机械设备维修区域资源优化调度仿真
发布时间：2019-02-18 07:29
【摘要】：对机械设备的维修区域进行资源优化调度,能够有效提高机械设备的工作时间。对机械设备的维修区域资源的优化调度,需要先增强全局搜索能力,利用排斥项避免种群搜索进程的早熟收敛,完成机械设备维修区域资源优化调度。传统方法利用遗传操作算子对编码方案进行改进,采用遗传操作算子精英保留策略构造最优解集,但忽略了搜索进程的早熟收敛,导致调度精度偏低。提出基于粒子群优化的机械设备维修资源优化调度方法。上述方法给出机械设备维修资源分配问题的目标函数,将资源调度问题分解为静态和动态维修任务调度问题,组建机械设备维修资源优化调度模型,结合粒子群优化理论对模型进行求解,利用排斥项避免种群搜索进程的早熟收敛,以获得的全局最优解为依据完成机械设备维修资源优化调度。实验结果表明,所提方法能够有效提升机械设备维修资源优化调度效率。
[Abstract]:The optimal scheduling of mechanical equipment maintenance area can effectively improve the working time of mechanical equipment. In order to optimize the maintenance area resources of mechanical equipment, the global search ability should be enhanced first, and the precocious convergence of the population search process should be avoided by using exclusions to complete the optimal scheduling of regional resources for mechanical equipment maintenance. The traditional method uses genetic operator to improve the coding scheme, and adopts the elite retention strategy of genetic operator to construct the optimal solution set, but neglects the precocious convergence of the search process, which leads to the low scheduling accuracy. An optimal scheduling method for mechanical equipment maintenance resources based on particle swarm optimization (PSO) is proposed. The objective function of mechanical equipment maintenance resource allocation problem is given in the above method. The resource scheduling problem is decomposed into static and dynamic maintenance task scheduling problems, and the optimal scheduling model of mechanical equipment maintenance resources is established. Based on the particle swarm optimization theory, the model is solved to avoid the premature convergence of population search process, and the optimal scheduling of mechanical equipment maintenance resources is completed based on the obtained global optimal solution. Experimental results show that the proposed method can effectively improve the efficiency of optimal scheduling of mechanical equipment maintenance resources.
【作者单位】： 辽宁工程技术大学电气与控制工程学院;
【分类号】：TH186;TP18
本文编号：2425601
[Abstract]:The optimal scheduling of mechanical equipment maintenance area can effectively improve the working time of mechanical equipment. In order to optimize the maintenance area resources of mechanical equipment, the global search ability should be enhanced first, and the precocious convergence of the population search process should be avoided by using exclusions to complete the optimal scheduling of regional resources for mechanical equipment maintenance. The traditional method uses genetic operator to improve the coding scheme, and adopts the elite retention strategy of genetic operator to construct the optimal solution set, but neglects the precocious convergence of the search process, which leads to the low scheduling accuracy. An optimal scheduling method for mechanical equipment maintenance resources based on particle swarm optimization (PSO) is proposed. The objective function of mechanical equipment maintenance resource allocation problem is given in the above method. The resource scheduling problem is decomposed into static and dynamic maintenance task scheduling problems, and the optimal scheduling model of mechanical equipment maintenance resources is established. Based on the particle swarm optimization theory, the model is solved to avoid the premature convergence of population search process, and the optimal scheduling of mechanical equipment maintenance resources is completed based on the obtained global optimal solution. Experimental results show that the proposed method can effectively improve the efficiency of optimal scheduling of mechanical equipment maintenance resources.
【作者单位】： 辽宁工程技术大学电气与控制工程学院;
【分类号】：TH186;TP18
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