【作者】 刘华；

【导师】 顾幸生；

【作者基本信息】 华东理工大学 ， 控制科学与工程， 2013， 硕士

【摘要】 调度问题的本质是一个合理分配资源的过程,也就是将有限的资源分配给多个不同的目标,从而优化一个或多个目标。优化的生产调度方案,可以提高企业的生产效率、降低生产成本,从而为企业带来经济效益。流水线调度问题是生产调度中的主要类型,越来越受到广大学者的重视。本文对基本的人工蜂群算法进行了改进并把它应用在流水线调度问题中,取得了不错的效果。论文的主要贡献如下：(1)针对人工蜂群算法存在的不足,通过引入局部搜索和混沌思想,提出了一种改进的人工蜂群算法(IABC),并通过标准测试函数对它进行测试,仿真实验表明IABC相对基本的人工蜂群算法而言具有较好的全局搜索能力并能更容易跳出局部最优,并且有更快的收敛速度。(2)在分析了置换流水线调度问题以及它的数学模型后,把提出的IABC算法应用在置换流水线调度问题中。采用基于工件的编码,并利用SPV规则实现了连续域和离散域的映射,并利用NEH启发式算法对解进行初始化优化了解的质量。仿真表明IABC算法在优于基本人工蜂群算法和粒子群算法。(3)针对批量流水线调度问题的特点,提出了一种离散的人工蜂群算法(DABC)。 DABC算法采用基于工件的编码,并在蜂群算法的基础上引入了NEH和局部搜索的思想。NEH启发式算法的引入能提高解的初始化质量,Local search的引入能增强算法的局部寻优能力。仿真实验表明DABC算法在求解批量流水线调度问题时具有优越性。更多还原

【Abstract】 The nature of the scheduling problem is the process of a rational allocation of resources. The aim of scheduling is allocate the limited resources to multiple targets to optimize one or more objectives. Optimized production scheduling scheme can improve production efficiency> reduce production cost and economic benefits for the company. The flowshop problem is one of the main types of production scheduling and attracts more attention from many scholars. At this thesis, we improved the basic ABC,applying it to flowshop problem and the results turn out to be better. The main contributions of this dissertation are listed below.(1) In order to overcome the shortcomings of ABC, we introduce the improved ABC with local search and chaos. By testing standard function, we know that the convergence rate and the ability of global search and escaping from local optima are better than ABC.(2) After the analysis of the permutation flowshop, we apply IABC to permutation flowshop. Use the SPV rules to connect the continuous and discrete domain based on the coding of job permutation and initialize the solution with NEH. The simulation results show that IABC is better than ABC and PSO.(3) Thinking of the characteristics of lot-streaming flowshop, we introduce a discrete artificial bee colony algorithm. The DABC use the coding of job permutation and have the idea of local search and NEH. The NEH heuristic algorithm can improve the quality of initialized solution and local search can enhance the ability of searching the optimum. The simulation results show that the DABC is better.更多还原