Parameter Estimation for a Model of Ionizing Radiation Effects on Targeted Cells using Genetic Algorithm and Pattern Search Method

A mechanistic model has been used to explain the effect of radiation. Themodel consists of parameters which represent the biological process following ionizingradiation. The parameters in the model are estimated using local and global optimiza-tion algorithms. The aim of this study is to compare the efficiency between local andglobal optimization method, which is Pattern Search and Genetic Algorithm respectively.Experimental data from the cell survival of irradiated HeLa cell line is used to find theminimum value of the sum of squared error (SSE) between experimental data and sim-ulation data from the model. The performance of both methods are compared based onthe computational time and the value of the objective function, SSE. The optimizationprocess is carried out by using the built-in function in MATLAB software. The parameterestimation results show that genetic algorithm is more superior than pattern search forthis problem.