本文選題：低溫奶 + 車輛路徑問題��； 參考：《浙江理工大學(xué)》2017年碩士論文

【摘要】：隨著消費(fèi)者對新鮮、健康產(chǎn)品的偏好日益增加,國內(nèi)消費(fèi)者在奶制品上對低溫奶的需求量也隨之增加。因低溫奶保質(zhì)期短、易腐易損,從生產(chǎn)到銷售需要全程冷鏈作支撐,冷鏈物流特別是冷鏈物流配送在低溫奶的流通中發(fā)揮著巨大的作用。近年來,我國冷鏈物流得到迅猛發(fā)展,城市中單個(gè)物流配送中心需要服務(wù)的網(wǎng)點(diǎn)越來越多,由此構(gòu)成的配送網(wǎng)絡(luò)錯(cuò)綜復(fù)雜,為低溫奶網(wǎng)點(diǎn)配送帶來了挑戰(zhàn)。此外,由于低溫奶對時(shí)效性要求高,配送半徑有限,如何合理安排車輛的行駛路線,快速安全的進(jìn)行低溫奶配送以縮短產(chǎn)品的在途時(shí)間,提高配送效率具有重要的現(xiàn)實(shí)意義。因此,本文以城市低溫奶網(wǎng)點(diǎn)配送為研究對象,采用先分組后路線的兩階段法研究低溫奶網(wǎng)點(diǎn)配送中的車輛路徑問題。本文主要工作和貢獻(xiàn)如下:(1)低溫奶網(wǎng)點(diǎn)分區(qū)研究。定義了最短干道距離,以實(shí)際距離代替歐式距離作為網(wǎng)點(diǎn)分區(qū)依據(jù)。同時(shí)考慮距離和密度對k-medoids聚類算法初始中心進(jìn)行優(yōu)化,增加配送量約束,對網(wǎng)點(diǎn)進(jìn)行分區(qū)聚類。(2)低溫奶網(wǎng)點(diǎn)配送中車輛路徑問題模型構(gòu)建與求解。根據(jù)低溫奶網(wǎng)點(diǎn)配送的特點(diǎn),構(gòu)建了低溫奶網(wǎng)點(diǎn)配送最短路徑模型。提出了一種基于模擬退火的離散型布谷鳥搜索算法(SA-DCS),并使用算例與改進(jìn)的布谷鳥搜索算法(RKCS)進(jìn)行仿真對比,以驗(yàn)證算法的有效性。(3)應(yīng)用案例研究。選用Y食品有限公司真鮮奶吧配送真實(shí)數(shù)據(jù),開展低溫奶網(wǎng)點(diǎn)配送中的車輛路徑問題案例研究,進(jìn)一步驗(yàn)證模型和算法的有效性。研究表明,本文所提出的改進(jìn)的k-medoids聚類算法具有良好的有效性和魯棒性,考慮配送量約束的聚類質(zhì)量明顯優(yōu)于未考慮配送量約束的聚類結(jié)果。且本文提出的基于模擬退火的離散型布谷鳥搜索算法在尋優(yōu)精度與搜索性能上具有良好的表現(xiàn)。此外,由上述兩者構(gòu)成的先分組后路線的兩階段法被證明是求解車輛路徑問題的有效方法。
[Abstract]:With consumers' preference for fresh and healthy products increasing, domestic consumers' demand for low temperature milk also increases. Cold chain logistics, especially cold chain logistics, play a great role in the circulation of low temperature milk because of its short shelf life and perishable and vulnerable. In recent years, the cold chain logistics in our country has been developing rapidly, and the single logistics distribution center in the city needs more and more outlets to serve. The complicated distribution network has brought challenges to the low-temperature milk distribution network. In addition, due to the high requirement of low temperature milk on timeliness and the limited distribution radius, it is of great practical significance to arrange the driving route of the vehicle reasonably, to quickly and safely distribute the low temperature milk in order to shorten the time on the way of the product and to improve the distribution efficiency. Therefore, this paper takes the urban low-temperature milk distribution as the research object, uses the two-stage method of grouping first and then the route to study the vehicle routing problem in the distribution of low-temperature milk network. The main work and contribution of this paper are as follows: 1. The shortest trunk road distance is defined and the actual distance is used to replace the Euclidean distance as the basis of dot partition. At the same time, considering the distance and density, the initial center of the k-medoids clustering algorithm is optimized, and the distribution volume constraints are increased. According to the characteristics of low temperature milk distribution, the shortest path model of low temperature milk distribution was constructed. A discrete-time cuckoo search algorithm based on simulated annealing is proposed, and a numerical example is compared with the improved Cuckoo search algorithm (RKCS) to verify the effectiveness of the algorithm. In order to verify the validity of the model and the algorithm, a case study of the vehicle routing problem in the distribution of low-temperature milk outlets was carried out by using the true milk bar of Y Food Co., Ltd. The research shows that the improved k-medoids clustering algorithm proposed in this paper has good effectiveness and robustness, and the clustering quality considering distribution constraints is obviously superior to the clustering results without considering the distribution volume constraints. The proposed discrete cuckoo search algorithm based on simulated annealing has good performance in searching accuracy and performance. In addition, the two-stage method, which consists of the above two methods, has been proved to be an effective method for solving the vehicle routing problem.
【學(xué)位授予單位】：浙江理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F252.1;TP18

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