本文關(guān)鍵詞： 燃油消耗 車輛路徑問題 貪婪算法 蟻群算法 物流配送　出處：《青島大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著世界經(jīng)濟(jì)全球化和一體化的發(fā)展,全球已進(jìn)入信息化時(shí)代,然而工業(yè)社會給人們的生活環(huán)境帶來的危害已經(jīng)初露端倪,環(huán)境和氣候問題嚴(yán)重威脅著地球上生物的生存和繁衍。特別是在全球電子商務(wù)迅猛發(fā)展的大背景下,物流行業(yè)倍受社會各階層的重視,同時(shí)對物流配送提出了更高的要求,更加追求服務(wù)的質(zhì)量,要求快速、準(zhǔn)確、訂單跟蹤時(shí)時(shí)更新等,進(jìn)而推動(dòng)了物流的發(fā)展。針對物流配送業(yè)的油耗成本問題,以最小化燃油消耗為目標(biāo),在分析和比較了現(xiàn)有燃油消耗模型的基礎(chǔ)上,以最新汽車?yán)碚撃芎哪Ｐ蜑榛A(chǔ),通過分析和簡化部分車輛行駛參數(shù),建立了相應(yīng)的低燃油車輛路徑問題模型(Low Fuel Capacitated Vehicle Routing Problem,LF-CVRP)。首先,考慮到蟻群算法在VRP領(lǐng)域中具有的各項(xiàng)優(yōu)點(diǎn),設(shè)計(jì)了以最小化油耗為目標(biāo)的蟻群算法(Ant Colony Optimization-LF-CVRP,ACO-LF-CVRP),并選用27個(gè)具有能力約束的標(biāo)準(zhǔn)車輛路徑問題算例進(jìn)行仿真;其次,考慮到雖然蟻群算法計(jì)算結(jié)果比較準(zhǔn)確,但是存在計(jì)算時(shí)間時(shí)間過長的缺點(diǎn),不適于現(xiàn)代信息實(shí)時(shí)更新的要求,設(shè)計(jì)了以最小化油耗為貪心規(guī)則的貪婪算法(Greedy Optimization Algorithm,GOA-LF-CVRP),并與ACO-LF-CVRP仿真結(jié)果的計(jì)算速度、總距離、總油耗、使用車輛數(shù)等方面對GOA-LF-CVRP和ACO-LF-CVRP進(jìn)行對比分析;最后,綜合改進(jìn)與分析了油耗模型及貪婪算法。說明LF-CVRP模型及GOA-LF-CVRP算法組成的求解策略,可以快捷、有效地計(jì)算油耗及配送路線,滿足現(xiàn)代物流配送路線實(shí)時(shí)更新的要求,為物流配送業(yè)提供綠色的決策方案。
[Abstract]:With the development of globalization and integration of the world economy, the world has entered the information age. However, the harm brought by the industrial society to people's living environment has already begun to emerge. Environment and climate problems seriously threaten the survival and reproduction of organisms on the earth, especially in the context of the rapid development of global electronic commerce, the logistics industry has been attached great importance to by all levels of society. At the same time, the logistics delivery put forward higher requirements, more pursuit of service quality, demand for speed, accuracy, order tracking and updating, and so on, thus promoting the development of logistics. In order to minimize fuel consumption, based on the analysis and comparison of existing fuel consumption models, and based on the latest vehicle theoretical energy consumption model, some vehicle driving parameters are analyzed and simplified. The low Fuel Capacitated Vehicle Routing Problem is established. First of all, considering the advantages of ant colony algorithm in the field of VRP. Ant Colony Optimization-LF-CVRP (ACO-LF-CVRP) is designed to minimize fuel consumption. And 27 examples of standard vehicle routing problem with capacity constraints are selected for simulation. Secondly, considering that the result of ant colony algorithm is accurate, but the computation time is too long, it is not suitable for the requirement of real-time updating of modern information. A greedy Optimization algorithm named greedy Optimization algorithm (GOA-LF-CVRP) is designed. The GOA-LF-CVRP and ACO-LF-CVRP are compared with the results of ACO-LF-CVRP simulation in terms of calculation speed, total distance, total fuel consumption and the number of vehicles used. Finally, the oil consumption model and greedy algorithm are comprehensively improved and analyzed. It is shown that the solution strategy composed of LF-CVRP model and GOA-LF-CVRP algorithm is quick. It can effectively calculate fuel consumption and distribution route, meet the requirement of real-time updating of modern logistics distribution route, and provide a green decision scheme for logistics distribution industry.
【學(xué)位授予單位】：青島大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F252;TP18

【參考文獻(xiàn)】

相關(guān)期刊論文 前8條

1 葛顯龍;許茂增;王偉鑫;;基于聯(lián)合配送的城市物流配送路徑優(yōu)化[J];控制與決策;2016年03期

2 饒衛(wèi)振;金淳;王新華;劉鋒;;考慮道路坡度因素的低碳VRP問題模型與求解策略[J];系統(tǒng)工程理論與實(shí)踐;2014年08期

3 于雷;王東;;模擬并行蟻群算法的綠色物流最小油耗VRPSDP[J];計(jì)算機(jī)系統(tǒng)應(yīng)用;2013年07期

4 葛顯龍;王旭;邢樂斌;;動(dòng)態(tài)需求的多車型車輛調(diào)度問題及云遺傳算法[J];系統(tǒng)工程學(xué)報(bào);2012年06期

5 杜玲玲;;混合超啟發(fā)式法求解大規(guī)模VRP的優(yōu)化研究[J];華東交通大學(xué)學(xué)報(bào);2011年01期

6 鄧愛民;毛超;周彥霆;;帶軟時(shí)間窗的集配貨一體化VRP改進(jìn)模擬退火算法優(yōu)化研究[J];系統(tǒng)工程理論與實(shí)踐;2009年05期

7 賀新;王岐東;葉身斌;;汽車油耗的測量與計(jì)算研究及其進(jìn)展[J];北京工商大學(xué)學(xué)報(bào)(自然科學(xué)版);2007年01期

8 章后忠,潘玉利,程珊珊,程正亮;建立四類代表車型的理論油耗模型[J];華東公路;2002年06期

相關(guān)碩士學(xué)位論文 前2條

1 于雷;模擬并行蟻群算法的綠色物流最小油耗配送路徑優(yōu)化[D];上海交通大學(xué);2013年

2 邱俊熒;基于帶Path-Relinking的GRASP的超啟發(fā)式方法[D];大連理工大學(xué);2011年

，

本文編號：1445380