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A Framework of Joint Energy Provisioning and Manufacturing Scheduling in Smart Industrial Wireless Rechargeable Sensor Networks

机译:智能工业无线可充电传感器网络中联合能源供应和制造调度的框架

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摘要

Energy provisioning is always a crucial problem restricting the further development and application of smart industrial wireless sensor networks in smart factories. In this paper, we present that it is necessary to develop smart industrial wireless rechargeable sensor networks (SIWRSNs) in a smart factory environment. Based on the complexity and time-effectiveness of factory operations, we establish a joint optimization framework named J-EPMS to effectively coordinate the charging strategies of wireless sensors and the scheduling plans of machines running. Then, we propose a novel double chains quantum genetic algorithm with Taboo search (DCQGA-TS) for J-EPMS to obtain a suboptimal solution. The simulation results demonstrate that the DCQGA-TS algorithm can maximally ensure the continuous manufacturing and markedly shorten the total completion time of all production tasks.
机译:能源供应始终是一个关键问题,制约了智能工厂中智能工业无线传感器网络的进一步开发和应用。在本文中,我们认为有必要在智能工厂环境中开发智能工业无线可充电传感器网络(SIWRSN)。基于工厂运营的复杂性和时间效率,我们建立了一个名为J-EPMS的联合优化框架,以有效地协调无线传感器的充电策略和机器运行的调度计划。然后,针对J-EPMS提出了一种新的带有禁忌搜索的双链量子遗传算法(DCQGA-TS),以获得次优解。仿真结果表明,DCQGA-TS算法可以最大程度地保证连续生产,并显着缩短了所有生产任务的总完成时间。

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