本文選題：電子商務 + 分區(qū)揀選系統(tǒng)��； 參考：《大連理工大學》2014年碩士論文

【摘要】：傳統(tǒng)倉儲操作中,人工訂單揀選系統(tǒng)成本占倉儲總成本的55%以上,而電子商務環(huán)境下,日訂單量可達十幾萬單,且訂購的商品種類繁多。為提高訂單揀選系統(tǒng)效率,從揀選環(huán)節(jié)加快訂單配送速度,本文針對電子商務環(huán)境下的訂單揀選系統(tǒng)展開研究�？紤]到訂單合并策略和分區(qū)揀選策略對提高揀選系統(tǒng)效率有效性更高,本文主要研究并行分區(qū)揀選系統(tǒng)的訂單合并優(yōu)化問題。當前訂單合并策略可分為以下五種：優(yōu)先規(guī)則算法、種子算法、節(jié)約算法、數(shù)據(jù)挖掘算法和啟發(fā)式算法。由于傳統(tǒng)種子訂單沒有從全局考慮訂單間的相似性,本文首先分析了基于相似度聚類的訂單合并問題,借用種子算法中合并訂單規(guī)則其中的一個系數(shù)——最大相同通道數(shù),構建基于相似度的訂單合并模型,從全局最優(yōu)的角度依據(jù)相似度系數(shù)進行訂單合并規(guī)則構建,最終求得訂單合并批次結果；針對并行分區(qū)的訂單合并問題,研究主要針對分區(qū)揀選的數(shù)量、大小、存儲商品數(shù)等因素對揀選系統(tǒng)效率的影響。雖有學者提出工作量均衡對分區(qū)揀選策略的重要性,但當前多采用商品合理分配的方法在規(guī)劃期解決該問題。本文從實際操作角度,構建最小化整體的工作量和平衡各個分區(qū)的工作量的訂單合并模型,并采用雙目標遺傳算法進行模型的求解。 本論文的主要研究內(nèi)容如下： (1)從電子商務物流出發(fā),通過對運作流程的梳理,說明訂單揀選作業(yè)在電子商務物流中的重要作用；同時總結了訂單揀選中可能存在的優(yōu)化問題,包括分揀系統(tǒng)的設計、倉庫布局的優(yōu)化、分揀作業(yè)方式和揀貨路徑策略；最后歸納了當前較常見的幾種訂單揀選路徑策略。 (2)對傳統(tǒng)單區(qū)型布局揀選系統(tǒng)的訂單合并策略進行了定義,并介紹了以最小化總體行走距離的通用訂單合并模型；將聚類的思想引入到訂單合并問題中,借鑒種子算法的最大相同通道系數(shù)為聚類相似性系數(shù),構建了基于相似度聚類的訂單合并優(yōu)化模型；采用改進種子算法構建基于相似度的訂單聚類規(guī)則,從全局的角度搜索相似度較高的訂單,每次進行訂單合并時,都選取訂單集合中相似度最高的兩個訂單；最后在五種不同的訂單環(huán)境下,基于四種評價指標,將聚類規(guī)則與種子算法、先來先服務算法進行比較分析,說明了模型和算法的有效性。 (3)在對單區(qū)型布局揀選系統(tǒng)研究基礎上,對并行分區(qū)揀選系統(tǒng)的特征及運作流程進行分析,說明工作量均衡在并行分區(qū)揀選系統(tǒng)運作中的重要性；分析了訂單完成總時間和各分區(qū)工作時間的特點,構建并行分區(qū)揀選時間序列模型；考慮到分區(qū)工作量均衡對揀選系統(tǒng)的重要性,構建最小化訂單完成總時間和各分區(qū)工作時間標準差的雙目標訂單合并模型；采用雙目標遺傳算法求解此模型,通過基于排序的表現(xiàn)矩陣計算染色體的適應度,并依據(jù)染色體的適應度大小和種群整體性能的比較確定其交叉和變異的概率,保持種群的多樣性,并控制種群向優(yōu)解的方向進化。最后在三種不同的訂單環(huán)境下,將結果與不考慮分區(qū)工作量均衡的單目標遺傳算法做了比較分析,說明模型在平衡分區(qū)工作量上的有效性。 本文針對電子商務環(huán)境下的并行分區(qū)揀選系統(tǒng)的訂單合并問題,分別考慮將相似性聚類和分區(qū)工作量均衡等因素引入訂單合并模型中,提高電子商務訂單揀選效率,有利用提高員工的工作積極性和公平感。研究可以為倉儲管理部門提高訂單處理速度提供決策支持,為倉儲配送中心更人性化的管理方式提供指導思路。
[Abstract]:In the traditional warehousing operation, the cost of the artificial order sorting system accounts for more than 55% of the total storage cost. In the e-business environment, the daily order amount can reach tens of thousands of orders, and there are many kinds of goods ordered. In order to improve the efficiency of order sorting system and speed up the order distribution speed from the picking link, this paper aims at the order sorting system under the e-business environment. Considering that order merger strategy and partition selection strategy are more efficient to improve the efficiency of sorting system, this paper mainly studies the problem of order merger optimization in parallel sorting system. The current order merger strategy can be divided into five types: priority rule algorithm, seed calculation method, saving algorithm, data mining algorithm and heuristic method. Because the traditional seed orders do not consider the similarity between orders globally, this paper first analyzes the problem of order merger based on similarity clustering, and constructs an order Merger Model Based on the similarity degree based on the coefficient of the largest same channel, which is based on the global optimum. The similarity coefficient is built for order merger rules, and the results of order merger are finally obtained. In order to solve the problem of order merger in parallel partitions, the influence of the quantity, size, and the number of storage goods on the efficiency of the sorting system is mainly studied. Although some scholars have proposed the importance of the workload balance to the sorting strategy, At present, the method of reasonable distribution of goods is used to solve the problem in the planning period. From the practical point of view, this paper constructs an order merger model which minimizes the overall workload and balances the workload of each partition, and uses a dual objective genetic algorithm to solve the model.
