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Sensors 2018, 18(8), 2591;

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

State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
Author to whom correspondence should be addressed.
Received: 1 July 2018 / Revised: 27 July 2018 / Accepted: 5 August 2018 / Published: 7 August 2018
(This article belongs to the Special Issue Smart Industrial Wireless Sensor Networks)
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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. View Full-Text
Keywords: SIWRSNs; energy provisioning; manufacturing scheduling; smart factory SIWRSNs; energy provisioning; manufacturing scheduling; smart factory

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Feng, Y.; Wang, Y.; Zheng, H.; Mi, S.; Tan, J. A Framework of Joint Energy Provisioning and Manufacturing Scheduling in Smart Industrial Wireless Rechargeable Sensor Networks. Sensors 2018, 18, 2591.

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