多加工路径柔性作业调度方法

为了提高企业生产效率,降低生产成本,以仪器仪表制造业为背景,针对某企业流量计生产车间的特点,建立优化目标函数,提出了多加工路径柔性作业车间调度模型(MPFJSP)。为了避免该模型中非可行解的干扰,采用新的顺序编码方式和在非可行解周围搜索可行解并代替之的方法;且为提高收敛速度,将粒子分为若干小段分别更新和扰动,以保留优秀基因,由此形成分段多目标粒子群优化算法(PMOPSO)。通过算法对比,发现所提方法能在工件的每一条加工路径中寻优,验证了其性能更优越,也验证了MPFJSP相对于传统柔性作业车间调度(FJSP)更灵活,得到的解也更优,在流量计生产车间的实验性生产中,违约成本约下降了12%,生产效率提升约10%。

Multi processing path flexible job scheduling method

In order to improve the production efficiency and reduce the production cost, in this paper, taking instrument and meter manufacturing industry as the background, aiming at the characteristics of a certain flow meter production workshop, we establish the optimization objective function, propose a multi processing path FJSP (MPFJSP) model. In order to avoid the interference of the non feasible solutions in the model, we adopt a new sequential encoding mode and a new method that searches the feasible solution nearby the non feasible solution and then replaces the non feasible solution. In order to improve the convergence speed, the particles are divided into a number of small segments, which are updated and disturbed respectively, and the excellent gene is reserved; thus, the PMOPSO algorithm is formed. Compared with other algorithms, the proposed algorithm could find the optimum machining path in every machining path of the workpiece, which verifies the superior performance of the algorithm; it is also verifies that the MPFJSP is more flexible than traditional FJSP, and the obtained solution is better. In the experimental production of the flow meter production workshop, the default cost is decreased by about 12%, and the production efficiency is improved by about 10%.