一种改进的遗传算法在车间调度中的应用

研究现代生产先进制造车间调度问题 ,对于发挥先进制造车间的高效性和灵活性具有十分重要的意义。生产过程的计划调度问题 ,是实现制造系统运筹技术、管理技术与优化技术的核心。因此 ,优化调度算法的性能直接影响到FMS的生产效率和应变能力。本文在传统的遗传算法的基础上 ,对车间调度算法进行了深入的研究。基于机床负荷平衡的思想 ,提出了面向先进制造车间的平衡遗传算法 ,并与传统的遗传调度算法进行了对比。实验表明 ,该调度方法具有较高的可行性、有效性和稳定性。保证了各个机床的负荷平衡 ,满足了交付期的要求

Application of An Improved Genetic Algorithm for Shop Floor Scheduling

It is very important to study the scheduling problems in advanced manufacturing shop floor(AMSF) community for fully exerting AMSF's high efficiency and flexibility. The planning and scheduling in production processing are principle problems for the development of operation, management and optimization techniques in manufacturing system. The production efficiency and flexibility of FMS is influenced directly by the capability of optimal scheduling algorithm. In this paper, the shop floor scheduling algorithm is studied. Based on the idea of machine's load balance, the Balance Genetic Algorithm (BGA) for AMSF is presented. Compared with the traditional GA, the simulations show that this method has the high feasibility, validity and stability.It balances the machine's load and meets the delivery time.