To cope with the task scheduling problem under multi-task and transportation consideration in large-scale service oriented manufacturing systems(SOMS), a service allocation optimization mathematical model was establis...To cope with the task scheduling problem under multi-task and transportation consideration in large-scale service oriented manufacturing systems(SOMS), a service allocation optimization mathematical model was established, and then a hybrid discrete particle swarm optimization-genetic algorithm(HDPSOGA) was proposed. In SOMS, each resource involved in the whole life cycle of a product, whether it is provided by a piece of software or a hardware device, is encapsulated into a service. So, the transportation during production of a task should be taken into account because the hard-services selected are possibly provided by various providers in different areas. In the service allocation optimization mathematical model, multi-task and transportation were considered simultaneously. In the proposed HDPSOGA algorithm, integer coding method was applied to establish the mapping between the particle location matrix and the service allocation scheme. The position updating process was performed according to the cognition part, the social part, and the previous velocity and position while introducing the crossover and mutation idea of genetic algorithm to fit the discrete space. Finally, related simulation experiments were carried out to compare with other two previous algorithms. The results indicate the effectiveness and efficiency of the proposed hybrid algorithm.展开更多
掘进机回转台在截割煤岩时承受偏载荷及强冲击作用,其性能影响掘进机的工作效率及安全性。为探究掘进机回转台疲劳寿命的影响因素及最佳服役参数,提出了一种基于Kriging代理模型和DEM-MFBD(discrete element model-multi flexible body ...掘进机回转台在截割煤岩时承受偏载荷及强冲击作用,其性能影响掘进机的工作效率及安全性。为探究掘进机回转台疲劳寿命的影响因素及最佳服役参数,提出了一种基于Kriging代理模型和DEM-MFBD(discrete element model-multi flexible body dynamics,离散单元法-多柔性体动力学)双向耦合技术的回转台疲劳寿命预测方法。首先,建立了掘进机截割部与回转台的空间受力模型,明确了截割部与回转台的受力规律。然后,联合RecurDyn与EDEM软件对回转台进行双向刚柔耦合动力学仿真分析,获得了回转台在工作状态下的应力分布。最后,利用拉丁超立方抽样法选取15组掘进机服役参数作为输入,以回转台疲劳寿命为响应,建立了对应的Kriging代理模型,并利用粒子群优化算法对代理模型进行寻优,得到了回转台在最佳服役参数下的疲劳寿命。结果表明,当掘进机的截割头转速为54 r/min、回转台横摆速度为1.003 m/min、截割臂垂直摆角为7°时,回转台的疲劳寿命最长。结合DEM-MFBD双向耦合技术、Kriging代理模型与粒子群优化算法来探究掘进机的最佳服役参数,可为回转类部件的优化设计提供新思路。展开更多
基金Project(2012B091100444)supported by the Production,Education and Research Cooperative Program of Guangdong Province and Ministry of Education,ChinaProject(2013ZM0091)supported by Fundamental Research Funds for the Central Universities of China
文摘To cope with the task scheduling problem under multi-task and transportation consideration in large-scale service oriented manufacturing systems(SOMS), a service allocation optimization mathematical model was established, and then a hybrid discrete particle swarm optimization-genetic algorithm(HDPSOGA) was proposed. In SOMS, each resource involved in the whole life cycle of a product, whether it is provided by a piece of software or a hardware device, is encapsulated into a service. So, the transportation during production of a task should be taken into account because the hard-services selected are possibly provided by various providers in different areas. In the service allocation optimization mathematical model, multi-task and transportation were considered simultaneously. In the proposed HDPSOGA algorithm, integer coding method was applied to establish the mapping between the particle location matrix and the service allocation scheme. The position updating process was performed according to the cognition part, the social part, and the previous velocity and position while introducing the crossover and mutation idea of genetic algorithm to fit the discrete space. Finally, related simulation experiments were carried out to compare with other two previous algorithms. The results indicate the effectiveness and efficiency of the proposed hybrid algorithm.
文摘掘进机回转台在截割煤岩时承受偏载荷及强冲击作用,其性能影响掘进机的工作效率及安全性。为探究掘进机回转台疲劳寿命的影响因素及最佳服役参数,提出了一种基于Kriging代理模型和DEM-MFBD(discrete element model-multi flexible body dynamics,离散单元法-多柔性体动力学)双向耦合技术的回转台疲劳寿命预测方法。首先,建立了掘进机截割部与回转台的空间受力模型,明确了截割部与回转台的受力规律。然后,联合RecurDyn与EDEM软件对回转台进行双向刚柔耦合动力学仿真分析,获得了回转台在工作状态下的应力分布。最后,利用拉丁超立方抽样法选取15组掘进机服役参数作为输入,以回转台疲劳寿命为响应,建立了对应的Kriging代理模型,并利用粒子群优化算法对代理模型进行寻优,得到了回转台在最佳服役参数下的疲劳寿命。结果表明,当掘进机的截割头转速为54 r/min、回转台横摆速度为1.003 m/min、截割臂垂直摆角为7°时,回转台的疲劳寿命最长。结合DEM-MFBD双向耦合技术、Kriging代理模型与粒子群优化算法来探究掘进机的最佳服役参数,可为回转类部件的优化设计提供新思路。
