本文選題：貨位分配　切入點：自動化立體庫　出處：《吉林大學》2017年碩士論文

【摘要】：自動化立體庫存儲貨物數(shù)量龐大、品種繁多,事先不對貨位進行規(guī)劃,勢必導致倉庫作業(yè)的擁堵、中斷,進而影響整個倉庫作業(yè)效率。隨著市場需求和企業(yè)的生產(chǎn)經(jīng)營活動的變化,自動化立體庫中的貨物在數(shù)量和種類上也會發(fā)生相應的變化,在時間累積效應下,原有的貨位分配方案不再適用,需要對貨位進行重新分配。因此,對貨物進行貨位分配是自動化立體庫管理活動中重要的決策內(nèi)容之一。目前絕大多數(shù)研究學者在研究貨位分配問題時,基于貨架整體的穩(wěn)定性、出入庫效率、分巷道存儲以及貨物關聯(lián)性等貨位分配原則進行考慮,只以貨架整體的穩(wěn)定性和貨物出入庫效率為目標,建立相應的貨位分配數(shù)學模型,然而,并沒有過多地在數(shù)學模型中考慮其他分配原則對貨位分配的影響。因此,本文在提高貨架整體穩(wěn)定性和出入庫效率目標的基礎上,同時考慮了貨物之間的關聯(lián)性,即在進行貨位分配時同時要求具有關聯(lián)性的貨物在貨架上就近存放。在求解貨位分配數(shù)學模型時,多采用了簡單加權遺傳算法,這種方法忽視了各目標函數(shù)之間的單位不統(tǒng)一的情況,同時也容易陷入局部最優(yōu),出現(xiàn)未成熟收斂問題。針對這些問題,本文在歸一化處理多個貨位分配優(yōu)化目標的同時,引入多種群遺傳算法求解,解決了各目標函數(shù)之間單位不統(tǒng)一,并避免了遺傳算法未成熟收斂問題。本文對自動化立體庫貨位分配問題的研究現(xiàn)狀進行了綜述,分析了貨位分配對倉庫作業(yè)的影響,對自動化立體庫構(gòu)造、貨物存儲模式和貨位分配的相關原則歸納總結(jié),提出了本文貨位優(yōu)化分配的三個目標:提高貨物出入庫效率、降低貨架整體的等效重心和關聯(lián)性貨物就近存儲;針對提出的貨位分配優(yōu)化目標,建立了相應的多目標貨位分配數(shù)學模型,并詳細設計多種群遺傳算法進行求解;結(jié)合魔幻戰(zhàn)蝠車模流水線裝配實驗的零件數(shù)量和重量信息,對自動化立體庫的貨位分配數(shù)學模型求解,分別得到多種群遺傳算法和簡單加權遺傳算法兩組求解方案,并對貨位分配方案對應的目標函數(shù)值和算法效率進行了對比分析,驗證了多種群遺傳算法在求解結(jié)果準確性和穩(wěn)定性的優(yōu)越性。最后,結(jié)合Flexsim軟件對算例貨位分配方案進行模擬,從動態(tài)的角度驗證了貨位分配方案的有效性。
[Abstract]:The quantity and variety of the goods stored in the automated warehouse are huge, so it will inevitably lead to the congestion and interruption of the warehouse operation, which will affect the efficiency of the whole warehouse operation.With the change of market demand and enterprise's production and management activities, the quantity and type of goods in the automated warehouse will also change correspondingly. Under the effect of time accumulation, the original distribution scheme of goods is no longer applicable.The cargo space needs to be reallocated.Therefore, the distribution of goods is one of the important decision-making contents in automated warehouse management.At present, most of the research scholars in the study of the allocation of cargo space, based on the overall shelf stability, storage efficiency, sub-laneway storage and cargo correlation and other cargo allocation principles are considered.Aiming at the stability of the whole shelf and the efficiency of goods entering and leaving, the mathematical model of the distribution of goods space is established. However, the influence of other allocation principles on the allocation of goods is not considered too much in the mathematical model.Therefore, on the basis of improving the overall stability of shelves and the efficiency of entering and leaving storage, this paper also takes into account the correlation between goods, that is, the goods with relevance are required to be stored nearby on the shelves during the distribution of goods.A simple weighted genetic algorithm is used to solve the mathematical model of cargo location allocation. This method ignores the unity of the units among the objective functions and is prone to fall into local optimum and appear immature convergence problem at the same time.In order to solve these problems, in order to solve the problem of unit disunity among objective functions and avoid the premature convergence of genetic algorithm, this paper normalizes the optimization target of multiple cargo allocation, and introduces multi-population genetic algorithm to solve the problem of multi-population genetic algorithm.In this paper, the current situation of research on the distribution of freight spaces in automated storage is summarized, and the influence of space allocation on warehouse operations is analyzed, and the construction, storage mode and relevant principles of distribution of goods are summarized.In this paper, three objectives of optimal allocation of goods are put forward: to improve the efficiency of loading and unloading, to reduce the equivalent center of gravity of the whole shelf and to store the relevant goods nearby, and to optimize the allocation of goods,The corresponding mathematical model of multi-target cargo space allocation is established, and the multi-population genetic algorithm is designed to solve the problem in detail, combining with the information of the number and weight of the parts in the assembly experiment of pipeline, the model of magic bat.To solve the mathematical model of freight location assignment of automated warehouse, two groups of solutions are obtained, namely, multi-population genetic algorithm and simple weighted genetic algorithm, and the objective function value and the efficiency of the algorithm are compared and analyzed.The superiority of multi-population genetic algorithm in the accuracy and stability of the solution is verified.Finally, the effectiveness of the allocation scheme is verified from the dynamic point of view by simulating the distribution scheme with Flexsim software.
【學位授予單位】：吉林大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F274;TP18

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