Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2751
Title: Experimental study on an efficient dengue disease management system: Planning and optimizing hospital staff allocation
Authors: Jayasuriya, M. M. C
Galappaththi, G. K. K. T
Sampath, M. A. D
Nipunika, H. N
Rankothge, W
Keywords: Optimization
genetic algorithm
iterated local searc
algorithm comparison
nurse scheduling
Issue Date: Jan-2018
Publisher: The Science and Information (SAI) Organization
Citation: Jayasuriya, M.M.C. & Galappaththi, G.K.K.T. & Sampath, M.A. & Nipunika, H.N. & Rankothge, Windhya. (2018). Experimental study on an efficient dengue disease management system: Planning and optimizing hospital staff allocation. International Journal of Advanced Computer Science and Applications. 9. 50-54. 10.14569/IJACSA.2018.091107.
Series/Report no.: International Journal of Advanced Computer Science and Applications;9(11):50-54
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 outbreaks, 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.
URI: http://rda.sliit.lk/handle/123456789/2751
ISSN: 2158-107X
Appears in Collections:Department of Computer Systems Engineering-Scopes
Research Papers - Dept of Computer Systems Engineering
Research Papers - Open Access Research
Research Papers - SLIIT Staff Publications

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