Weight Optimization of Optimal Control Influenza Model Using Artificial Bee Colony
Kata Kunci:
optimal control., influenza model, Artificial Bee colonyAbstrak
Influenza is disease which can be contagious through contact with infected individual. There are two types of control strategies to bound the spread of disease: prevention action for controlling susceptible and treatment for controlling infected. Optimal control is used for minimizing the number of infected individual, the cost of prevention action and the cost of treatment. Due to the cost of objective function depends on weight, in this research we will apply Artificial Bee Colony algorithm to optimize weight minimizing cost of objective function. The simulations show that the number of infected with control is lower than without control. Furthermore, we also obtain optimal weight related to cost of prevention action and treatment.
Referensi
“Influenza,” http://en.wikipedia.org/wiki/influenza, accessed: 2017-07-01.
M. Hia, O. Balatif, M. Rachik, and J. Bouyaghroumni, “Application of optimal control theory to an seir model with immigration of infectives,” IJCSI International Journal of Computer Science Issues, 2013.
E. Bakare, A. Nwagwo, and E. Danso-Addo, “Optimal control analysis of an sir epidemic model with constant recruitment,” International Journal of Applied Mathematical Research, vol. 3, no. 3, pp. 273–285, 2014.
Z. Michalewicz, C. Janikow, and J. Krawczyk, “A modified genetic algorithm for optimal control problems,” Computers & Mathematics with Applications, vol. 23, no. 12, pp. 83–94, 1992.
D. Karaboga and B. Basturk, “A powerful and efficient algorithm for numerical function optimization: artificial bee colony (abc) algorithm,” Journal of global optimization, vol. 39, no. 3, pp. 459–471, 2007.
J. Burl, Linear optimal control: H (2) and H (Infinity) methods. Addison-Wesley Longman Publishing Co., Inc., 1998.
D. Rahmalia and T. Herlambang, “Application ant colony optimization on weight selection of optimal control seir epidemic model,” in Proceeding the 7th Annual Basic Science International Conference, Dec. 2017, pp. 196–199.
T. Liao, D. Aydin, and T. Stutzle, “Artificial bee colonies for continuous optimization: Experimental analysis and improvements,” Swarm Intelligence, vol. 7, no. 4, pp. 327–356, 2013.
O. Sharomi and T. Malik, “Optimal control in epidemiology,” Annals of Operations Research, vol. 251, no. 1-2, pp. 55–71, 2017.
