CAJ | 학술논문

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。
재당전고강도임무상태하，전장중심생산능력수도제다인소적제약，통과분석득출제약생산적주요모순위다형호임무하발후적차간생산조도병경문제。제출료기우미립군우화산법（PSO）적차간조도종합해결방안，이전장중심모월생산임무위례，근거산법류정진행료방진화실제응용。결과표명，해방법능신속고효지형성차간임무조도계화，특별대우다임무계통，PSO산법학실능급출굉관최우해，득출보증차간소유임무전부완성소수요적최단시간。
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.