【摘要】：傳統(tǒng)的車輛路徑問題(Vehicle Routing Problem, VRP)大多從經(jīng)濟(jì)效益視角考慮,研究目標(biāo)為最小化旅行距離或物流成本,而從環(huán)境效益的角度考慮運(yùn)輸對環(huán)境影響的相關(guān)研究還比較少。物流和交通運(yùn)輸已成為碳排放的主要來源之一,是落實(shí)節(jié)能減排的重要領(lǐng)域。實(shí)際運(yùn)輸企業(yè)大多擁有多個車場,同時考慮到車場車輛數(shù)、車輛載重、車輛工作時間以及客戶時間窗等實(shí)際約束,本文研究了一類新的車輛路徑問題——帶時間窗的多車場低碳車輛路徑問題(Multi-Depot Low-Carbon Vehicle Routing Problem with Time Windows, MDLCVRPTW).該問題將研究目標(biāo)轉(zhuǎn)移到環(huán)境效益中去,是對傳統(tǒng)的帶時間窗的多車場車輛路徑問題(Multi-Depot Vehicle Routing Problem with Time Windows, MDVRPTW)的擴(kuò)展,通過合理安排車輛運(yùn)輸路線,以期減少能耗和碳排放。基于歷史統(tǒng)計數(shù)據(jù)和已有研究成果,本文首先建立了車輛能耗和碳排放量的宏觀計量模型,模型綜合考慮了距離和重量這兩個影響碳排放量的關(guān)鍵因素；在此基礎(chǔ)上建立了MDLCVRPTW問題的數(shù)學(xué)優(yōu)化模型,目標(biāo)函數(shù)為最小化碳排放量。由于MDLCVRPTW屬于NP-hard問題,本文設(shè)計了帶適應(yīng)性變異的混合遺傳算法來求解該問題：設(shè)計了基于輪盤賭的初始解構(gòu)造方法,采用了父代參與競爭的錦標(biāo)賽選擇機(jī)制,然后改進(jìn)了Ox交叉算子,設(shè)計了基于適應(yīng)性鄰域搜索的變異操作,并通過種群管理保持種群多樣性。為了評估算法的有效性,首先采用Cordeau的MDVRPTW標(biāo)準(zhǔn)測試算例數(shù)據(jù),求解了MDVRPTW問題,從解的質(zhì)量、算法穩(wěn)定性以及收斂時間三方面表明了本文算法的有效性。然后將MDLCVRPTW模型計算結(jié)果與MDVRPTW模型計算結(jié)果相比較,結(jié)果表明,前者較后者旅行距離平均增加1.65%,但碳排放量平均降低0.90%,由此表明在小批量多批次貨物配送中,適當(dāng)增加旅行距離能減少碳排放量,同時也表明僅考慮旅行距離不利于節(jié)能減排。最后將本文的模型與算法應(yīng)用于蘇果社區(qū)店的實(shí)際配送作業(yè)中,給出了合理的運(yùn)輸路線安排。本文拓展了已有車輛路徑問題的研究,能夠?yàn)槠髽I(yè)實(shí)施低碳運(yùn)輸提供重要的決策支持。
[Abstract]:The traditional vehicle routing problem (Vehicle Routing Problem, VRP) is mostly considered from the perspective of economic benefits. The research goal is to minimize travel distance or logistics cost, but there are few researches on the environmental impact of transport from the perspective of environmental benefits. Logistics and transportation have become one of the main sources of carbon emissions, which is an important field of energy saving and emission reduction. Most of the actual transportation enterprises have more than one vehicle yard, considering the actual constraints such as the number of vehicles in the yard, vehicle load, vehicle working time and customer time window, etc. In this paper, we study a new class of vehicle routing problem The low carbon vehicle routing problem with time windows (Multi-Depot Low-Carbon Vehicle Routing Problem with Time Windows, MDLCVRPTW).) This problem transfers the research target to the environmental benefit. It extends the traditional vehicle routing problem with time window (Multi-Depot Vehicle Routing Problem with Time Windows, MDVRPTW) and reasonably arranges the vehicle transportation route. To reduce energy consumption and carbon emissions. Based on the historical statistical data and the existing research results, this paper first established the vehicle energy consumption and carbon emissions macro measurement model, the model considered the distance and weight of the two key factors affecting carbon emissions; On this basis, the mathematical optimization model of MDLCVRPTW problem is established. The objective function is to minimize carbon emissions. As MDLCVRPTW belongs to the NP-hard problem, a hybrid genetic algorithm with adaptive mutation is designed to solve the problem. An initial solution construction method based on roulette is designed. Then the Ox crossover operator is improved and the mutation operation based on adaptive neighborhood search is designed and population diversity is maintained through population management. In order to evaluate the validity of the algorithm, the MDVRPTW problem is solved by using the MDVRPTW standard test data of Cordeau. The effectiveness of the proposed algorithm is demonstrated from three aspects: the quality of the solution, the stability of the algorithm and the convergence time. The results of MDLCVRPTW model are compared with those of MDVRPTW model. The results show that the former increases the travel distance by 1.65 on average, but the carbon emission decreases by 0.90 on average. A proper increase in travel distance can reduce carbon emissions, but it also shows that only considering travel distance is not conducive to energy saving and emission reduction. Finally, the model and algorithm of this paper are applied to the practical distribution of the community store of Suguo, and the reasonable transportation route is given. In this paper, the existing research on vehicle routing problem is extended, which can provide important decision support for enterprises to implement low-carbon transportation.
【學(xué)位授予單位】：南京農(nóng)業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：F259.22;U492.22

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