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自動(dòng)化立體倉(cāng)庫(kù)揀貨系統(tǒng)的建模與優(yōu)化研究

發(fā)布時(shí)間:2018-01-11 23:02

  本文關(guān)鍵詞:自動(dòng)化立體倉(cāng)庫(kù)揀貨系統(tǒng)的建模與優(yōu)化研究 出處:《青島大學(xué)》2013年碩士論文 論文類(lèi)型:學(xué)位論文


  更多相關(guān)文章: 自動(dòng)化立體倉(cāng)庫(kù) 揀貨系統(tǒng) 啟發(fā)式算法 遺傳算法


【摘要】:自動(dòng)化立體倉(cāng)庫(kù)是一種采用高層立體貨架儲(chǔ)存物資,計(jì)算機(jī)系統(tǒng)進(jìn)行控制管理,自動(dòng)控制堆垛機(jī)及運(yùn)輸車(chē)進(jìn)行存取作業(yè)的倉(cāng)庫(kù),它作為倉(cāng)儲(chǔ)管理的重要組成部分,其工作效率直接影響著整個(gè)倉(cāng)儲(chǔ)作業(yè)的運(yùn)作效率。在企業(yè)競(jìng)爭(zhēng)日趨激烈的環(huán)境下,效率己被視為企業(yè)的競(jìng)爭(zhēng)核心,這就對(duì)自動(dòng)化倉(cāng)儲(chǔ)技術(shù)提出新的挑戰(zhàn)。 自動(dòng)化立體倉(cāng)庫(kù)主要包括貨物輸送系統(tǒng)、揀貨系統(tǒng)、管理與控制系統(tǒng)等部分,揀貨系統(tǒng)是自動(dòng)化立體倉(cāng)庫(kù)的關(guān)鍵部分,其流程中揀貨作業(yè)時(shí)間占整個(gè)倉(cāng)庫(kù)運(yùn)作時(shí)間的一半以上,因此,揀貨作業(yè)的效率決定著自動(dòng)化倉(cāng)庫(kù)的運(yùn)作效率。影響揀貨作業(yè)效率的關(guān)鍵因素是揀貨路徑的長(zhǎng)短,這就需要尋找優(yōu)化揀貨路徑的方法。 本文針對(duì)如何提高揀貨系統(tǒng)效率尋求方法。首先簡(jiǎn)述自動(dòng)化立體倉(cāng)庫(kù)的發(fā)展和它的結(jié)構(gòu)組成,描述揀貨系統(tǒng)的流程,分析影響揀貨效率的因素,得出優(yōu)化揀貨路徑是提高揀貨效率的關(guān)鍵。然后提出優(yōu)化揀貨路徑的方法,重點(diǎn)研究遺傳算法、蟻群算法和粒子群算法在尋求最優(yōu)揀貨路徑的實(shí)現(xiàn)方法。最后文章提出一種基于啟發(fā)式規(guī)則的算法,用此算法求解以揀貨時(shí)間最小化為目標(biāo)的數(shù)學(xué)模型,并在實(shí)例中與遺傳算法比較,證明其實(shí)用價(jià)值。此算法簡(jiǎn)單并且運(yùn)算時(shí)間短,在實(shí)際應(yīng)用方面,可考慮用于堆垛機(jī)的單機(jī)自動(dòng)運(yùn)行功能中,由PLC編程實(shí)現(xiàn)。
[Abstract]:Automatic warehouse is a kind of warehouse which uses the storage material of the high level shelf, the computer system carries on the control management, automatically controls the stacker and the transport vehicle to carry on the access operation. As an important part of warehouse management, its working efficiency directly affects the operation efficiency of the whole warehouse operation. In the increasingly competitive environment, efficiency has been regarded as the core of enterprise competition. This poses a new challenge to automated warehousing technology. Automated warehouse mainly includes cargo delivery system, picking system, management and control system, etc. Picking system is the key part of automated three-dimensional warehouse. The picking time in the process accounts for more than half of the operation time of the whole warehouse, therefore. The efficiency of picking operations determines the operational efficiency of automated warehouses, and the key factor affecting the efficiency of picking operations is the length of the picking path, which needs to find a way to optimize the picking path. This paper aims at how to improve the efficiency of picking system. Firstly, the development and structure of automated warehouse are briefly described, the process of picking system is described, and the factors affecting the efficiency of picking are analyzed. It is concluded that optimizing the picking path is the key to improve the picking efficiency. Then the method of optimizing the picking path is put forward, and the genetic algorithm is studied emphatically. Ant colony algorithm (ACA) and particle swarm optimization (PSO) algorithm are used to realize the optimal picking path. Finally, an algorithm based on heuristic rules is proposed to solve the mathematical model with the aim of minimizing the picking time. Compared with the genetic algorithm, this algorithm is simple and has short operation time. In practical application, it can be considered to be used in the single machine automatic running function of stacker, which can be realized by PLC programming.
【學(xué)位授予單位】:青島大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2013
【分類(lèi)號(hào)】:TP18;TH692.3

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