【摘要】：隨著電商平臺的發(fā)展,電商企業(yè)對市場的占有率逐年提升,其產(chǎn)品具有種類繁多、市場需求變動較大且周期較短的特點。目前電商倉庫通常采用“先貨位指派,后揀貨”的作業(yè)方式,這種作業(yè)方式對于產(chǎn)品需求變動較大的倉庫難以滿足實時市場需求,并且會加大分揀人員工作難度,降低其工作效率。因此對于此類型產(chǎn)品的倉庫,貨位指派與揀貨路徑系統(tǒng)優(yōu)化是當(dāng)前研究的必然趨勢。本文主要針對電商、零售等企業(yè)其產(chǎn)品需求變動較大的特點,提出一種“動態(tài)貨位指派與揀貨”協(xié)同作業(yè)的揀貨方式,通過協(xié)同作業(yè)和動態(tài)貨位指派,最終達(dá)到倉庫適應(yīng)市場實時變化,并提高分揀人員工作效率的目的。具體內(nèi)容如下:首先,對貨位指派、路徑優(yōu)化和模擬退火算法的相關(guān)理論進(jìn)行簡要概述;其次,建立優(yōu)化數(shù)學(xué)模型,通過模型假設(shè)條件和約束條件,建立優(yōu)化模型目標(biāo)函數(shù);再次,基于模擬退火算法進(jìn)行求解,根據(jù)實際情況及國內(nèi)外研究成果設(shè)計出模型影響因素,并進(jìn)行基準(zhǔn)實驗設(shè)計;最后對優(yōu)化模型進(jìn)行仿真分析,為了驗證算法的正確性,本文使用matlab軟件對算法進(jìn)行求解,并對求解結(jié)果進(jìn)行分析,分析結(jié)果包含兩部分,其一是驗證優(yōu)化模型的有效性;其二評價各組合策略的效果。
[Abstract]:With the development of ecommerce platform, the market share of ecommerce enterprises is increasing year by year. Its products have many kinds, the market demand changes greatly and the cycle is short. At present, the e-commerce warehouse usually adopts the operation mode of "first place assignment, then picking goods". This kind of operation mode is difficult to meet the real-time market demand for the warehouse where the product demand changes greatly, and it will make it more difficult for the sorting personnel to work. Reduce the efficiency of its work. Therefore, for the warehouse of this type of products, the optimization of cargo location assignment and picking path system is the inevitable trend of current research. In view of the great change of product demand in e-commerce, retail and other enterprises, this paper puts forward a kind of picking mode of "dynamic cargo location assignment and picking" cooperative operation, through collaborative operation and dynamic cargo location assignment. Finally, the warehouse adapts to the real-time changes in the market and improves the efficiency of sorting personnel. The specific contents are as follows: firstly, the related theories of cargo location assignment, path optimization and simulated annealing algorithm are briefly summarized. Secondly, the optimization mathematical model is established, and the objective function of the optimization model is established through the assumptions and constraints of the model. Thirdly, based on the simulated annealing algorithm, the influencing factors of the model are designed according to the actual situation and the research results at home and abroad, and the benchmark experiment design is carried out. Finally, the optimization model is simulated and analyzed. In order to verify the correctness of the algorithm, this paper uses matlab software to solve the algorithm, and analyzes the solution results. The analysis results include two parts, one is to verify the effectiveness of the optimization model; Second, the effect of each combination strategy is evaluated.
【學(xué)位授予單位】：華東交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F252

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