Fast Non-dominated Sorting Genetic Algorithm with Three Crossover Individuals for Network Topology Optimization in Industrial Internet of Things

2019 ◽  
Author(s):  
Fanrong Kong ◽  
Yan Huang ◽  
Maoqing Zhang
Keyword(s):  
Genetic Algorithm ◽  
Topology Optimization ◽  
Internet Of Things ◽  
Network Topology ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Network Topology Optimization

scholarly journals Fast Nondominated Sorting Genetic Algorithm II with Lévy Distribution for Network Topology Optimization

2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Maoqing Zhang ◽  
Lei Wang ◽  
Zhihua Cui ◽  
Jiangshan Liu ◽  
Dong Du ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Topology Optimization ◽  
Network Topology ◽  
Optimization Problems ◽  
Selection Strategy ◽  
Nsga Ii ◽  
Comparison Results ◽  
Practical Engineering ◽  
Network Topology Optimization ◽  
Nondominated Sorting

Fast nondominated sorting genetic algorithm II (NSGA-II) is a classical method for multiobjective optimization problems and has exhibited outstanding performance in many practical engineering problems. However, the tournament selection strategy used for the reproduction in NSGA-II may generate a large amount of repetitive individuals, resulting in the decrease of population diversity. To alleviate this issue, Lévy distribution, which is famous for excellent search ability in the cuckoo search algorithm, is incorporated into NSGA-II. To verify the proposed algorithm, this paper employs three different test sets, including ZDT, DTLZ, and MaF test suits. Experimental results demonstrate that the proposed algorithm is more promising compared with the state-of-the-art algorithms. Parameter sensitivity analysis further confirms the robustness of the proposed algorithm. In addition, a two-objective network topology optimization model is then used to further verify the proposed algorithm. The practical comparison results demonstrate that the proposed algorithm is more effective in dealing with practical engineering optimization problems.

Improved Process Control Using Hybrid Industrial Internet of Things Network Topology

2021 ◽  
Author(s):  
David Guerra-Zubiaga ◽  
Jay Strickland ◽  
Kevin Kamperman ◽  
Ryan Mchale ◽  
Navid Nasajpour-Esfahani
Keyword(s):  
Internet Of Things ◽  
Process Control ◽  
Network Topology ◽  
Industrial Internet Of Things ◽  
Industrial Internet

scholarly journals Attribute Reduction Based on Genetic Algorithm for the Coevolution of Meteorological Data in the Industrial Internet of Things

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Yong Cheng ◽  
Zhongren Zheng ◽  
Jun Wang ◽  
Ling Yang ◽  
Shaohua Wan
Keyword(s):  
Genetic Algorithm ◽  
Internet Of Things ◽  
Meteorological Data ◽  
Attribute Reduction ◽  
Evolutionary Process ◽  
Population Diversity ◽  
The Other ◽  
Industrial Internet Of Things ◽  
Reduction Operation ◽  
Industrial Internet

Due to the problem of attribute redundancy in meteorological data from the Industrial Internet of Things (IIoT) and the slow efficiency of existing attribute reduction algorithms, attribute reduction based on a genetic algorithm for the coevolution of meteorological data was proposed. The evolutionary population was divided into two subpopulations: one subpopulation used elite individuals to assist crossover operations to increase the convergence speed of the algorithm, and the other subpopulation balanced the population diversity in the evolutionary process by introducing a random population; these two subpopulations completed the evolutionary operations together. With the TSDPSO-AR algorithm and ARAGA algorithm, the attribute reduction operation for precipitation in meteorological data was performed. The results showed that the proposed algorithm maintained the diversity of the population during evolution, improved the reduction performance, and simplified the information system.

An Integrated Legacy of Modbus Devices to Industrial Internet of Things: Approach for Smart Industries

2020 ◽  
Author(s):  
Karthik Muthineni
Keyword(s):  
Internet Of Things ◽  
Industrial Revolution ◽  
Digital Technologies ◽  
Industrial Internet Of Things ◽  
Intelligent Decision Making ◽  
Internet Of Everything ◽  
Industrial Internet ◽  
Intelligent Decision ◽  
Network Platform ◽  
Smart Factories

The new industrial revolution Industry 4.0, connecting manufacturing process with digital technologies that can communicate, analyze, and use information for intelligent decision making includes Industrial Internet of Things (IIoT) to help manufactures and consumers for efficient controlling and monitoring. This work presents the design and implementation of an IIoT ecosystem for smart factories. The design is based on Siemens Simatic IoT2040, an intelligent industrial gateway that is connected to modbus sensors publishing data onto Network Platform for Internet of Everything (NETPIE). The design demonstrates the capabilities of Simatic IoT2040 by taking Python, Node-Red, and Mosca into account that works simultaneously on the device.

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