【作者】 王芳；

【导师】 房亚东；

【作者基本信息】 西安工业大学 ， 机械制造及其自动化， 2013， 硕士

【摘要】 目前在关于多品种、变批量的作业车间调度研究中,很少考虑资源配置这一环节,现有的方法并没有很好地解决离散制造系统中所面临的一些实际生产问题。本文采用多色粒子群算法将车间的资源配置和作业调度这两个问题综合进行考虑,快速、有效地解决了制造资源的合理配置和调度方案的优化问题,完全达到了优化生产调度的目的。先阐述了车间制造资源配置问题,介绍了解决制造资源配置时所用到的多色集合理论。接着描述了生产车间的调度问题,详细叙述了本文选取的优化调度方案的粒子群智能算法,并且在软件中将此实现过程进行仿真模拟。利用多色粒子群算法解决单目标作业车间调度问题。针对车间设备资源管理和配置的特点,应用多色理论,建立资源关联图模型。对作业任务需要的加工设备进行分配,推导出工序集所有可行的资源配置集合。然后用粒子群算法优化调度方案,以最大完工时间最小为优化目标,选择基于工序的编码方式,构建了求解单目标作业车间调度问题的方法,并通过实例验证了算法的收敛性及有效性。在单目标基础之上解决多目标作业车间调度问题。叙述了解决多目标作业车间调度问题的相关数学理论。对多目标作业车间调度实例进行研究,用粒子群算法对多目标作业车间调度方案进行优化,并和传统算法比较,得出粒子群算法在解决多目标作业车间调度问题时具有较强的优化能力。结合以上的研究内容,开发了一个计算机辅助的车间生产管理系统。对实现系统的关键技术、建模过程和主要功能模块进行介绍,给出了主要实现界面。更多还原

【Abstract】 At present, the researches about multi-specification and small-batch job shop scheduling rarely consider resource allocation problem, the existing methods is no good solution to actual production problems of discrete manufacturing systems are facing. The paper considers resource reconfiguring and job-shop scheduling in the matching machining process based on polychromatic particle swarm algorithm. It quickly and effectively deploys manufacturing resource and optimizing scheduling program to meet the purpose of optimizing production.First, this chapter describes workshop manufacturing resource configuration, polychromatic sets theory is introduced for allocating manufacturing resource, then it describes the job shop scheduling problem. Finally, particle swarm intelligence algorithm of the paper is detail introduced for optimization job shop scheduling, and this implementation process is simulated in software.It uses polychromatic particle swarm algorithm to solve the single-objective job shop scheduling problem. Paper uses polychromatic sets theory to establishing the mode of equipment allocation according to management and configuration features of workshop equipment resource. Separating equipment in the light of tasks and gains corresponding resource set. Then the particle swarm algorithm is used to changes scheduling scheme, the optimization goal is minimum makespan with process-based encoding, paper builds the method of solving the single-objective job shop scheduling problem, and verifying the convergence and effectiveness of the algorithm by an example.Multi-objective job shop scheduling problem is solved based on single objective. Then narratives related mathematical theory of solving multi-objective job shop scheduling problems. The last researches example of multi-objective job shop scheduling and using particle swarm algorithm optimization, and comparison result with the traditional algorithm that obtain strong optimization capability of particle swarm algorithm to resolve multi-objective job shop scheduling.Combination the above research, it develops workshop production management system of computer-aided. The key technology, modeling process and main function modules are introduced, and shows the interface of main achievement.更多还原