Skip Navigation Links
Journal of Applied Nonlinear Dynamics
Miguel A. F. Sanjuan (editor), Albert C.J. Luo (editor)
Miguel A. F. Sanjuan (editor)

Department of Physics, Universidad Rey Juan Carlos, 28933 Mostoles, Madrid, Spain

Email: miguel.sanjuan@urjc.es

Albert C.J. Luo (editor)

Department of Mechanical and Industrial Engineering, Southern Illinois University Ed-wardsville, IL 62026-1805, USA

Fax: +1 618 650 2555 Email: aluo@siue.edu


Optimizing Rotavirus Vaccine Cost: A Dynamic Approach for Global Health and Environmental Sustainability

Journal of Applied Nonlinear Dynamics 14(4) (2025) 959--971 | DOI:10.5890/JAND.2025.12.014

Vinita Dwivedi, Uttam Kumar Khedlekar

Department of Mathematics and Statistics, Dr. Harisingh Gour Vishwavidyalaya, Sagar, M.P. - 470003, India

Download Full Text PDF

 

Abstract

This study addresses the global threat of rotavirus, particularly its impact on infants and young children, and emphasizes the importance of integrating rotavirus vaccines into childhood immunization programs, as recommended by the WHO. It highlights the need for promotional efforts to raise awareness, coupled with efficient vaccine inventory management due to perishability, using preservation techniques and cold storage. The study also proposes green technology investments to reduce carbon emissions from vaccine deterioration, aligning with Sustainable Development Goals. Advanced optimization algorithms, such as Ant Colony, Modified Flower Pollination, Cuckoo Search, and Particle Swarm Optimization, are utilized to optimize pricing, preservation, green investments, and replenishment schedules. Numerical experiments demonstrate the effectiveness of these dynamic investment strategies, and sensitivity analysis provides valuable insights for decision-makers. The study concludes by highlighting the role of green technology in managing the social and environmental impacts of vaccine inventories, offering practical solutions and strategic insights for rotavirus disease response.

