拆卸线平衡问题的人工蜂群算法研究及其应用

发布时间：2018-05-10 23:31

本文选题：拆卸线平衡问题 + 多目标优化　；参考：《西南交通大学》2014年硕士论文

【摘要】：资源短缺和环境污染是当今社会发展面临的两大难题,旧产品回收再利用,是解决这两大难题的有效的方法之一。当今中国每年产生几千万件的废旧电器,面对如此大规模废旧产品的拆卸,拆卸线是最高效的组织形式。因此,对拆卸线平衡问题的研究具有重要意义。拆卸线平衡问题是一个NP问题,基于仿生原理的人工蜂群算法具有明显的优势。本文研究课题结合国家自然科学基金项目(51205328),对拆卸线平衡问题的人工蜂群算法展开研究。标准人工蜂群算法收敛慢,易陷入局部最优。因此,本文提出一种改进的人工蜂群算法求解拆卸线平衡问题。本文的改进措施主要包括以下四个方面：(1)在生成初始解时,加入任务危害和需求因素的影响,提高初始解在危害和需求方面的质量；(2)设计一种由局部最优解和当前解调节的可变步长,加强对近优解的搜索力度,加速淘汰质量差、优化慢的解；(3)为观察蜂设计一种蠕动的搜索策略,针对有危害和高需求的任务向前做微小的移动搜索,增强其对后续目标的优化能力；(4)将嵌入衰减操作的分布估计算法引入侦察蜂的搜索策略,改进为向较优解中任务与位置对应关系学习的启发式搜索和全局随机并用的策略,有效的改善了侦察蜂的搜索质量。完善算法流程,设定相关参数,用MATLAB将算法程序化。用改进的人工蜂群算法求解大量不同规模和特点的实例,如复杂优先关系、多种拆卸方向、非确定拆卸时间等。并与标准人工蜂群算法和文献中的一些算法进行对比,结果表明所提算法对小规模算例均能快速找到最优解,对大规模算例优化结果要好于文献的结果,验证了算法的有效性。在本文第五章用改进算法对某企业的实际拆卸生产案例进行优化,得到了比原方案更好的结果,提高了拆卸线的平衡率和生产率,充分表明了本文工作的实际意义。
[Abstract]:The shortage of resources and environmental pollution are two major problems facing the social development nowadays. The recycling and reuse of old products is one of the effective methods to solve these two problems. Tens of millions of used electrical appliances are produced every year in China. The disassembly line is the most efficient organization form in the face of the disassembly of such large scale used products. Therefore, the study of disassembly line balance is of great significance. The disassembly line balance problem is a NP problem, and the artificial bee colony algorithm based on bionic principle has obvious advantages. In this paper, the artificial bee colony algorithm for the disassembly line balance problem is studied in conjunction with the National Natural Science Foundation of China (NSFC) project No. 5120 5328. Standard artificial bee colony algorithm is easy to fall into local optimum because of its slow convergence. Therefore, an improved artificial bee colony algorithm is proposed to solve the disassembly line balance problem. The improvement measures in this paper mainly include the following four aspects: 1) when the initial solution is generated, the influence of task harm and demand factors is added. Improve the quality of the initial solution in terms of harm and demand) Design a variable step size adjusted by the local optimal solution and the current solution, strengthen the search for the near optimal solution, and accelerate the elimination of the poor quality. The slow solution 3) designed a peristaltic search strategy for observation bees, making tiny moving searches forward for hazardous and demanding tasks. In order to enhance its ability to optimize the subsequent target, the distribution estimation algorithm with embedded attenuation operation is introduced into the search strategy of the reconnaissance bee, which is improved as a heuristic search strategy to learn from the corresponding relationship between the task and the position in the optimal solution and a strategy of global random use. Effectively improves the search quality of reconnaissance bees. Improve the algorithm flow, set relevant parameters, and use MATLAB to program the algorithm. The improved artificial bee colony algorithm is used to solve a large number of examples of different scales and characteristics, such as complex precedence relations, multiple disassembly directions, uncertain disassembly time and so on. Compared with the standard artificial bee colony algorithm and some algorithms in literature, the results show that the proposed algorithm can quickly find the optimal solution for small scale examples, and the optimization results for large scale examples are better than those in literature, and the validity of the proposed algorithm is verified. In the fifth chapter, an improved algorithm is used to optimize the actual disassembly production case of an enterprise. The results are better than that of the original scheme, and the balance rate and productivity of the disassembly line are improved, which fully shows the practical significance of the work in this paper.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP18;TH186

【参考文献】