Abstract
This chapter explores the use of genetic algorithms as a tool for calculating the kinetic parameters of the thermoluminescence curve. Genetic algorithm is a search algorithm inspired by the process of natural selection, and it has proven to be effective in solving optimization problems in various fields. Author used genetic algorithm to estimate the activation energy and frequency factor of the thermoluminescence curve, which are important parameters in determining the dosimetric properties of materials. The results showed that genetic algorithm could accurately estimate the kinetic parameters of the thermoluminescence curve with high precision and efficiency compared to conventional methods. This approach can also handle noisy data and reduce the impact of outliers on the estimation process. Furthermore, author demonstrated that genetic algorithm can be generalized to different types of the thermoluminescence curves, such as those generated by different materials or under different experimental conditions. The proposed method is fast, accurate, and robust, making it useful for researchers in the field of dosimetry who require precise estimations of these parameters.