提出问题用计算机求解论文,流水调度问题的启发式求解-计算机应用技术专业论文.docx...

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文章标签：提出问题用计算机求解论文

蹬尔滨理王大学工学硕士学整论文流水调度问题的启发式求解

蹬尔滨理王大学工学硕士学整论文

流水调度问题的启发式求解

摘要

以总完工时间为目标的Flow shop调度问题是一个重要的制造加工系统，广泛应用于王业环境中。流水调度是很多实际流水线生产调度润题的筵化模型，也是一类典型的NP完全问题，已被证明在多项式时间内得不到最优值。该问题是生产管理中的核心问题，好的求解方法可以促进企业提高生产率。因此，该研究无论从理论还是实际都有重要意义。近年来，对于流水

调度问题的求解主要有启发式算法和元启发式算法，但各有其不足之处：元寤发式方法豹运行时间长，可获{!譬较好的解，但其鳃不稳定；窟发式方法可在较短的时间内得到鲁棒性较强的解，但是极少获得较优的解。为了更好地解决流水调度问题，提出两个相应的启发式算法，从优解性和实时性薅个方面与现有的算法进行比较，大量试验结果表明该方法能有效求解所考虑的流水调度问题。

针对以总完王时闻失优化蟊标的流水作业调度闷题，提建基于局都插入和全局插入方法的双插入启发式算法lip和RT。RP和RT算法与目前求解流水调度问题最好的启发算法有RZ、WY、FL在1700个实例上进行比较。试验表明，RP帮RT算法具有最好的性能，在最好调度翡获取施力、所得调度的平均质量及所得调度的稳定性方面，RID和RT算法均是最优的。RP期RT能够更有效地解决以总完工时间最小为基标的Flow Shop调度问题。

关键词流水调度；雇发式算法；总完工时闻

哈尔滨理工大学工学硕士学位论文

Heuristics for Flow Shop Scheduling Problem

Abstract

Flow shop scheduling problem with total flowtime minimization is an important manufacturing system widely existing in industrial environments．Flow shop scheduling is the simplified model of many actual productions．And flow shop scheduling is a typically NP—complete problem，which means that it is impossible to find the global optimum in polynomial complexity．It is one of the key problem in the production management．Good algorithms for this problem can promote productivity of enterprises．So the study of flow shop scheduling plays an important role on theory and practice．In recent years，meta-heuristics and heuristics arc two kinds of algorithm for flow shop problem．However,they are different in CPU-time and performance．Meta-heuristics can always obtain

better solutions than heuristics but they need much more CPU—times．As well，

robustness of heuristics is good but optimum can seldom be obtained．To beRer solve problem,two heuristics are proposed．The proposed heuristics are compared研tIl the existing ones in both efficiency and effectiveness．The

experimental results show that the proposed heuristics can solve the considered

problem effectively and efficiently．

Two new composite heuristic RP and RT are designed for flow shop

scheduling problem to minimize tot