数控机床与机器人一体化车间多目标优化布局

Equipment Layout Multi-object Optimization of Machine Tool & Robot Integrated Workshop

为降低一体化生产车间的物流运输费用和减少设备占用面积,提出了组合变异多种群遗传算法的设备布局优化方法。对数控机床与机器人的一体化车间设备布局问题进行了抽象,以物流费用最少和占用面积最小为目标,建立了车间设备布局问题的优化模型。根据交叉和变异参数对算法的影响,通过设置不同算法参数实现不同搜索策略倾向;为了深化局部搜索能力,给出了随机数调节的组合变异策略,从而提出了组合变异多种群遗传算法的模型求解方法。经验证,组合变异多种群遗传算法的搜索能力强于标准遗传算法;加入机器人后,工件物流费用减少了15.85%,对设备的包络长度减少了6.64%,说明了机器人加入生产车间的经济性与合理性。

In order to lower logistics transportation expenses and reduce equipment occupying area, equipment layout optimization method based on combined mutation multi-population genetic algorithm is proposed. Equipment layout optimization problem of integrated workshop is abstracted, and the optimal model of workshop equipment layout problem is built by setting the goal of lowering logistics expense and reducing occupying area. Depending on crossover and mutation parameters influence on algorithm property, different parameters value is setting to realize different searching strategy. To deepen local searching ability, combined mutation strategy adjusting by random number is provided, so that model solving method based on combined mutation multi-population genetic algorithm is put forward. It is clarified that searching ability of combined mutation multi-population genetic algorithm is optimal to standard genetic algorithm. After robot joining in producing system, workpiece logistics expense decreases by 15.85%, and the length of envelop for equipment decreases by 6.64%, which shows that economy and rationality of robot joining in production system.