A Novel Mixed-Variable Fireworks Optimization Algorithm for Path and Time Sequence Optimization in WRSNs

  • Chengkai Xia
  • Zhenchun Wei
  • Zengwei Lyu
  • Liangliang Wang
  • Fei Liu
  • Lin FengEmail author
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 262)


To prolong the lifespan of the network, the auxiliary charging equipment is introduced into the traditional Wireless Sensor Networks (WSNs), known as Wireless Rechargeable Sensor Networks (WRSNs). Different from existing researches, in this paper, a periodic charging and data collecting model in WRSNs is proposed to keep the network working perpetually and improve data collection ratio. Meanwhile, the Wireless Charging Vehicle (WCV) has more working patterns, charging, waiting, and collecting data when staying at the sensor nodes. Then, the simultaneous optimization for the traveling path and time sequence is formulated to be a mixed-variable optimization problem. A novel Mixed-Variable Fireworks Optimization Algorithm (MVFOA) is proposed to solve it. A large number of experiments show the feasibility of the MVFOA, and MVFOA is superior to the Greedy Algorithm.


Wireless rechargeable sensor networks Mixed-variable optimization Fireworks algorithm 


  1. 1.
    Kurs, A., Karalis, A., Moffatt, R., Joannopoulos, J.D., Fisher, P., Soljai, M.: Wireless power transfer via strongly coupled magnetic resonances. Science 317(5834), 83–86 (2007)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Xie, L., Shi, Y., Hou, Y.T., Sherali, H.D.: Making sensor networks immortal: an energy-renewal approach with wireless power transfer. IEEE/ACM Trans. Netw. 20(6), 1748–1761 (2012)CrossRefGoogle Scholar
  3. 3.
    Xie, L., Shi, Y., Hou, Y.T., Lou, W., Sherali, H.D., Zhou, H.: A mobile platform for wireless charging and data collection in sensor networks. IEEE J. Sel. Areas Commun. 33(8), 1521–1533 (2015)Google Scholar
  4. 4.
    Guo, S., Wang, C., Yang, Y.: Joint mobile data gathering and energy provisioning in wireless rechargeable sensor networks. IEEE Trans. Mob. Comput. 13(12), 2836–2852 (2014)CrossRefGoogle Scholar
  5. 5.
    Wang, C., Li, J., Yang, Y.: Low-latency mobile data collection for Wireless Rechargeable Sensor Networks. In: International Conference on Communications, pp. 6524–6529. IEEE, London (2015)Google Scholar
  6. 6.
    Zhong, P., Li, Y.T., Liu, W.R., Duan, G.H., Chen, Y.W., Xiong, N.: Joint mobile data collection and wireless energy transfer in wireless rechargeable sensor networks. Sensors 17(8), 1–23 (2017)CrossRefGoogle Scholar
  7. 7.
    Lin, Y., Du, W., Liao, T., Stützle, T.: Three L-SHADE based algorithms on mixed-variables optimization problems. In: IEEE Congress on Evolutionary Computation, pp. 2274–2281. IEEE, San Sebastian (2017)Google Scholar
  8. 8.
    Tan, Y., Zhu, Y.: Fireworks algorithm for optimization. In: International Conference on Advances in Swarm Intelligence, pp. 355–364. Springer, Berlin (2010)Google Scholar
  9. 9.
    Li, J., Zheng, S., Tan, Y.: Adaptive fireworks algorithm. In: IEEE Congress on Evolutionary Computation, pp. 3214–3221. IEEE, Beijing (2014)Google Scholar
  10. 10.
    Tan, Y.: Fireworks Algorithm: A Novel Swarm Intelligence Optimization Method. Springer, Berlin (2015)CrossRefGoogle Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  • Chengkai Xia
    • 1
  • Zhenchun Wei
    • 1
    • 2
    • 3
  • Zengwei Lyu
    • 1
  • Liangliang Wang
    • 1
  • Fei Liu
    • 1
  • Lin Feng
    • 1
    Email author
  1. 1.School of Computer and InformationHefei University of TechnologyHefeiChina
  2. 2.Engineering Research Center of Safety Critical Industrial Measurement and Control Technology, Ministry of EducationHefeiChina
  3. 3.Key Laboratory of Industry Safety and Emergency TechnologyHefeiChina

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