本文選題：訂單分批 + 路徑選擇　； 參考：《山東大學(xué)》2015年碩士論文

【摘要】：揀選作業(yè)是物流中心主要的作業(yè)流程之一,揀選作業(yè)成本占據(jù)著物流中心運(yùn)營(yíng)成本的60%,提高揀選效率是降低物流中心揀選成本的有效途徑之一。在揀選客戶訂單之前,合理地對(duì)訂單進(jìn)行分批,將同一批的訂單在一次揀選過程中同時(shí)完成,可以顯著地節(jié)省揀選時(shí)間,提高揀選貨物的效率,即使減少相當(dāng)少的揀選時(shí)間也能相應(yīng)的減少物流中心揀貨成本。本文旨在研究一種實(shí)用有效方法,通過對(duì)訂單進(jìn)行合理的分批,使得完成所有訂單貨物揀選的總行走距離最小。首先,本文在總結(jié)訂單分批常用算法的基礎(chǔ)上,從路徑選擇的角度考慮建模,即先為每一個(gè)訂單從一個(gè)路徑集中選擇一條路徑,再將相同路徑下的所有訂單進(jìn)行合并分批。模型以全部訂單總行走距離最小為目標(biāo)函數(shù)。其次,針對(duì)訂單總行走距離最短問題提出了遺傳算法(GA)和局部搜索算法(ILS)混合求解算法。模型的求解過程分為兩個(gè)步驟：一是建立訂單路徑集；二是結(jié)合遺傳算法(GA)和局部搜索算法(ILS)對(duì)訂單進(jìn)行分批合并。其中,遺傳算法是用來(lái)為每一個(gè)訂單選擇一條最優(yōu)路徑；局部迭代搜索算法是用來(lái)對(duì)同一路徑下的所有訂單進(jìn)行分批,目的是使分批數(shù)目最少。最后,在考慮了不同的揀選設(shè)備容量和訂單數(shù)目的基礎(chǔ)上,設(shè)計(jì)了8個(gè)算例實(shí)驗(yàn)。從計(jì)算效率、目標(biāo)函數(shù)優(yōu)化程度的角度分別對(duì)比三種算法,即本文提出的混合遺傳算法和局部迭代搜索算法(GA-ILS)、先進(jìn)先出算法(FCFS)和簡(jiǎn)單遺傳算法(base-GA)。實(shí)驗(yàn)結(jié)果表明,本文提出的混合遺傳算法和局部迭代搜索算法(GA-ILS)相比于FCFS和base-GA算法在總揀選距離上具有明顯優(yōu)勢(shì),在計(jì)算速度上比base-GA算法更快。
[Abstract]:Picking operation is one of the main processes of logistics center. Picking operation cost occupies 60% of the operating cost of logistics center. Improving picking efficiency is one of the effective ways to reduce the selection cost of logistics center. Before selecting the customer's order, the order can be divided reasonably, and the same batch of order can be completed at the same time in one picking process, which can significantly save the picking time and improve the efficiency of picking the goods. Even a relatively small reduction in picking time can reduce the cost of picking goods in logistics centers. The purpose of this paper is to study a practical and effective method to minimize the total walking distance to complete the picking of all the goods ordered by a reasonable order in batches. Firstly, on the basis of summarizing the common algorithms of order batching, this paper considers the modeling from the point of view of path selection, that is to say, we first select a path from one path set for each order, and then merge all orders under the same path into batches. The model takes the minimum total walking distance of all orders as the objective function. Secondly, a hybrid algorithm of genetic algorithm (GA) and local search algorithm (ILS) is proposed to solve the shortest total walking distance of orders. The solution of the model is divided into two steps: one is to establish the order path set, the other is to combine the genetic algorithm (GA) with the local search algorithm (ILS) to merge the orders in batches. The genetic algorithm is used to select an optimal path for each order and the local iterative search algorithm is used to batch all orders on the same path in order to minimize the number of batches. Finally, on the basis of considering the capacity of different sorting equipment and the number of orders, eight numerical examples are designed. From the point of view of computational efficiency and degree of optimization of objective function, three algorithms are compared, that is, hybrid genetic algorithm and local iterative search algorithm, first-in-first-out algorithm (FCFS) and simple genetic algorithm (GA-ILSU) and simple genetic algorithm (GA). The experimental results show that the proposed hybrid genetic algorithm and local iterative search algorithm (GA-ILS) have obvious advantages over FCFS and base-GA in total picking distance, and the computational speed is faster than that of base-GA.
【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：F252.1

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 馬士華,文堅(jiān);基于時(shí)間延遲的訂單分批策略研究[J];工業(yè)工程與管理;2004年06期

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本文編號(hào)：2004000