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A fast two-objective differential evolution for the two-objective coverage problem of WSNs

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Abstract

The aim of this article is to study the two-objective coverage problem of wireless sensor networks (WSNs) by means of differential evolution algorithm. Firstly, in order to reduce the computing redundancy of multi-objective optimization, namely to reduce the number of individuals which participate in non-dominated solution sorting, we introduced a fast two-objective differential evolution algorithm (FTODE). The FTODE contains a fast non-dominated solution sorted and a uniform crowding distance calculation method. The fast sorting method just handles the highest rank individuals but not all individuals in the current population. Meanwhile, during the individuals sorted, it can choose some of individuals into next generation and reduce the time complexity. The uniform crowding distance calculation can enhance the diversity of population due to it will retain the outline of optimal solution set by choosing the individual uniformly. Secondly, we use the FTODE framework to research the two-objective coverage problem of WSNs. The two objectives are formulated as: the minimum number of sensor used and the maximum coverage rate. For this specific problem, decimal integer encoding are used and a recombination operation is introduced into FTODE, which performs after initialization and guarantees at least one critical target’s sensor is divided into different disjoint sets. Finally, the simulation experiment shows that the FTODE provides competitive results in terms of time complexity and performance, and it also obtains better solutions than comparison algorithms on the two-objective coverage problem of WSNs.

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Acknowledgements

The authors gratefully acknowledge the helpful comments and suggestions of editors and anonymous reviewers. This work was supported by the key scientific research project of Henan provinces’ university (Nos. 15A520083 and 17B520017); the National Natural Science Foundation of China (Nos. 81703946, 61503328, 61772475 and 61502434); the doctoral research fund in Henan University of Chinese Medicine (Nos. BSJJ2015-19); the science and technology research Project of Henan province (Nos. 172102210361 and 172102310536).

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Authors and Affiliations

  1. School of Information Engineering, Zhengzhou University, ZhengZhou, 450052, China

    Yulong Xu & Yangdong Ye

  2. School of Information and Technology, Henan University of Traditional Chinese Medicine, Zhengzhou, 450046, China

    Yulong Xu & Yali Lv

  3. Intelligent Control Laboratory, College of Engineering, Peking University, Beijing, 100871, China

    Han Zhang

  4. Department of Mathematics, Yangzhou University, Yangzhou, 225002, Jiangsu, China

    Wenbing Zhang

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  1. Yulong Xu
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Correspondence to Yangdong Ye.

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Xu, Y., Ye, Y., Zhang, H. et al. A fast two-objective differential evolution for the two-objective coverage problem of WSNs. Memetic Comp. 11, 89–107 (2019). https://doi.org/10.1007/s12293-018-0264-7

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