AbstractID: 9183 Title: Optimization of beam intensities with evolutionary programming
algorithms
This work applies the evolutionary programming algorithms used in other disciplines to the optimization of treatment beam intensities
in intensity modulated radiotherapy (IMRT). The evolutionary programming algorithms adopt mutation based reproduction
mechanisms in generating new trial solutions. They are independent of the building block hypothesis which is the base of genetic
algorithms and expected to generate better trial solutions than the genetic algorithms when applied to the non-biological problem of
treatment plan optimization. The self-adaptive step size perturbation strategy in the evolutionary programming algorithms prevents the
pre-mature convergence to a local minimum which likely happens to simulated annealing algorithms with deterministic cooling
schemes. An evolutionary programming algorithm has been investigated and applied to optimize the treatment beam intensities.
Clinically satisfactory dose distributions in the optimized plans have been observed. The evolutionary programming algorithm can be
used on optimizing IMRT treatment plans with the potential to overcome aforementioned limitations of genetic and simulated
annealing algorithms.