： 首先,按照不同分類(lèi)標(biāo)準(zhǔn)將車(chē)輛路徑優(yōu)化問(wèn)題進(jìn)行分類(lèi),并對(duì)常用算法的特點(diǎn)進(jìn)行分析。 其次,考慮貨車(chē)受車(chē)廂尺寸和最大載重量的限制、車(chē)輛能耗因子受車(chē)速和貨車(chē)載重的影響,分別構(gòu)建三維裝箱數(shù)學(xué)模型和車(chē)輛綜合油耗計(jì)算模型。進(jìn)而,以三維裝箱模型為約束條件,以配送方案油耗最低為優(yōu)化目標(biāo),構(gòu)建考慮三維裝箱和時(shí)間窗約束的時(shí)間依賴型節(jié)能配送路徑優(yōu)化問(wèn)題數(shù)學(xué)模型。 再次,針對(duì)以上模型,對(duì)蟻群算法進(jìn)行了如下改進(jìn)：第一,在考慮客戶點(diǎn)周邊路網(wǎng)條件、貨物需求特征的基礎(chǔ)上,提出可將車(chē)輛臨時(shí)�？吭诘缆妨硪粋�(cè)的備選�？奎c(diǎn)處,以減少因配送車(chē)輛只能停靠在客戶所在道路一側(cè)可能造成的迂回運(yùn)輸,進(jìn)而減少能耗；第二,利用模擬退火算法求解三維裝箱約束模型,在滿足車(chē)輛載重約束的同時(shí),也滿足貨物不相互重疊、先卸后裝等約束；第三,以油耗為標(biāo)準(zhǔn)更新蟻群信息素濃度,達(dá)到逐步優(yōu)化配送方案、降低油耗的目的；第四,基于初步優(yōu)化結(jié)果,考慮車(chē)速對(duì)車(chē)輛能耗因子的影響,結(jié)合路網(wǎng)動(dòng)態(tài)交通信息,通過(guò)調(diào)整配送車(chē)輛從配送中心及各客戶點(diǎn)的出發(fā)時(shí)刻,實(shí)現(xiàn)對(duì)配送方案總油耗的進(jìn)一步優(yōu)化。 最后,利用北京市實(shí)際路網(wǎng)和動(dòng)態(tài)交通數(shù)據(jù),構(gòu)造6個(gè)不同客戶點(diǎn)數(shù)量規(guī)模的配送案例,并采用以上所提出的數(shù)學(xué)模型和蟻群算法進(jìn)行求解。計(jì)算結(jié)果表明,相對(duì)于傳統(tǒng)方法,本文所提出的優(yōu)化方法可使物流配送油耗量最多可降低25.52%。
[Abstract]:In recent years, the logistics industry plays a more and more important role in the social and economic development, but also brings serious energy and environmental problems. The rational planning of the distribution path of logistics vehicles is regarded as one of the important ways to reduce the operating cost of logistics enterprises and alleviate the energy shortage and environmental pollution. In this paper, we take the optimization of energy saving distribution path of logistics vehicles as the research object, consider the requirements of distribution time window, the influence of vehicle loading constraints, load and speed on vehicle energy consumption factors, and construct an integer programming model. The improved ant colony algorithm is used to solve the problem and energy saving distribution is realized with the least energy consumption. The main contents of this paper are as follows: Firstly, the vehicle routing optimization problem is classified according to different classification criteria, and the characteristics of common algorithms are analyzed. Secondly, considering the limitation of truck size and maximum load, and the influence of vehicle energy consumption factor on vehicle speed and truck load, a three-dimensional packing mathematical model and a vehicle comprehensive fuel consumption calculation model are constructed respectively. Furthermore, taking the three-dimensional packing model as the constraint condition and the lowest fuel consumption of the distribution scheme as the optimization objective, the mathematical model of time-dependent energy saving distribution path optimization problem considering three-dimensional packing and time window constraints is constructed. Thirdly, according to the above model, the ant colony algorithm is improved as follows: first, considering the network conditions around the customer points and the characteristics of the cargo demand, the paper proposes that the vehicles can be temporarily parked at alternative stops on the other side of the road. In order to reduce the circuitous transportation caused by the distribution vehicles only parked on one side of the road where the customer is, and then reduce the energy consumption. Secondly, the simulated annealing algorithm is used to solve the three-dimensional packing constraint model, which satisfies the vehicle load constraints at the same time. It also meets the constraints of goods not overlapping, first unloaded and then loaded; third, the ant colony pheromone concentration is updated according to fuel consumption to achieve the purpose of gradually optimizing the distribution scheme and reducing fuel consumption; fourth, based on the preliminary optimization results, Considering the influence of vehicle speed on vehicle energy consumption factor, combined with the dynamic traffic information of road network, the total fuel consumption of distribution scheme can be further optimized by adjusting the departure time of distribution vehicle from distribution center and each customer point. Finally, based on the actual road network and dynamic traffic data in Beijing, six distribution cases with different number of customer points are constructed, and the above mathematical model and ant colony algorithm are used to solve the problem. The results show that compared with the traditional method, the optimization method proposed in this paper can reduce the fuel consumption of logistics distribution by 25.52%.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：U492.22

【參考文獻(xiàn)】

相關(guān)期刊論文 前7條

1 顧志康,李旭宏,徐家兵;一種改進(jìn)遺傳算法在物流配送車(chē)輛調(diào)度中的應(yīng)用研究[J];公路交通科技;2004年11期

2 ;2011年我國(guó)社會(huì)物流總額近160萬(wàn)億元[J];港口經(jīng)濟(jì);2012年03期

3 畢軍,付夢(mèng)印,張宇河;一種改進(jìn)的蟻群算法求解最短路徑問(wèn)題[J];計(jì)算機(jī)工程與應(yīng)用;2003年03期

4 張麗萍,柴躍廷,曹瑞;有時(shí)間窗車(chē)輛路徑問(wèn)題的改進(jìn)遺傳算法[J];計(jì)算機(jī)集成制造系統(tǒng)-CIMS;2002年06期

5 段征宇;楊東援;王上;;時(shí)間依賴型車(chē)輛路徑問(wèn)題的一種改進(jìn)蟻群算法[J];控制理論與應(yīng)用;2010年11期

6 劉志碩,申金升,柴躍廷;基于自適應(yīng)蟻群算法的車(chē)輛路徑問(wèn)題研究[J];控制與決策;2005年05期

7 黃瑞銘;;配送時(shí)間窗約束下車(chē)輛調(diào)度遺傳算法研究[J];物流科技;2011年04期

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本文編號(hào)：1983470