本文關(guān)鍵詞： VRP模型 兩階段算法 行程時(shí)間預(yù)測(cè) 交通流誘導(dǎo) 模擬退火算法　出處：《大連海事大學(xué)》2015年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：在現(xiàn)如今經(jīng)濟(jì)高速發(fā)展的社會(huì),物流已經(jīng)成為了社會(huì)經(jīng)濟(jì)高速騰飛的重要基石。在我國(guó)第十二個(gè)五年規(guī)劃中,將物流行業(yè)的發(fā)展提上了國(guó)家戰(zhàn)略層面,這個(gè)政策說(shuō)明了物流行業(yè)的春天來(lái)了�？v觀物流行業(yè)發(fā)展至今,困擾著無(wú)數(shù)物流人的兩個(gè)大的問(wèn)題,也是物流費(fèi)用產(chǎn)生的核心源頭,即運(yùn)輸費(fèi)用和倉(cāng)儲(chǔ)費(fèi)用。根據(jù)國(guó)際上相關(guān)權(quán)威機(jī)構(gòu)的調(diào)查數(shù)據(jù)顯示,中國(guó)的物流行業(yè)的運(yùn)輸費(fèi)用占據(jù)了物流的總費(fèi)用的50%以上,占據(jù)國(guó)民生產(chǎn)總值的20%～300%。這個(gè)巨大的數(shù)字比例意味著每年都有一筆天文數(shù)字的資金在浪費(fèi)掉,所以對(duì)運(yùn)輸費(fèi)用的研究就非常的有必要。國(guó)內(nèi)外學(xué)者對(duì)物流配送過(guò)程中的車(chē)輛路徑問(wèn)題都做出了非常大、非常多、非常廣的研究和討論,也得出了很多非常優(yōu)秀的結(jié)果。但是,一般確定客戶(hù)及配送中心之間的車(chē)輛行程時(shí)間,主要是通過(guò)獲取客戶(hù)及配送中心的地理位置坐標(biāo),利用坐標(biāo)兩點(diǎn)間直線距離公式和車(chē)輛平均行駛速度之商計(jì)算,并沒(méi)有考慮到現(xiàn)實(shí)中復(fù)雜的交通情況,當(dāng)?shù)贸龅能?chē)輛路徑方案遇到交通擁擠等復(fù)雜情況時(shí),就不能很好的按照方案得到預(yù)期的結(jié)果。本文在詳細(xì)研究帶時(shí)間窗的多車(chē)型車(chē)輛路徑問(wèn)題的基礎(chǔ)上,給出了一種能夠求解出貼近現(xiàn)實(shí)交通情況的客戶(hù)及配送中心之間車(chē)輛行程時(shí)間的預(yù)測(cè)方法,即通過(guò)交通流誘導(dǎo)技術(shù)中駕駛員行為特性、行程時(shí)間預(yù)測(cè)技術(shù)以及Dijkstra最短路算法,利用調(diào)查獲取的平均交通流量數(shù)據(jù),預(yù)測(cè)并求出客戶(hù)及配送中心之間的車(chē)輛行程時(shí)間,為后續(xù)車(chē)輛路徑方案優(yōu)化提供車(chē)輛行程時(shí)間數(shù)據(jù)支持。在求解模型的算法設(shè)計(jì)上,借鑒兩階段算法理念,結(jié)合駕駛員行為特性、行程時(shí)間預(yù)測(cè)、Dijkstra最短路算法和模擬退火算法,求解出符合要求的配送車(chē)輛路徑方案。本文具體內(nèi)容包括：首先,介紹了論文題目的背景以及國(guó)內(nèi)外研究現(xiàn)狀和選題的意義和目的,闡述了本文的創(chuàng)新點(diǎn)。其次,對(duì)車(chē)輛路徑問(wèn)題以及交通流誘導(dǎo)理論進(jìn)行了詳細(xì)的闡述。最后,建立了帶時(shí)間窗的多車(chē)型車(chē)輛路徑問(wèn)題模型,借鑒兩階段算法理念設(shè)計(jì)求解算法,并利用計(jì)算機(jī)仿真軟件進(jìn)行編程,通過(guò)案例應(yīng)用得出符合要求的車(chē)輛路徑方案。
[Abstract]:In today's society with rapid economic development, logistics has become an important cornerstone for the rapid development of social economy. In the 12th five-year plan of our country, the development of logistics industry has been promoted to the national strategic level. This policy shows that the spring of the logistics industry has come. Looking at the development of the logistics industry so far, there are two major problems puzzling countless logistics people, and it is also the core source of the production of logistics costs. That is, transportation costs and warehousing costs. According to the survey data of relevant international authorities, the transportation costs of China's logistics industry account for more than 50% of the total logistics costs. This huge proportion of GDP means that an astronomical amount of money is wasted every year. So the research on transportation cost is very necessary. Scholars at home and abroad have made a very large, many, very extensive research and discussion on the vehicle routing problem in the process of logistics distribution. However, they have also got a lot of excellent results. In general, the vehicle travel time between the customer and the distribution center is determined, mainly by obtaining the geographical coordinates of the customer and the distribution center, using the straight line distance formula between the two points of coordinates and the quotient of the average vehicle speed. It does not take into account the complex traffic situation in reality. When the vehicle routing scheme is met with complex situations such as traffic congestion, We can not get the expected results according to the plan. Based on the detailed study of the multi-model vehicle routing problem with time window, In this paper, a prediction method of vehicle travel time between customers and distribution centers, which is close to the actual traffic situation, is presented, which includes driver behavior characteristic, travel time prediction technology and Dijkstra shortest path algorithm in traffic flow guidance technology. Using the average traffic flow data obtained from the investigation, the vehicle travel time between the customer and the distribution center is predicted and calculated, which provides the vehicle travel time data support for the subsequent vehicle routing scheme optimization. Based on the two-stage algorithm, combined with driver behavior, travel time prediction Dijkstra shortest path algorithm and simulated annealing algorithm, the vehicle routing scheme that meets the requirements is solved. The specific contents of this paper are as follows: first, This paper introduces the background of the topic, the significance and purpose of the research at home and abroad, and expounds the innovation of this paper. Secondly, the vehicle routing problem and the theory of traffic flow guidance are elaborated in detail. The model of multi-vehicle vehicle routing problem with time window is established, and the solution algorithm is designed by using two-stage algorithm, and the vehicle routing scheme according to the requirements is obtained by using the computer simulation software for programming.
【學(xué)位授予單位】：大連海事大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：F259.2

