摘 要随着近一个世纪的科学技术的发展，企业对其生产与管理模式的不断改进已经成为了一个重要性的问题，而生产调度问题在该方面则显得尤为重要。生产调度问题广泛存在于各个行业之中，如食品加工行业，纺织业，制药业等。而带有阻塞区域的车间流水调度问题显示更有代表意义。该问题可以应用于不同行业之中，例如机器加工产业可以利用该问题选择不同工件的加工顺序，石化产业可以选取不同工序的流程等。该问题的研究价值在现实生活中显得越来越重要。87127

本文针对阻塞流水车间调度问题提出了一种以最小化最大完工时间为目标的人工蜂群算法。本算法在初始化阶段采用了启发式算法的概念对初始数据进行随机处理，从而用来提高初始解的质量。在该蜂群算法的雇佣蜂阶段，引入了交叉、变异、局部重构等方法，对某个已知解进行一次或多次处理，进一步增强了该算法对解集的优化能力。跟随蜂阶段则处理由雇佣蜂传递过来的信息，利用随机解的迭代处理增强了对解的处理能力，同时也保证了解在一定区间内的优势性。侦查蜂阶段则防止解集陷入局部最优解，并对解进行领域扰动增强多样性。最终算法通过多次迭代产生最优序列。

针对之前学者研究的数据，对提供的m个工件，n台机器（m，n可变）的加工数据进行实验测试，通过对变量的控制变化，证明了该算法在小型区间内的可行性。

毕业论文关键词：蜂群算法；最大完工时间；迭代处理；局部最优

Abstract With the development of science and technology in the last century, the continuous improvement of production and management mode of enterprises has become an important issue, and the production scheduling problem is particularly important。 Production scheduling problem is widely existed in various industries, such as food processing industry, textile industry, pharmaceutical industry and so on。 The shop flow scheduling problem with blocking area shows more representative。 The problem can be used in different industries, such as machine processing industry can use the problem to choose different parts of the processing sequence, the petrochemical industry can choose different processes, such as processes。 The research value of this problem is becoming more and more important in real life。

In this paper, an artificial bee colony algorithm based on the makespan for the blocking flow shop scheduling problem is proposed。 This algorithm adopts the concept of heuristic algorithm to deal with the initial data in the initialization stage。 So as to improve the quality of the initial solution。 In the bee colony algorithm employed bees stage and introduces the cross, variation, partial reconfiguration method, once or several times for a known solution, further enhancing the solution set of optimization ability of the algorithm。 In the process of the following bees, the information that is transferred by the employment bees is processed, and the processing ability of the solution is enhanced by the iterative process of the random solution。 During the period of the criminal investigation, the solution set is prevented from falling into the local optimal solution, and the solution is enhanced by the field disturbance。 The final algorithm produces the optimal sequence through multiple iterations。 

Finally, according to the data provided by the mentor m, n machine (m, n variable), the experimental test, through the control of variables change, it is proved that the algorithm in a small range of practicality。

Keywords:Bee Colony Algorithm; Makespan; Iterative Processing; Local Optimum

目 录

第一章 绪论 1

1。1 研究背景