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分布式數(shù)控系統(tǒng)車(chē)間排產(chǎn)系統(tǒng)的設(shè)計(jì)與實(shí)現(xiàn)

發(fā)布時(shí)間:2018-08-11 17:37
【摘要】:信息技術(shù)的高速發(fā)展和廣泛應(yīng)用,使得企業(yè)的管理都逐漸由傳統(tǒng)管理向計(jì)算機(jī)管理轉(zhuǎn)變。生產(chǎn)調(diào)度排產(chǎn)是制造執(zhí)行系統(tǒng)中的重要部分,直接關(guān)系著企業(yè)的生產(chǎn)和管理效率,有效的調(diào)度方案能高效的利用生產(chǎn)資源,降低企業(yè)的生產(chǎn)成本,提高企業(yè)競(jìng)爭(zhēng)力。 車(chē)間作業(yè)調(diào)度問(wèn)題是一個(gè)非常復(fù)雜的問(wèn)題,本論文對(duì)遺傳算法和模擬退火算法進(jìn)行了詳細(xì)地研究,結(jié)合遺傳算法(GA)和模擬退火算法(SA)的優(yōu)點(diǎn),提出了一種混合遺傳模擬退火算法(GASA),以便高效地解決車(chē)間作業(yè)調(diào)度問(wèn)題。該算法既發(fā)揮了遺傳算法收斂速度快、模擬退火算法搜索面廣的優(yōu)點(diǎn),又克服了前者收斂容易早熟而后者收斂速度較慢的問(wèn)題。從而既防止了算法會(huì)陷入局部最優(yōu)解的問(wèn)題,,又提高了算法的收斂速度及搜索效率。 在GASA算法的基礎(chǔ)上,設(shè)計(jì)和實(shí)現(xiàn)了基于Java EE平臺(tái)的分布式數(shù)控系統(tǒng)車(chē)間排產(chǎn)系統(tǒng)。其主要目的是實(shí)現(xiàn)作業(yè)調(diào)度,并對(duì)生產(chǎn)過(guò)程進(jìn)行實(shí)時(shí)控制和管理。該系統(tǒng)是基于B/S架構(gòu)的,系統(tǒng)結(jié)構(gòu)可具體細(xì)分為如下幾層:表現(xiàn)層、Web層、業(yè)務(wù)邏輯層、DAO層、領(lǐng)域?qū)ο髮印?shù)據(jù)庫(kù)服務(wù)層。它綜合使用Struts、Spring和Hibernate框架,具體來(lái)說(shuō),使用Struts框架實(shí)現(xiàn)表現(xiàn)層和Web層,使用Spring框架實(shí)現(xiàn)業(yè)務(wù)邏輯層,使用Hibernate框架實(shí)現(xiàn)數(shù)據(jù)庫(kù)的持久化鏈接。
[Abstract]:With the rapid development and wide application of information technology, the management of enterprises has gradually changed from traditional management to computer management. Production scheduling and scheduling is an important part of manufacturing execution system, which is directly related to the production and management efficiency of enterprises. An effective scheduling scheme can efficiently utilize production resources, reduce production costs and improve the competitiveness of enterprises. Job shop scheduling problem is a very complex problem. In this paper, genetic algorithm and simulated annealing algorithm are studied in detail, combining the advantages of genetic algorithm (GA) and simulated annealing algorithm (SA). A hybrid genetic simulated annealing algorithm (GASA),) is proposed to efficiently solve the job shop scheduling problem. This algorithm not only brings into play the advantages of fast convergence speed of genetic algorithm and wide search range of simulated annealing algorithm, but also overcomes the problem that the former converges prematurely and the latter converges slowly. This not only prevents the algorithm from falling into the problem of local optimal solution, but also improves the convergence speed and search efficiency of the algorithm. Based on GASA algorithm, a distributed NC system workshop scheduling system based on Java EE platform is designed and implemented. The main purpose is to achieve job scheduling and real-time control and management of production process. The system is based on the B / S architecture and can be subdivided into the following layers: presentation layer, business logic layer and Dao layer, domain object layer and database service layer. It uses Struts Spring and Hibernate framework. In particular, it uses Struts framework to implement presentation layer and Web layer, Spring framework to implement business logic layer, and Hibernate framework to implement persistent link of database.
【學(xué)位授予單位】:中國(guó)科學(xué)院研究生院(沈陽(yáng)計(jì)算技術(shù)研究所)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2014
【分類號(hào)】:TP311.52;TB497

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