Harris Hawks optimization for ambulance vehicle routing in smart cities

Authors

DOI:

https://doi.org/10.15587/1729-4061.2023.278002

Keywords:

ambulance vehicle routing, Harris Hawks optimization method, smart city

Abstract

The ambulance routing problem is one of the capacitated ambulance routing problem forms. It deals with injuries and their requests for saving. Therefore, the main aim of the ambulance routing problem is to determine the minimum (i.e., optimum) required distances of between:

1) accident places and the ambulance station;

2) the location of the nearest hospital and the accident places.

Although of the efforts proposed in the literature, determining the optimum route is crucial. Therefore, this article seeks to tackle ambulance vehicle routing in smart cities using Harris Hawks Optimization (HHO) algorithm. It attempts to take the victims as quickly as possible and confidently. Several engineering optimization problems confirm that HHO outperforms many well-known Swarm intelligence approaches. In our system, let’s use the node approach to produce a city map. Initially, the control station receives accident site information and sends it to the hospital and the ambulance. The HHO vehicle routing algorithm receives data from the driver; the data includes the location of the accident and the node position of the ambulance vehicle. Then, the driver’s shortest route to the accident scene by the HHO. The locations of the accident and hospital are updated by the driver once the car reaches the accident site. The fastest route (which results in the least travel time) to the hospital is then determined. The HHO can provide offline information for a potential combination of the coordinates of destination and source. Extensive simulation experiments demonstrated that the HHO can provide optimal solutions. Furthermore, performance evaluation experiments demonstrated the superiority of the HHO algorithm over its counterparts (SAODV, TVR, and TBM methods). Furthermore, for ten malicious nodes, the PDF of the algorithm was 0.91, which is higher than the counterparts

Author Biographies

Taha Darwassh Hanawy Hussein, National Engineering School of Sfax (ENIS)

