【摘要】：隨著近幾年在中國(guó)電子商務(wù)的快速發(fā)展，，一些B2C企業(yè)開始也建自己的物流配送中心和配送體系，配送中心是整個(gè)物流系統(tǒng)中的重要環(huán)節(jié)，配送中心的工作效率直接影響物流配送的快慢程度。物流配送服務(wù)水平的高低也直接影響客戶的購(gòu)物體驗(yàn)和服務(wù)滿意度，這也間接的反映客戶對(duì)公司的品牌信任度，所以如何有效的提高配送中心的管理和運(yùn)作效率，己經(jīng)成為眾多B2C企業(yè)面臨的最棘手的問(wèn)題。 配送中心內(nèi)部作業(yè)中包括多個(gè)環(huán)節(jié)，如：接貨、搬運(yùn)、存儲(chǔ)、揀選、分揀、出貨等。這些作業(yè)中揀選作業(yè)是非常重要的一個(gè)環(huán)節(jié)，在配送中心內(nèi)部作業(yè)中占的比重較大，也是最耗時(shí)間的工作，因此可以說(shuō)揀選效率直接影響配送中的整體運(yùn)作效率和客戶服務(wù)滿意度。本文以雙區(qū)型倉(cāng)庫(kù)為研究對(duì)象在配送中心貨物管理系統(tǒng)中引入RFID技術(shù)，重點(diǎn)針對(duì)揀貨車輛揀選路徑進(jìn)行了優(yōu)化處理，以單個(gè)揀貨車輛和多個(gè)揀貨車輛的條件下各自單獨(dú)的建立揀選路徑問(wèn)題的數(shù)學(xué)模型，設(shè)計(jì)相應(yīng)的算法對(duì)揀貨車輛行走路徑進(jìn)行了優(yōu)化處理，從而有效的減少了揀貨車輛揀貨過(guò)程中的行走距離。 通過(guò)對(duì)揀選路徑優(yōu)化算法驗(yàn)證，證明單車輛揀選路徑優(yōu)化中混合遺傳退火算法相比遺傳算法的有效性，針對(duì)多車輛揀選路徑優(yōu)化中先用單車輛揀選路徑優(yōu)化的混合遺傳算法對(duì)數(shù)學(xué)模型整體優(yōu)化，就是先對(duì)訂單進(jìn)行分批處理，然后對(duì)每輛車的揀選路徑用遺傳算法求解TSP問(wèn)題，這樣可以在多車輛揀選情況下最大限度的減少揀選過(guò)程中的行走距離。 在編程求解方面，本文運(yùn)用MATLAB語(yǔ)言進(jìn)行編程實(shí)現(xiàn)問(wèn)題的相關(guān)算法，對(duì)揀選路徑優(yōu)化模型進(jìn)行求解，并在MATLAB R2010a平臺(tái)上進(jìn)行了算法的仿真實(shí)現(xiàn)。
[Abstract]:With the rapid development of e-commerce in China in recent years, some B2C enterprises have started to build their own logistics distribution center and distribution system. Distribution center is an important link in the whole logistics system. The efficiency of distribution center directly affects the speed and speed of logistics distribution. The level of logistics distribution service also directly affects the customer's shopping experience and service satisfaction, which also indirectly reflects the customer's brand trust in the company, so how to effectively improve the management and operational efficiency of the distribution center, It has become the most difficult problem faced by many B2C enterprises. Distribution center internal operations include a number of links, such as: pick-up, handling, storage, picking, sorting, shipping, and so on. Selection is a very important link in these operations, which accounts for a large proportion of the internal operations in the distribution center and is also the most time-consuming work. Therefore, it can be said that picking efficiency directly affects the overall operational efficiency and customer service satisfaction in distribution. In this paper, RFID technology is introduced into the cargo management system of distribution center with dual-area warehouse as the research object, and the optimization of picking path of picking vehicle is focused on. Under the condition of single picking vehicle and multiple picking vehicle, the mathematical model of picking path problem is established separately, and the corresponding algorithm is designed to optimize the walking path of picking vehicle, and the mathematical model of picking path problem is established separately under the condition of single picking vehicle and multiple picking vehicle. Thus effectively reduces the picking vehicle in the picking process of the walking distance. It is proved that the hybrid genetic annealing algorithm is more effective than the genetic algorithm in single vehicle picking path optimization through the verification of the picking path optimization algorithm. In the multi-vehicle picking path optimization, a hybrid genetic algorithm based on single vehicle picking path optimization is used to optimize the whole mathematical model, that is to say, the order is processed in batches first, and then the TSP problem is solved by genetic algorithm for the picking path of each vehicle. This can minimize the walking distance during the picking process in the case of multi-vehicle picking. In the aspect of programming solution, this paper uses MATLAB language to carry on the related algorithm of the programming realization problem, to solve the picking path optimization model, and has carried on the simulation realization to the algorithm on the MATLAB R2010a platform.
【學(xué)位授予單位】：沈陽(yáng)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)】：TP18;TP391.44

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