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 mate-
rials. The results showed that genetic algorithm could accurately estimate the kinetic
parameters of the thermoluminescence curve with high precision and efficiency com-
pared 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 thermolumines-
cence curves, such as those generated by different materials or under different exper-
imental 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.