COVID-19 Vaccine Distribution Time Optimization with Genetic Algorithm

Abstract: Covid-19 emerged in 2019 in Wuhan, China, and spread from there to the whole world. Some vaccines have been developed by scientists to combat this virus. These vaccines were distributed to hospitals and health centres to be delivered to people. Vaccines are distributed in special conditions by special vehicles without spoiling. Distribution of vaccines can be thought of as a traveling salesman problem. The traveling salesman problem is an NP-hard type problem. It is not possible to solve it mathematically in normal time. For this reason, genetic algorithm, which is a very popular algorithm, was used to create the vaccine distribution route in this study. The genetic algorithm is an algorithm that works on the principle of the fittest survives. In the genetic algorithm, a random population containing a certain number of solutions is first created. This population undergoes metamorphosis through the stages of selection, crossover, and mutation. The good ones from the new solutions created are transferred to the next generation and thus, better solutions are obtained. In the traveling salesman problem, the solution sequence is tested with the solutions generated by the genetic algorithm, and the solution that distributes in the shortest time is recorded as the best solution. Thus, the distribution of the vaccine is carried out as soon as possible. With the genetic algorithm, it is aimed to determine the shortest time for vaccine distribution to health centres in Kayseri. The solution obtained is quite successful.

Keywords: Covid-19, Genetic Algorithm, Traveling Salesman Problem, Optimization

Publication details: Conference abstract presented at the The International Conference on Engineering, Natural and Applied Science (ICENAS'21), 24-26 November 2021, Osmaniye, Türkiye. Published in: ICENAS'21 Book of Abstracts, pp. 100. Publisher: Osmaniye Korkut Ata University. ISBN: 978-605-61237-3-3.

How to cite / Kaynak gösterimi

APA 7: Gülmez, B., & Korhan, E. (2021, November). COVID-19 Vaccine Distribution Time Optimization with Genetic Algorithm [Conference abstract]. In B. Yanıktepe, D. Ovalı Döndaş, O. Kara, & A. B. Güher (Eds.), ICENAS'21 Book of Abstracts (p. 100). Osmaniye Korkut Ata University. The International Conference on Engineering, Natural and Applied Science (ICENAS'21), Osmaniye, Türkiye. https://doi.org/10.5281/zenodo.23036880

IEEE: B. Gülmez and E. Korhan, "COVID-19 Vaccine Distribution Time Optimization with Genetic Algorithm," in ICENAS'21 Book of Abstracts, Osmaniye, Türkiye, Nov. 2021, p. 100, ISBN: 978-605-61237-3-3, doi: 10.5281/zenodo.23036880.

Chicago: Gülmez, Burak, and Emrah Korhan. 2021. "COVID-19 Vaccine Distribution Time Optimization with Genetic Algorithm." In ICENAS'21 Book of Abstracts, 100. Osmaniye, Türkiye: Osmaniye Korkut Ata University. https://doi.org/10.5281/zenodo.23036880.

MLA 9: Gülmez, Burak, and Emrah Korhan. "COVID-19 Vaccine Distribution Time Optimization with Genetic Algorithm." ICENAS'21 Book of Abstracts, Osmaniye Korkut Ata University, 2021, p. 100. https://doi.org/10.5281/zenodo.23036880.

Harvard: Gülmez, B. and Korhan, E. (2021) 'COVID-19 Vaccine Distribution Time Optimization with Genetic Algorithm', in ICENAS'21 Book of Abstracts. Osmaniye, Türkiye: Osmaniye Korkut Ata University, pp. 100. doi: 10.5281/zenodo.23036880.

BibTeX:

@inproceedings{Gulmez2021covid19,
  author    = {Gülmez, Burak and Korhan, Emrah},
  title     = {COVID-19 Vaccine Distribution Time Optimization with Genetic Algorithm},
  booktitle = {ICENAS'21 Book of Abstracts},
  year      = {2021},
  month     = {nov},
  pages     = {100},
  address   = {Osmaniye, Türkiye},
  publisher = {Osmaniye Korkut Ata University},
  isbn      = {978-605-61237-3-3},
  doi       = {10.5281/zenodo.23036880},
  url       = {https://doi.org/10.5281/zenodo.23036880}
}