  Radiotherapy dosimetry plays a crucial role in optimizing treatment plans for
cancer patients. In this study, we investigate the performance of a dozen
standard state-of-the-art open-source optimizers for radiotherapy dosimetry.
Our evaluation includes the use of TGG119 benchmark cases as well as one real
case obtained from the Institute du Cancer de Montpellier (ICM). Among the
tested optimizers, Newton CG demonstrates the fastest convergence in terms of
the number of iterations. However, when considering the computation time per
iteration, LBFGS emerges as the most efficient optimizer. These findings shed
light on the performance of open-source optimizers for radiotherapy dosimetry,
aiding practitioners in selecting suitable optimization tools for efficient
treatment planning.
