Abstract: Dengue has become a serious health hazard in Sri Lanka with the increasing cases and loss of human lives. It is necessary to develop an efficient dengue disease management system which could predict the dengue out breaks, plan the countermeasures accordingly and allocate resources for the countermeasures. We have proposed a platform for Dengue disease management with following modules: (1) a prediction module to predict the dengue outbreak and (2) an optimization algorithm module to optimize hospital staff according to the predictions made on future dengue patient counts. This paper focuses on the optimization algorithm module. It has been developed based on two approaches: (1) Genetic Algorithm (GA) and (2) Iterated Local Search (ILS). We are presenting the performances of our optimization algorithm module with a comparison of the two approaches. Our results show that the GA approach is much more efficient and faster than the ILS approach.

J M.M.C Jayasuriya, G.K.K.T.Galappaththi, M.A.Dilupa Sampath, H.N.Nipunika and W.H. Rankothge, “Experimental Study on an Efficient Dengue Disease Management System” International Journal of Advanced Computer Science and Applications(IJACSA), 9(11), 2018. http://dx.doi.org/10.14569/IJACSA.2018.091107

@article{Jayasuriya2018,
title = {Experimental Study on an Efficient Dengue Disease Management System},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2018.091107},
url = {http://dx.doi.org/10.14569/IJACSA.2018.091107},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {11},
author = {J M.M.C Jayasuriya and G.K.K.T.Galappaththi and M.A.Dilupa Sampath and H.N.Nipunika and W.H. Rankothge},
}