本文選題：混合流水車間調度 + 資源約束　； 參考：《電子科技大學》2012年碩士論文

【摘要】：本論文的研究基于四川省青年基金項目“面向迂回生產流程的多目標生產規(guī)劃研究”（批準號：09ZQ026-054）�；旌狭魉囬g調度(Hybrid Flow Shop Scheduling,HFSS)問題是兩類經典調度問題Flow Shop和并Parallel Shop的推廣，相比之下，HFSS問題要求在整個加工流程中，至少有一個階段具有兩臺及以上的并行機器，屬于較為復雜的NP-Hard難題。此類問題至少需要同時解決兩個問題：各工件的加工順序以及各工件在各加工階段加工機器的分配情況。針對目前國內外車間調度的研究現(xiàn)狀以及存在的實際問題，本文重點研究了考慮資源約束的混合流水車間調度問題以及具有預防性維修的資源約束混合流水車間調度問題。 針對混合流水車間稀缺資源約束的調度問題，將稀缺資源約束對最小化最大完工時間(makespan)的影響考慮到目標函數(shù)中建立了基于資源約束的數(shù)學規(guī)劃模型，有效的解決了多臺并行機因競爭稀缺資源而造成的時延等待、設備利用率低的調度問題。由于傳統(tǒng)遺傳算法存在早熟收斂的不足，提出采用NEH啟發(fā)式算法產生初始種群的改進遺傳算法。實例仿真結果表明，在此模型下，改進的遺傳算法較傳統(tǒng)遺傳算法能更好的解決有限稀缺資源約束的混合流水車間調度問題。 在生產過程中，由于需要定期對設備進行預防性維修，因此需考慮設備預防性維修對車間調度的影響。本文在建考慮資源約束調度模型的基礎上，將預防性維修與稀缺資源等待對工序起始加工時間的影響考慮到目標函數(shù)中，建立具有預防性維修的資源約束混合流水車間調度模型，該模型能夠滿足合理優(yōu)化配置有限資源以及定期對設備進行預防性維修的同時，使得設備利用率最高，生產周期最短。為解決此類復雜約束調度問題，本文提出新的啟發(fā)式規(guī)則，結合遺傳算法對調度模型進行求解。通過實例驗證，改進的算法能夠取得較好的調度方案。 同時，本文通過收集某風電葉片制造廠實際車間數(shù)據(jù)，，對文中所提出的兩類調度模型分別與傳統(tǒng)調度模型作對比，通過計算各項調度指標，驗證了本文所建模型能夠很好的解決稀缺資源約束及統(tǒng)籌優(yōu)化設備預防性維修與調度的問題，達到提高資源利用率、縮短生產周期的目的。
[Abstract]:The research of this thesis is based on Sichuan Youth Foundation Project "Multi-objective production Planning for circuitous production process" (Grant No.: 09ZQ026-054). Hybrid flow shop scheduling (HFSS) problem is a generalization of two classical scheduling problems, flow Shop and parallel Shop. In contrast, HFSS problem requires that there are at least two parallel machines in one stage in the whole process. It belongs to the more complicated NP-Hard problem. This kind of problem needs to solve at least two problems simultaneously: the processing order of each workpiece and the distribution of each workpiece in each processing stage. In view of the current situation and practical problems of job shop scheduling at home and abroad, this paper focuses on the hybrid flow-shop scheduling problem with resource constraints and the resource-constrained hybrid flow-shop scheduling problem with preventive maintenance. In order to solve the scheduling problem of resource constraints in mixed flow shop, a mathematical programming model based on resource constraints is established by taking into account the influence of scarce resource constraints on minimizing the maximum completion time (makespan). It effectively solves the problem of delay waiting caused by competing for scarce resources and low utilization of equipment on many parallel machines. Because the traditional genetic algorithm has the deficiency of premature convergence, an improved genetic algorithm using NEH heuristic algorithm to generate initial population is proposed. The simulation results show that the improved genetic algorithm is better than the traditional genetic algorithm in solving the mixed flow shop scheduling problem with limited scarce resource constraints. In the process of production, the preventive maintenance of equipment is required, so it is necessary to consider the influence of preventive maintenance on workshop scheduling. Based on the resource constrained scheduling model, the effects of preventive maintenance and scarce resource waiting on the process starting processing time are taken into account in the objective function in this paper. A resource constrained hybrid flow shop scheduling model with preventive maintenance is established. The model can meet the requirements of rational allocation of limited resources and periodic preventive maintenance of the equipment, which makes the equipment utilization rate highest and the production cycle shortest. In order to solve this kind of complex constrained scheduling problem, a new heuristic rule is proposed in this paper, and a genetic algorithm is used to solve the scheduling model. An example shows that the improved algorithm can achieve a better scheduling scheme. At the same time, by collecting the actual workshop data of a wind turbine blade factory, the two kinds of scheduling models proposed in this paper are compared with the traditional scheduling models, and each scheduling index is calculated. It is verified that the proposed model can solve the problem of scarce resource constraints and optimize the preventive maintenance and scheduling of equipment as a whole to improve the utilization of resources and shorten the production cycle.
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：TH186

【參考文獻】

相關期刊論文 前10條

1 寧維巍;雷毅;仲華惟;閆光榮;;無等待排列流水車間提前/延期調度問題[J];北京郵電大學學報;2009年06期

2 馬佳;高立群;石剛;李丹;;求解柔性作業(yè)車間調度問題的免疫遺傳算法[J];東北大學學報(自然科學版);2008年07期

3 李波;吳志明;王強;;多產品半柔性并聯(lián)生產線預防性維修調度模型研究[J];電子科技大學學報;2011年05期

4 周炳海;蔣舒宇;王世進;吳斌;奚立峰;;集成生產與預防性維護的流水線車間調度算法[J];大連海事大學學報;2007年03期

5 孫志峻,朱劍英;雙資源作業(yè)車間智能優(yōu)化調度[J];東南大學學報(自然科學版);2005年03期

6 曹政才;余紅霞;喬非;;基于Petri網與遺傳算法的半導體生產線建模與優(yōu)化調度[J];電子學報;2010年02期

7 唐大志;;用Hopfield神經網絡解決作業(yè)車間調度問題[J];遼寧工程技術大學學報;2004年S1期

8 雷衛(wèi)東;車阿大;;帶時間窗口的自動化混流生產線調度方法[J];工業(yè)工程;2011年05期

9 金玉蘭;蔣祖華;;預防性維修計劃和生產調度的多目標優(yōu)化[J];哈爾濱工程大學學報;2011年09期

10 劉曉霞;謝里陽;崔敬巍;;雙資源生產車間調度問題的研究[J];計算機工程與應用;2007年06期

相關博士學位論文 前3條

1 曾強;離散制造企業(yè)批量生產車間調度智能優(yōu)化研究[D];重慶大學;2010年

2 張超勇;基于自然啟發(fā)式算法的作業(yè)車間調度問題理論與應用研究[D];華中科技大學;2007年

3 蔡蘭;制造業(yè)車間生產調度及其評估理論的研究和應用[D];武漢理工大學;2008年

相關碩士學位論文 前1條

1 劉捷;不確定條件下基于遺傳算法的柔性作業(yè)車間調度問題研究[D];華中科技大學;2009年

本文編號：2112893