An efficient genetic algorithm for large-scale planning of dense and robust industrial wireless networks

作者：

Highlights：

• An over-dimensioning model for planning robust industrial wireless local area networks considering 3D obstacle shadowing effects.

• An efficient genetic algorithm (GA) is proposed to solve this model even at a hyper-large scale.

• A greedy heuristic and a random placement algorithm are introduced as benchmarks.

• This model and GA are both experimentally validated and numerically demonstrated.

摘要

•An over-dimensioning model for planning robust industrial wireless local area networks considering 3D obstacle shadowing effects.•An efficient genetic algorithm (GA) is proposed to solve this model even at a hyper-large scale.•A greedy heuristic and a random placement algorithm are introduced as benchmarks.•This model and GA are both experimentally validated and numerically demonstrated.

论文关键词：Genetic algorithms,Large-scale optimization,Wireless network deployment,Internet of things,Cyber physical systems

论文评审过程：Received 23 March 2017, Revised 6 September 2017, Accepted 6 December 2017, Available online 8 December 2017, Version of Record 22 December 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.12.011