【摘要】：經(jīng)濟的全球化以及互聯(lián)網(wǎng)時代的到來,極大的推動了電子商務(wù)的發(fā)展,同時也帶來了與之相應(yīng)的電商供應(yīng)鏈的極大關(guān)注。如何建立與電商發(fā)展同步的供應(yīng)鏈,是保障其高速發(fā)展的重要因素。本文基于極值優(yōu)化算法,建立了電商的供應(yīng)鏈網(wǎng)絡(luò)模型,并對其彈性進行了分析。本文首先介紹了電商供應(yīng)鏈中的前臺物流與后臺物流。后臺物流即供應(yīng)鏈網(wǎng)絡(luò)問題,前臺物流即末端物流問題。之后介紹了他們的大致情況以及發(fā)展狀況,并指出了其中的不足。隨后介紹了針對這些不足即將采取的研究方法,即極值優(yōu)化算法。從算法基礎(chǔ)到改進方法,以及研究進展和存在問題等多個方面,大致的講解了算法情況。隨后,建立了供應(yīng)網(wǎng)絡(luò)的數(shù)學模型,模型從負載與節(jié)點滿意度兩個角度進行分析,實現(xiàn)了供應(yīng)網(wǎng)絡(luò)中個體利益與全局利益的最優(yōu)化。同時從適應(yīng)性以及恢復(fù)能力等角度分析了網(wǎng)絡(luò)彈性。最后通過引入經(jīng)典的豐田汽車的供應(yīng)鏈案例進行仿真,驗證了算法在增加其彈性上的有效性。最后,由于現(xiàn)有的末端物流問題大多只有理論分析,缺乏實際的定量仿真,或者仿真模型并沒有充分考慮末端物流中客戶需求的個性化。因此,為降低配送成本同時提高服務(wù)質(zhì)量,本文結(jié)合車輛路徑問題與電商中消費需求品種多批量小、批次多周期短的特點,針對客戶每日需求的不確定性,提出針對每日需求的信息化的彈性配送策略,以人均成本最小化為目標構(gòu)造了模型;設(shè)計基于極值動力學的改進蟻群算法對物流配送路徑進行優(yōu)化,通過 尋優(yōu)‖與 棄差‖、局部搜索與全局搜索相結(jié)合,提高了算法收斂效率;并在最后通過對算例驗證了該算法在面對多種不確定性需求時候的彈性,有助于實現(xiàn)末端物流的高效配送。
[Abstract]:The globalization of economy and the arrival of the Internet era have greatly promoted the development of electronic commerce and brought great attention to the corresponding e-commerce supply chain. How to establish a supply chain synchronized with the development of e-commerce is an important factor to ensure its rapid development. Based on the extremum optimization algorithm, the supply chain network model of E-quotient is established and its elasticity is analyzed. This paper first introduces the foreground logistics and background logistics in e-commerce supply chain. The backstage logistics is the supply chain network problem, and the foreground logistics is the terminal logistics problem. Then introduced their general situation and development, and pointed out the shortcomings. Then, the paper introduces the research method that will be adopted to solve these problems, that is, extremum optimization algorithm. From the basic of the algorithm to the improved method, as well as the research progress and existing problems and other aspects, the algorithm is explained roughly. Then, the mathematical model of the supply network is established. The model is analyzed from the perspectives of load and node satisfaction, and the optimization of individual and global interests in the supply network is realized. At the same time, the flexibility of the network is analyzed from the aspects of adaptability and resilience. Finally, by introducing the classic Toyota supply chain case to the simulation, the effectiveness of the algorithm in increasing its elasticity is verified. Finally, because most of the existing terminal logistics problems are only theoretical analysis, lack of practical quantitative simulation, or the simulation model does not fully consider the customer needs in the end logistics personalized. Therefore, in order to reduce the cost of distribution and improve the quality of service, this paper combines the vehicle routing problem with the characteristics of small quantity and short batch and short period of consumption demand in e-commerce, aiming at the uncertainty of customer's daily demand. A flexible distribution strategy based on daily demand is proposed, and the model is constructed with the goal of minimizing the cost per capita. An improved ant colony algorithm based on extremum dynamics is designed to optimize the logistics distribution path. The convergence efficiency of the algorithm is improved by combining local search with global search. Finally, an example is given to verify the flexibility of the algorithm in the face of a variety of uncertain demands, which is helpful to realize the efficient distribution of terminal logistics.
【學位授予單位】：華中科技大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：F724.6;F274

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