本文關(guān)鍵詞：考慮碳排放因素的車輛路徑優(yōu)化建模研究　出處：《重慶交通大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 碳排放 車輛路徑問題 時(shí)間窗 混合遺傳算法

【摘要】：伴隨著全球經(jīng)濟(jì)一體化的深入,中國經(jīng)濟(jì)迎來快速發(fā)展的春天,與此同時(shí)其能源消耗也呈現(xiàn)日益增長的趨勢。其中,中國碳排放量從1980年的14.5億噸急劇增長到2013年的100億噸而位居全球第一,占據(jù)全球總排放量的29%。研究顯示,物流配送已經(jīng)成為全球碳排放的重要來源之一,其產(chǎn)生的溫室氣體占據(jù)全部份額的14%。相比美國12%和歐盟11%的份額,我國物流業(yè)溫室氣體排放占據(jù)總溫室氣體高達(dá)19%。因此,研究考慮碳排放因素的車輛路徑問題以降低我國物流運(yùn)輸行業(yè)碳排放變得至關(guān)重要。本篇文章研究的重點(diǎn)是考慮碳排放因素下車輛路徑模型和優(yōu)化方法,具體的研究內(nèi)容和創(chuàng)新之處如下所示:首先,針對計(jì)算貨運(yùn)車輛的碳排放量需要,比較分析碳排放的計(jì)算模型;考慮到計(jì)算的簡便性和可操作性,適當(dāng)簡化處理計(jì)算模型。針對物流企業(yè)可能參與到碳交易中,同時(shí)面臨碳排放權(quán)的買賣操作和碳懲罰的情況,研究適用于物流配送企業(yè)的帶碳懲罰的碳交易機(jī)制和模型,此外還分析碳交易機(jī)制的波動(dòng)對物流配送構(gòu)成的影響。其次,針對研究的車輛路徑問題,建立帶碳排放和時(shí)間窗的多目標(biāo)整數(shù)規(guī)劃模型;考慮到求解模型的復(fù)雜性,結(jié)合聚類分析方法、掃描算法和兩邊逐次修正算法來設(shè)計(jì)新的混合遺傳算法。通過聚類分析技術(shù)可以根據(jù)客戶的離散情況進(jìn)行分類,減少算法的無效搜索;其次,采用掃描算法可以對同類客戶進(jìn)行快速排序,避免產(chǎn)生適應(yīng)度太差的個(gè)體;最后,使用兩邊逐次修正算法可以對優(yōu)化后的子路徑進(jìn)行再度優(yōu)化,從而提高算法的求解性能。為驗(yàn)證設(shè)計(jì)算法的性能,采用標(biāo)準(zhǔn)算例對算法的有效性和可靠性進(jìn)行測試。最后,結(jié)合重慶天友乳業(yè)股份有限公司的物流配送案例,驗(yàn)證本文建立的考慮碳排放因素的車輛路徑模型和設(shè)計(jì)的混合遺傳算法。同時(shí)根據(jù)本案例,分別討論在單車型、混合車型、不同比例下碳交易量、不同碳交易價(jià)格和碳懲罰價(jià)格對物流配送的影響,此外還對比其他啟發(fā)式算法驗(yàn)證設(shè)計(jì)的混合遺傳算法實(shí)用性和穩(wěn)定性。本文的主要貢獻(xiàn)是,第一,總結(jié)物流配送車輛的碳排放計(jì)算模型,確定適合本文的碳排放計(jì)算方式,其次建立碳交易機(jī)制和討論對物流配送的影響。第二,針對問題建立多目標(biāo)帶碳排放和時(shí)間窗的車輛路徑整數(shù)規(guī)劃模型,針對求解模型的復(fù)雜性設(shè)計(jì)出混合遺傳算法,同時(shí)采用算例驗(yàn)證了模型和算法。第三,通過案例進(jìn)一步驗(yàn)證構(gòu)建的考慮碳排放的車輛路徑模型和求解算法。
[Abstract]:Along with the deepening of global economic integration, China economy ushered in the rapid development of the spring at the same time, the energy consumption also shows an increasing trend. Among them, carbon emissions China from 1980 14.5 tons of rapid growth of 100 tons by 2013 and ranked first in the world, accounting for the total global emissions according to the 29%. study shows that the logistics distribution has one of the important sources of global carbon emissions of greenhouse gases, the share of 14%. accounted for 12% compared to the United States and EU 11% share, occupy the total greenhouse gas emissions of greenhouse gases in China's logistics industry is as high as 19%. so, considering the vehicle routing problem of carbon emission factors to reduce China's carbon emissions becomes crucial for transportation and logistics industry the focus of this article. The research is to consider the carbon emission factors under the vehicle routing model and optimization method, the specific research contents and innovations are as follows First, for carbon emissions calculation of freight vehicles, comparison analysis and calculation model of carbon emission; considering the computational simplicity and operability, a simplified calculation model for logistics enterprises may be involved in carbon trading, carbon emissions are buying and selling operations and carbon punishment at the same time, research suitable for logistics enterprises with carbon carbon trading mechanism and model of punishment, in addition to the analysis of effects of carbon trading mechanism fluctuation on logistics distribution structure. Secondly, according to the study on vehicle routing problem, a multi-objective integer programming model with carbon emissions and time window; considering the complexity of solving the model, combined with clustering analysis method, scanning algorithm and successive correction algorithm on both sides to design the new hybrid genetic algorithm. Through clustering analysis technology can be classified according to the discrete situation of customers, reduce the invalid search algorithm ; secondly, using scanning algorithm can quickly sort of similar customers, avoid bad individual fitness; finally, the use of two successive correction algorithm can be re optimization of the optimized sub path, so as to improve the capability of the algorithm. To validate the performance of algorithm design, using standard examples to test the effectiveness the algorithm and reliability. Finally, combined with the logistics distribution case of Chongqing Tianyou dairy Limited by Share Ltd, considering the hybrid genetic algorithm to vehicle routing model and design of carbon emission factors to verify this. At the same time according to the case, are discussed respectively in the single models, mixed models, carbon trading volume ratio, the influence of different carbon trading price the price of carbon and punishment of logistics and distribution, in addition, compared with other heuristic algorithms and verify the design of the hybrid genetic algorithm is practical and stable. The main contribution of this paper Is the first, summarize the logistics vehicle emissions calculation model, calculation method to determine the suitable carbon emissions, followed by establishing carbon trading mechanism and Discussion on logistics distribution vehicle routing. Second integer programming model to solve the problem of multi target with carbon emissions and time windows, designed to solve the model according to the complexity of hybrid the genetic algorithm, the results verify the model and algorithm. Third, through the case further verification considering vehicle routing model and algorithm for the construction of carbon emissions.

【學(xué)位授予單位】：重慶交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：U492.22

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本文編號：1427423