Using evolutionary algorithm for the optimization of epidemic surveillance and control in networks | |
| Author | Chaipichet Palotaitakerng |
| Call Number | AIT Thesis no.IM-13-03 |
| Subject(s) | Computer algorithms Public health surveillance Epidemiology--Simulation methods |
| Note | A thesis submitted in partial fulfillment of the requirements for thedegree of Master of Engineering inInformation Management |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. IM-13-03 |
| Abstract | In this research study, we appliedan evolutionary algorithm (EA)to study the optimization of epidemic surveillance and control in networks. We use a simulation of infectious disease stochastically spread in network as a tool. Disease spread in thesimulation is based onthesusceptible-infected-recovered (SIR)epidemic model. The EA evaluates the fitness of each solution bythe results of the simulation. The EA is applied to obtain the optimum outcomes, the sets of the optimum valuefor the variablesof epidemic surveillance and control. The optimum outcomesexhibitlow infected population and low cost of thesurveillance and control. The results which are obtained by using EA have beenstudied to conclude the effects of network topology and EA fitness function to the results. |
| Year | 2013 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. IM-13-03 |
| Type | Thesis |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Information Management (IM) |
| Chairperson(s) | Duboz Raphaël |
| Examination Committee(s) | Guha, Sumanta;Phan Minh Dung |
| Scholarship Donor(s) | Royal Thai Government -AIT Fellowship |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2013 |