PhD Student

Doctoral School of Science and Technology

Mondher Frikha, National School of Electronics and Telecoms of Sfax

PhD in Electrical Engineering

Doctoral in Electrical Engineering

Javad Rahebi, Istanbul Topkapi University

PhD in Engineering

Department of Software Engineering

References

  1. Arunmozhi, P., William, P. J. (2014). Automatic ambulance rescue system using shortest path finding algorithm. International Journal of Science and Research (IJSR), 3 (5). Available at: https://www.ijsr.net/archive/v3i5/MDIwMTMxODM2.pdf
  2. Suthaputchakun, C., Cao, Y. (2019). Ambulance-to-Traffic Light Controller Communications for Rescue Mission Enhancement: A Thailand Use Case. IEEE Communications Magazine, 57 (12), 91–97. doi: https://doi.org/10.1109/mcom.001.1900038
  3. Allam, S. (2021). Research on intelligent medical big data system based on Hadoop and blockchain. International Journal of Emerging Technologies and Innovative Research, 8 (4). Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3855242
  4. Adanur, B., Bakir-Gungor, B., Soran, A. (2020). Blockchain-based Fog Computing Applications in Healthcare. 2020 28th Signal Processing and Communications Applications Conference (SIU). doi: https://doi.org/10.1109/siu49456.2020.9302168
  5. Gul, M. J., Subramanian, B., Paul, A., Kim, J. (2021). Blockchain for public health care in smart society. Microprocessors and Microsystems, 80, 103524. doi: https://doi.org/10.1016/j.micpro.2020.103524
  6. AMohammed Al-Mafrji, A. A., Hamodi, Y. I., Hassn, S. G., Mohammed, A. B. (2023). Analyzing the use of expert systems in improving the quality of decision-making. Eastern-European Journal of Enterprise Technologies, 1 (3 (121)), 73–80. doi: https://doi.org/10.15587/1729-4061.2023.274584
  7. Majid, M., Habib, S., Javed, A. R., Rizwan, M., Srivastava, G., Gadekallu, T. R., Lin, J. C.-W. (2022). Applications of Wireless Sensor Networks and Internet of Things Frameworks in the Industry Revolution 4.0: A Systematic Literature Review. Sensors, 22 (6), 2087. doi: https://doi.org/10.3390/s22062087
  8. Tripathy, B. K., Reddy Maddikunta, P. K., Pham, Q.-V., Gadekallu, T. R., Dev, K., Pandya, S., ElHalawany, B. M. (2022). Harris Hawk Optimization: A Survey onVariants and Applications. Computational Intelligence and Neuroscience, 2022, 1–20. doi: https://doi.org/10.1155/2022/2218594
  9. Umar, S., Sadiku, L. U., Tonga, D. A. (2019). Intelligent-Based Control System for Effective Road Traffic Management in Nigeria: A Proposed Model. International Journal of Latest Engineering Science (IJLES), 2 (6). Available at: https://www.ijlesjournal.org/2019/volume-2%20issue-6/ijles-v2i6p103.pdf
  10. Priyadarshi, S., Mehrotra, R., Shekhar, S. (2019). Self Control & Monitoring Traffic Management System. 2019 2nd International Conference on Power Energy, Environment and Intelligent Control (PEEIC). doi: https://doi.org/10.1109/peeic47157.2019.8976768
  11. Ghazal, B., ElKhatib, K., Chahine, K., Kherfan, M. (2016). Smart traffic light control system. 2016 Third International Conference on Electrical, Electronics, Computer Engineering and Their Applications (EECEA). doi: https://doi.org/10.1109/eecea.2016.7470780
  12. Lee, W.-H., Chiu, C.-Y. (2020). Design and Implementation of a Smart Traffic Signal Control System for Smart City Applications. Sensors, 20 (2), 508. doi: https://doi.org/10.3390/s20020508
  13. Shanmughasundaram, R., Prasanna Vadanan, S., Dharmarajan, V. (2018). Li-Fi Based Automatic Traffic Signal Control for Emergency Vehicles. 2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC). doi: https://doi.org/10.1109/icaecc.2018.8479427
  14. Boynton, A. C., Victor, B., Pine II, B. J. (1993). New competitive strategies: Challenges to organizations and information technology. IBM Systems Journal, 32 (1), 40–64. doi: https://doi.org/10.1147/sj.321.0040
  15. Hussein, T. D. H., Frikha, M., Ahmed, S., Rahebi, J. (2022). Ambulance Vehicle Routing in Smart Cities Using Artificial Neural Network. 2022 6th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP). doi: https://doi.org/10.1109/atsip55956.2022.9805857
  16. Deshmukh, S., Vanjale, S. B. (2018). IOT Based Traffic Signal Control for Reducing Time Delay of an Emergency Vehicle Using GPS. 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA). doi: https://doi.org/10.1109/iccubea.2018.8697555
  17. Djahel, S., Smith, N., Wang, S., Murphy, J. (2015). Reducing emergency services response time in smart cities: An advanced adaptive and fuzzy approach. 2015 IEEE First International Smart Cities Conference (ISC2). doi: https://doi.org/10.1109/isc2.2015.7366151
  18. Constantinescu, V., Patrascu, M. (2017). Route encoding in evolutionary control systems for emergency vehicles. 2017 15th International Conference on ITS Telecommunications (ITST). doi: https://doi.org/10.1109/itst.2017.7972216
  19. Chen, M. (2014). Improved genetic algorithm for emergency logistics distribution vehicle routing problems. Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC). doi: https://doi.org/10.1109/spac.2014.6982721
  20. El Fallahi, A., Sefrioui, I. (2019). A linear programming model and memetic algorithm for the Emergency Vehicle Routing. 2019 4th World Conference on Complex Systems (WCCS). doi: https://doi.org/10.1109/icocs.2019.8930750
  21. Mouhcine, E., Karouani, Y., Mansouri, K., Mohamed, Y. (2018). Toward a distributed strategy for emergency ambulance routing problem. 2018 4th International Conference on Optimization and Applications (ICOA). doi: https://doi.org/10.1109/icoa.2018.8370582
  22. Rathore, N., Jain, P. K., Parida, M. (2018). A routing model for emergency vehicles using the real time traffic data. 2018 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI). doi: https://doi.org/10.1109/soli.2018.8476771
  23. Tlili, T., Harzi, M., Krichen, S. (2017). Swarm-based approach for solving the ambulance routing problem. Procedia Computer Science, 112, 350–357. doi: https://doi.org/10.1016/j.procs.2017.08.012
  24. Tavakkoli-Moghaddam, R., Memari, P., Talebi, E. (2018). A bi-objective location-allocation problem of temporary emergency stations and ambulance routing in a disaster situation. 2018 4th International Conference on Optimization and Applications (ICOA). doi: https://doi.org/10.1109/icoa.2018.8370579
  25. Kamireddy, C. R., Bingisateesh, Keshavamurthy, B. N. (2016). Efficient routing of 108 ambulances using clustering techniques. 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC). doi: https://doi.org/10.1109/iccic.2016.7919560
  26. Sharma, A., Kumar, R. (2017). An optimal routing scheme for critical healthcare HTH services — an IOT perspective. 2017 Fourth International Conference on Image Information Processing (ICIIP). doi: https://doi.org/10.1109/iciip.2017.8313784
  27. Madisa, M. K., Joseph, M. K. (2018). Android and Cloud Based Traffic Control System. 2018 International Conference on Advances in Big Data, Computing and Data Communication Systems (IcABCD). doi: https://doi.org/10.1109/icabcd.2018.8465443
  28. Heidari, A. A., Mirjalili, S., Faris, H., Aljarah, I., Mafarja, M., Chen, H. (2019). Harris hawks optimization: Algorithm and applications. Future Generation Computer Systems, 97, 849–872. doi: https://doi.org/10.1016/j.future.2019.02.028
  29. Tripathi, K. N., Sharma, S. C. (2019). A trust based model (TBM) to detect rogue nodes in vehicular ad-hoc networks (VANETS). International Journal of System Assurance Engineering and Management, 11 (2), 426–440. doi: https://doi.org/10.1007/s13198-019-00871-0
  30. Mirsadeghi, F., Rafsanjani, M. K., Gupta, B. B. (2020). A trust infrastructure based authentication method for clustered vehicular ad hoc networks. Peer-to-Peer Networking and Applications, 14 (4), 2537–2553. doi: https://doi.org/10.1007/s12083-020-01010-4
  31. Kumar, A., Varadarajan, V., Kumar, A., Dadheech, P., Choudhary, S. S., Kumar, V. D. A. et al. (2021). Black hole attack detection in vehicular ad-hoc network using secure AODV routing algorithm. Microprocessors and Microsystems, 80, 103352. doi: https://doi.org/10.1016/j.micpro.2020.103352
Harris Hawks optimization for ambulance vehicle routing in smart cities

Downloads

Published

2023-04-30

How to Cite

Hussein, T. D. H., Frikha, M., & Rahebi, J. (2023). Harris Hawks optimization for ambulance vehicle routing in smart cities. Eastern-European Journal of Enterprise Technologies, 2(3 (122), 74–81. https://doi.org/10.15587/1729-4061.2023.278002

Issue

Vol. 2 No. 3 (122) (2023): Control processes

Section

Control processes

License

Copyright (c) 2023 Taha Darwassh Hanawy Hussein, Mondher Frikha, Javad Rahebi

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.

A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.