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Printed circuit board assembly optimization based on genetic algorithm with model constraints of polychromatic sets

机译:基于遗传算法的多色集模型约束的印刷电路板组装优化

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Aimed at the optimization problem of printed circuit board (PCB) assembly workshop (WPCBA) with multiple assembly machines and tasks, combined with polychromatic sets and genetic algorithm (GA), an optimization method is presented to optimize PCB assignment, component allocation and PCB assembly sequence problem simultaneously. On the basis of the polychromatic sets theory, numerical contour matrix is presented to describe the constraint of machine and operation sequence for WPCBA optimization problem and formulate the constraint model. Constraint model guarantees that GA searches optimal result in the effective solution space and simplify the calculation of fitness value. Moreover, if the machine and assembly task are changed, through a simple modification of constraint model, the WPCBA problem would be optimized conveniently. Computational results indicate that the solution efficiency of WPCBA optimization problem can be improved significantly and the dynamical optimization can be implemented.
机译:针对印刷电路板(PCB)组装车间(WPCBA)的优化问题,具有多个装配机器和任务,结合多色组和遗传算法(GA),提出了优化方法以优化PCB分配,组件分配和PCB组件序列问题同时。在多色组理论的基础上,提出了数值轮廓矩阵来描述WPCBA优化问题的机器和操作顺序的约束,并制定约束模型。约束模型保证GA在有效解决方案空间中搜索最佳结果,并简化了适应性值的计算。此外,如果机器和组装任务被改变,通过简单修改约束模型,WPCBA问题将方便地优化。计算结果表明,可以显着提高WPCBA优化问题的解决方案效率,并且可以实现动态优化。

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