發(fā)布時(shí)間：2019-03-29 10:48

【摘要】：面對(duì)規(guī)模龐大的在線交易系統(tǒng)以及巨大的競(jìng)爭(zhēng)壓力,物流公司需要不斷提升自身的服務(wù)質(zhì)量以及降低成本。車輛路徑問(wèn)題為物流公司規(guī)劃合理的配送路線,對(duì)降低物流公司的運(yùn)輸成本和提高其服務(wù)質(zhì)量都具有很重要的意義。本文重點(diǎn)研究了多階段車輛路徑問(wèn)題和綠色車輛路徑問(wèn)題。針對(duì)多階段車輛路徑問(wèn)題,本文設(shè)計(jì)一種混合式的啟發(fā)式算法,能夠?qū)Τ^(guò)兩階段的大規(guī)模車輛路徑問(wèn)題進(jìn)行求解。為了提高搜索解的質(zhì)量,本文提出一種負(fù)載平衡策略,使得解的搜索過(guò)程可以快速?gòu)呢?fù)載不平衡狀態(tài)變遷到平衡狀態(tài)。該算法把多階段車輛路徑問(wèn)題分解成不同的子問(wèn)題,利用最后一個(gè)階段的獨(dú)立性,并結(jié)合并行優(yōu)化的思想,本文設(shè)計(jì)混合策略模擬退火算法來(lái)解決最后階段的車輛路徑問(wèn)題,并采用線性規(guī)劃對(duì)中間階段進(jìn)行精確求解。實(shí)驗(yàn)結(jié)果表明,在66組基準(zhǔn)數(shù)據(jù)集上,目標(biāo)值與最優(yōu)解平均偏差2.4%,其中56.06%的數(shù)據(jù)集能求出最優(yōu)解;與現(xiàn)有的精確算法相比,與其最終解平均偏差2.8%;相比現(xiàn)有的精確算法,該算法能夠處理更大規(guī)模的問(wèn)題以及任意階段數(shù)量的車輛路徑問(wèn)題。在以能耗為優(yōu)化目標(biāo)的綠色車輛路徑問(wèn)題中,本文提出并行混合策略模擬退火算法。本文從實(shí)際的角度出發(fā),選擇了車輛負(fù)載和行駛距離作為影響車輛能耗速率的關(guān)鍵因素,并建立能耗速率與車輛負(fù)載以及車輛行駛的距離之間關(guān)系。在此基礎(chǔ)上,建立綠色車輛路徑問(wèn)題的模型。利用在多階段車輛路徑的研究成果,負(fù)載平衡策略被有效的運(yùn)用到解決綠色車輛路徑問(wèn)題的算法設(shè)計(jì)中。在同樣迭代次數(shù)的條件下,并行計(jì)算有效的擴(kuò)大解的搜索范圍。實(shí)驗(yàn)結(jié)果表明,相比優(yōu)化前的算法,目標(biāo)值平均減少了42.49%,方差平均減少了86.41%。
[Abstract]:Facing large-scale online trading system and huge competitive pressure, logistics companies need to continuously improve their service quality and reduce costs. The vehicle routing problem is a reasonable distribution route for logistics companies. It is of great significance to reduce the transportation cost and improve the service quality of logistics companies. This paper focuses on the multi-stage vehicle routing problem and the green vehicle routing problem. For the multi-stage vehicle routing problem, a hybrid heuristic algorithm is designed in this paper, which can solve the large-scale vehicle routing problem with more than two stages. In order to improve the quality of the search solution, a load balancing strategy is proposed in this paper, so that the search process of the solution can quickly change from the load imbalance state to the equilibrium state. The algorithm decomposes the multi-stage vehicle routing problem into different sub-problems. Using the independence of the last stage and the idea of parallel optimization, this paper designs a hybrid strategy simulated annealing algorithm to solve the vehicle routing problem in the final stage. Linear programming is used to solve the intermediate stage accurately. The experimental results show that the average deviation between the target value and the optimal solution is 2.4% on 66 sets of benchmark data sets, and 56.06% of the data sets can find the optimal solution, and the average deviation between the target value and the optimal solution is 2.8%, compared with the existing accurate algorithm, and the average deviation between the target value and the optimal solution is 2.8%. Compared with the existing accurate algorithms, the proposed algorithm can deal with large-scale problems and vehicle routing problems with arbitrary number of phases. In this paper, a parallel hybrid strategy simulated annealing algorithm is proposed for the green vehicle routing problem with energy consumption as the optimization objective. In this paper, the vehicle load and driving distance are selected as the key factors affecting the energy consumption rate from the practical point of view, and the relationship between the energy consumption rate and the vehicle load as well as the vehicle driving distance is established. On this basis, the model of green vehicle routing problem is established. Using the research results of multi-stage vehicle routing, the load balancing strategy is effectively applied to the algorithm design of solving the green vehicle routing problem. Under the condition of the same number of iterations, parallel computing extends the search range of efficient solutions. The experimental results show that the target value and variance decrease by 42.49% and 86.41%, respectively, compared with the algorithm before optimization.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TP301.6

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相關(guān)期刊論文 前1條

1 呂品;;基于最小碳排放的綠色供應(yīng)鏈網(wǎng)絡(luò)設(shè)計(jì)模型研究[J];物流技術(shù);2013年07期

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本文編號(hào)：2449453