【參考文獻(xiàn)】

相關(guān)期刊論文 前8條

1 方金城;張岐山;;物流配送車(chē)輛路徑問(wèn)題(VRP)算法綜述[J];沈陽(yáng)工程學(xué)院學(xué)報(bào)(自然科學(xué)版);2006年04期

2 徐天東;孫立軍;郝媛;杜豫川;;不同交通信息下網(wǎng)絡(luò)交通動(dòng)態(tài)路徑選擇行為[J];同濟(jì)大學(xué)學(xué)報(bào)(自然科學(xué)版);2009年08期

3 呂鵬舉;原杰;呂菁華;;基于模擬退火算法的全國(guó)最優(yōu)旅行方案[J];現(xiàn)代電子技術(shù);2011年02期

4 鄒彤,李寧,孫德寶;不確定車(chē)輛數(shù)的有時(shí)間窗車(chē)輛路徑問(wèn)題的遺傳算法[J];系統(tǒng)工程理論與實(shí)踐;2004年06期

5 馬建華;房勇;袁杰;;多車(chē)場(chǎng)多車(chē)型最快完成車(chē)輛路徑問(wèn)題的變異蟻群算法[J];系統(tǒng)工程理論與實(shí)踐;2011年08期

6 鐘石泉;賀國(guó)光;;多車(chē)場(chǎng)有時(shí)間窗的多車(chē)型車(chē)輛調(diào)度及其禁忌算法研究[J];運(yùn)籌學(xué)學(xué)報(bào);2005年04期

7 陶胤強(qiáng);�；菝�;;帶時(shí)間窗的多車(chē)型多費(fèi)用車(chē)輛路徑問(wèn)題的模型和算法[J];交通運(yùn)輸系統(tǒng)工程與信息;2008年01期

8 郎茂祥;;動(dòng)態(tài)車(chē)輛配送優(yōu)化調(diào)度問(wèn)題的兩階段算法[J];交通運(yùn)輸系統(tǒng)工程與信息;2009年04期

相關(guān)碩士學(xué)位論文 前1條

1 李劍文;帶時(shí)間窗車(chē)輛路徑問(wèn)題的優(yōu)化控制研究[D];哈爾濱工程大學(xué);2007年

，

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