The main contents of this paper are as follows:
(1) from the e-commerce logistics, through the combing of the operation process, the important role of order picking operation in e-business logistics is explained. At the same time, the optimization problems that may exist in order picking are summarized, including the design of the sorting system, the optimization of the warehouse layout, the sorting operation mode and the picking route strategy. Several more common order picking path strategies.
(2) the order merger strategy of the traditional single area layout sorting system is defined, and a general order merger model is introduced to minimize the overall walking distance. The idea of clustering is introduced to the order merger problem, and the similarity coefficient based on the maximum same channel coefficient of the seed algorithm is used for reference, and the similarity clustering is constructed. The order merger optimization model is used to construct the order clustering rule based on the similarity degree, and the similarity degree of order is searched from the global point of view. Two orders with the highest similarity in the order set are selected each time the order merger is merged. Finally, the four evaluation indexes will be based on the five different order environment. The clustering rule and seed algorithm are compared with the first come first service algorithm, which shows the effectiveness of the model and algorithm.
(3) on the basis of the study of the single area layout selection system, the characteristics and operation process of the parallel zoning sorting system are analyzed, and the importance of the workload balance in the operation of the parallel zoning sorting system is illustrated. The characteristics of the total time and the working time of each partition are analyzed, and the parallel sorting time sequence model is constructed. Considering the importance of the partitioned workload balance to the selection system, a two objective order merger model is constructed to minimize the total time and the standard deviation of the working time of each partition. The dual objective genetic algorithm is used to solve the model, and the fitness of the chromosomes is calculated by the sort based representation matrix, and the fitness of the chromosomes is large. The comparison of the performance of the small and the population determines the probability of its crossover and mutation, maintains the diversity of the population, and controls the evolution of the population in the direction of the optimal solution. In the end, the results are compared with the single objective genetic algorithm which does not consider the partition of the work load in the three different order environments, and shows that the model is in the balance partition workload. Validity.
This paper, aiming at the order merger of the parallel partition sorting system in the e-business environment, introduces the similarity clustering and the partition workload balance into the order merger model to improve the efficiency of the order sorting of e-commerce, and improves the employees' working enthusiasm and fairness. The research can be proposed for the warehouse management department. High order processing speed provides decision support, providing guidance for the more humane management mode of warehousing distribution center.

【學位授予單位】：大連理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：F713.36;TP18

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本文編號：1896494