【摘要】 在当前高强度任务状态下,电装中心生产能力受到诸多因素的制约,通过分析得出制约生产的主要矛盾为多型号任务下发后的车间生产调度瓶颈问题。提出了基于微粒群优化算法(PSO)的车间调度综合解决方案,以电装中心某月生产任务为例,根据算法流程进行了仿真和实际应用。结果表明,该方法能迅速高效地形成车间任务调度计划,特别对于多任务系统,PSO算法确实能给出宏观最优解,得出保证车间所有任务全部完成所需要的最短时间。更多还原

【Abstract】 With the current state of high-intensity tasks, denso center’s capacity is constrained by many factors. The main contradiction of restricting production is the problem of workshop production scheduling bottlenecks under the multi-model task. In this paper, shop scheduling algorithm based on particle swarm optimization(PSO) is proposed, taking a monthly production task of denso center for example, with simulation and practical application of the algorithm flow. The results show that shop scheduling plan can be formed by this method quickly and efficiently, especially for multi-tasking systems, which can really give the macro optimal solution by PSO algorithm, giving the minimum time to guarantee all the tasks are completed.更多还原