云制造环境下分布式3D打印任务调度研究

Research on Distributed 3D Printing Task Scheduling in Cloud Manufacturing Environment

在云制造环境下,针对分布式3D打印任务与3D打印设备资源的供需匹配问题,首先,充分考虑云制造环境下用户订单与3D打印设备资源在空间的异构性以及生产目标要求多样的特征,提出了一种云制造3D打印服务平台,并在此基础上构建了云制造下分布式3D打印任务调度的多目标优化模型,可以实现分布式3D打印任务的时间和成本最优;然后,提出了一种改进非支配排序遗传算法(NSGA-Ⅱ)求解该多目标优化模型,并与传统NSGA-Ⅱ算法进行对比分析,得到包含多个解的Pareto最优解集;最后通过算例仿真验证了其有效性,发现其能够很好地解决云制造环境下的分布式3D打印任务供需匹配问题。

In the cloud manufacturing environment,in order to match the supply and demand of distributed 3D printing tasks and 3D printing equipment resources.Firstly,considering the spatial heterogeneity of user orders and 3D printing equipment resources in cloud manufacturing environment,and the characteristics of diverse production objectives,a cloud manufacturing 3D printing service platform is proposed,and on this basis,a multi-objective optimization model of distributed 3D printing task scheduling in cloud manufacturing is constructed,which can achieve the optimal time and cost of distributed 3D printing tasks;Then,an improved non dominated sorting genetic algorithm(NSGA-Ⅱ)is proposed to solve the multi-objective optimization model.Compared with the traditional NSGA-Ⅱalgorithm,the Pareto optimal solution set containing multiple solutions is obtained.Finally,it is verified by a simulation example in view of its effectiveness,it is found that it can well solve the problem of matching supply and demand of distributed 3D printing tasks in the cloud manufacturing environment.