References

  1. [1]  León-Cava, N., Lutter, C., Ross, J., and Martin, L. (2002) Quantifying the benefits of breastfeeding: a summary of the evidence. Pan American Health Organization, Washington DC, 3, 1-3.
  2. [2]  Ahmad, S., Ullah, A., Arfan, M., and Shah, K. (2020) On analysis of the fractional mathematical model of rotavirus epidemic with the effects of breastfeeding and vaccination under atangana-baleanu (ab) derivative. Chaos, Solitons $\&$ Fractals, 140, 1-5. doi: https://doi.org/10.1016/j.chaos.2020.110233.
  3. [3]  Aly, E.S., Almalahi, M.A., Aldwoah, K.A., and Shah, K. (2024) Criteria of existence and stability of an n-coupled system of generalized Sturm-Liouville equations with a modified ABC fractional derivative and an application to the SEIR influenza epidemic model. AIMS Mathematics, 9(6), 14228-14252.
  4. [4]  Sinan, M., Ansari, K.J., Kanwal, A., Shah, K., Abdeljawad, T., Abdalla, B., et al. (2023) Analysis of the mathematical model of cutaneous leishmaniasis disease. Alexandria Engineering Journal, 72, 117-134. Elsevier.
  5. [5]  Yadav, P., Jahan, S., Shah, K., Peter, O.J., and Abdeljawad, T. (2023) Fractional-order modelling and analysis of diabetes mellitus: Utilizing the Atangana-Baleanu Caputo (ABC) operator. Alexandria Engineering Journal, 81, 200-209. Elsevier.
  6. [6]  Shah, K., Sarwar, M., Abdeljawad, T., et al. (2024) On rotavirus infectious disease model using piecewise modified $ABC$ fractional order derivative. Networks $\&$ Heterogeneous Media, 19(1).
  7. [7]  Dye, C.Y., and Hsieh, T.P. (2012) An optimal replenishment policy for deteriorating items with effective investment in preservation technology. European Journal of Operational Research, 218(1), 106-112.
  8. [8]  Ullah, M., Khan, I., and Sarkar, B. (2019) Dynamic pricing in a multi-period newsvendor under stochastic price-dependent demand. Mathematics, 7(6), 520.
  9. [9]  Yu, A.P.I., Chuang, S.C., Cheng, Y.H., and Wu, Y.C. (2020) The influence of sharing versus self-use on the preference for different types of promotional offers. Journal of Retailing and Consumer Services, 54, 1-4.
  10. [10]  Afshar-Nadjafi, B., Mashatzadeghan, H., and Khamseh, A. (2016) Time-dependent demand and utility-sensitive sale price in a retailing system. Journal of Retailing and Consumer Services, 32, 171-174.
  11. [11]  Goli, A., Aazami, A., and Jabbarzadeh, A. (2018) Accelerated cuckoo optimization algorithm for capacitated vehicle routing problem in competitive conditions. International Journal of Artificial Intelligence, 16(1), 88-112.
  12. [12]  Tiwari, S., Jaggi, C.K., Gupta, M., and Cárdenas-Barrón, L.E. (2018) Optimal pricing and lot-sizing policy for supply chain system with deteriorating items under limited storage capacity. International Journal of Production Economics, 200, 278-290.
  13. [13]  Tiwari, S., Cárdenas-Barrón, L.E., Goh, M., and Shaikh, A.A. (2018) Joint pricing and inventory model for deteriorating items with expiration dates and partial backlogging under two-level partial trade credits in supply chain. International Journal of Production Economics, 200, 16-36.
  14. [14]  Hsu, P., Wee, H., and Teng, H. (2010) Preservation technology investment for deteriorating inventory. International Journal of Production Economics, 124(2), 388-394.
  15. [15]  Mishra, U., Wu, J.Z., and Sarkar, B. (2020) A sustainable production-inventory model for a controllable carbon emissions rate under shortages. Journal of Cleaner Production, 256, 120268.
  16. [16]  De-la Cruz-Márquez, C.G., Cárdenas-Barrón, L.E., and Mandal, B. (2021) An inventory model for growing items with imperfect quality when the demand is price sensitive under carbon emissions and shortages. Mathematical Problems in Engineering, 2021, 1-23.
  17. [17]  Sepehri, A. (2021) Controllable carbon emissions in an inventory model for perishable items under trade credit policy for credit-risk customers. Carbon Capture Science $\&$ Technology, 1, 100004.
  18. [18]  Jauhari, W.A. (2022) Sustainable inventory management for a closed-loop supply chain with energy usage, imperfect production, and green investment. Cleaner Logistics and Supply Chain, 4, 100055.
  19. [19]  Daryanto, Y., and Wee, H. (2020) Three-echelon green supply chain inventory decision for imperfect quality deteriorating items. Operations and Supply Chain Management: An International Journal, 14(1), 26-38.
  20. [20]  Saha, S., Chatterjee, D., and Sarkar, B. (2021) The ramification of dynamic investment on the promotion and preservation technology for inventory management through a modified flower pollination algorithm. Journal of Retailing and Consumer Services, 58, 102326.
  21. [21]  Wang, L., Song, H., Yang, H., and Huang, F. (2020) Optimal dynamic pricing for non-instantaneous deteriorating items dependent on price and time demand. International Journal of Computing Science and Mathematics, 11(4), 372-384.
  22. [22]  Mashud, A.H.M., Miah, S., Daryanto, Y., Chakrabortty, R.K., Hasan, S.M., and Tseng, M.L. (2022) Inventory decisions on the transportation system and carbon emissions under covid-19 effects: A sensitivity analysis. Computers $\&$ Industrial Engineering, 171, 108393.
  23. [23]  Jha, J., and Shanker, K. (2009) A single-vendor single-buyer production-inventory model with controllable lead time and service level constraint for decaying items. International Journal of Production Research, 47(24), 6875-6898.
  24. [24]  Yu, W., Hou, G., Li, J., et al. (2019) Supply chain joint inventory management and cost optimization based on ant colony algorithm and fuzzy model. Tehnicki vjesnik, 26(6), 1729-1737.
  25. [25]  Karl, J.A., Ribeiro, L., Bergomi, C., Fischer, R., Dunne, S., and Medvedev, O.N. (2024) Making it short: Shortening the comprehensive inventory of mindfulness experiences using ant colony optimization. Mindfulness, 1-14.
  26. [26]  Agarwal, S., et al. (2024) Optimizing inventory management in dual-warehouse systems using the cuckoo search algorithm. Journal of Research Administration, 6(1).
  27. [27]  Shah, N.H., Patel, D.G., Shah, D.B., and Prajapati, N.M. (2023) A sustainable production inventory model with green technology investment for perishable products. Decision Analytics Journal, 8, 100309.
  28. [28]  Hethcote, H.W. (1989) Three basic epidemiological models. Journal Name, 119-144.
  29. [29]  Srinivasan, S., Pauwels, K., Hanssens, D.M., and Dekimpe, M.G. (2004) Do promotions benefit manufacturers, retailers, or both? Management Science, 50(5), 617-629.
  30. [30]  Yang, X.S. (2012) Flower pollination algorithm for global optimization. In: Proceedings of the International Conference on Unconventional Computing and Natural Computation, Springer, 240-249.
  31. [31]  Kennedy, J., and Eberhart, R. (1995) Particle swarm optimization. In: Proceedings of ICNN'95-International conference on neural networks, 4, IEEE, 1942-1948.