Simulation of Influenza Pandemic Based on Genetic Algorithm and Agent-Based Modeling: A Multi-objective Optimization Problem Solving - Ria Lestari Moedomo; Adi Pancoro; Jorga Ibrahim; Adang Suwandi Ahmad; Muhammad Sukrisno Mardiyanto; Mohammad Bahrelfi Belatiff; Hengki Tasman (Jurnal Matematika & Sains, 2010)
This paper describes the analysis, design and development process of simulation software for the Avian Influenza (H5N1) viruses mutation. Influenza Pandemics, which have occurred since 1729, caused by mutation (antigenic drift) and recombination (antigenic shift) of Influenza viruses. The purpose of this research is to define the modeling of virus mutation causing the Influenza Pandemic phenomena. Additionally, the objective of this simulation is to obtain all possible virus strains might be formed from mutation, the scope within this article, which can potentially trigger Influenza Pandemic. These new strains could then be utilized to support the vaccine planning process. The Influenza Pandemic simulation program can be developed based on Genetic Algorithm method, for solving this multi-objective optimization problem. By utilizing the Genetic Algorithm approach, the chromosome solution and fitness values/functions of Influenza Pandemic stages are defined and the maximum fitness values are to be searched. The simulation result of H5N1 mutation gave 3 (three) best fitness values and a more dynamic mean fitness values, including best fitness value from several mutations combination. Simulation program was developed by utilizing MATLABÂ© software, with Genetic Algorithm Toolbox provided.