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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。
Under the current state of high-intensity tasks, the production capacity of electrical installation center is restricted by many factors. The main contradiction that restricts production is the bottleneck of production scheduling after the release of many types of tasks. Based on Particle Swarm Optimization (PSO), an integrated solution to the shop scheduling problem was proposed. Taking a certain production task of the electrical installation center as an example, the simulation and practical application were carried out according to the algorithm flow. The results show that this method can quickly and efficiently form a shop scheduling schedule. Especially for multi-tasking systems, the PSO algorithm can indeed give the macro-optimal solution, and the shortest time required to ensure all the tasks in the shop is completed.