【摘要】：在現(xiàn)代物流技術(shù)領(lǐng)域中,新產(chǎn)生了一個存儲模式,即為自動化立體倉庫,在一定程度上影響了工業(yè)生產(chǎn),并在工業(yè)生產(chǎn)中起著極其重要的作用。本文的主要研究內(nèi)容如下:(1)現(xiàn)代物流系統(tǒng)中優(yōu)化自動化立體倉庫調(diào)度起著極其重大得影響;為了更好的進行后文的建模和優(yōu)化調(diào)度問題,在第一章中介紹自動化立體倉庫的基本概念及其結(jié)構(gòu)。(2)以對自動化立體倉庫的入庫貨位分區(qū)及貨位分配問題進行了詳細介紹,分別闡述了自動化立體倉庫的分區(qū)和分配原則,并建立了貨位優(yōu)化數(shù)學模型及貨位分配優(yōu)化模型。(3)對堆垛機的調(diào)度和調(diào)度優(yōu)化目標的進行了分析,對堆垛機五種常見停留策略進行了討論,并分析比較五種停留策略性能優(yōu)劣。(4)為了更好的優(yōu)化堆垛機揀選作業(yè)和復(fù)合作業(yè),詳細分析堆垛機作業(yè)方式的特點,并針對這兩種作業(yè)方式提出了優(yōu)化方法。對于揀選作業(yè),提出了含周轉(zhuǎn)貨箱容量限制作業(yè)調(diào)度,重新構(gòu)建數(shù)學模型。對模型進行分析,發(fā)現(xiàn)該模型為NP完全問題,對這個模型求解的方法可采用遺傳算法。對于復(fù)合作業(yè),經(jīng)過適當轉(zhuǎn)換規(guī)則發(fā)展,把這類作業(yè)調(diào)度問題轉(zhuǎn)變成旅行商問題,優(yōu)化復(fù)合作業(yè)這種作業(yè)方式的方法可采用遺傳算法。通過仿真驗證以上兩種作業(yè)方式的優(yōu)化,和隨機調(diào)度相比較,結(jié)果表明,該優(yōu)化算法可大大縮短調(diào)度的運行時間。
[Abstract]:In the field of modern logistics technology, a new storage mode has emerged, that is, automatic three-dimensional warehouse, which has affected industrial production to a certain extent and played an extremely important role in industrial production. The main contents of this paper are as follows: (1) the optimization of automated warehouse scheduling in modern logistics system plays an extremely important role; In the first chapter, the basic concept and structure of automated warehouse are introduced. (2) the partition and distribution of storage space are introduced in detail, and the partition and distribution principle of automated warehouse are expounded respectively. The mathematical model of cargo location optimization and the optimization model of cargo location allocation are established. (3) the scheduling and scheduling optimization objectives of the stacker are analyzed, and five common stopover strategies of the stacker are discussed. The performance of the five stopover strategies is analyzed and compared. (4) in order to optimize the picking and composite operations of the stacker, the characteristics of the stacker operation are analyzed in detail, and the optimization methods are proposed. For the picking operation, a new mathematical model is proposed, which includes the limited capacity of the container and the scheduling of the operation. By analyzing the model, it is found that the model is a NP complete problem, and the genetic algorithm can be used to solve the model. For compound jobs, after proper transformation rules, this kind of job scheduling problem is transformed into traveling salesman problem. Genetic algorithm can be used to optimize the operation mode of compound jobs. The simulation results show that the proposed optimization algorithm can greatly shorten the scheduling time compared with the random scheduling.
【學位授予單位】：沈陽大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：F252;TP18

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本文編號：2284834