https://doi.org/10.1051/epjconf/201715306004
A versatile multi-objective FLUKA optimization using Genetic Algorithms
1 Dep EN, CERN CH-1211, Switzerland
2 Medical University of Vienna, Austria
3 Accelerator and Technology Sector, CERN CH-1211, Switzerland
a Corresponding author: Vasilis.Vlachoudis@cern.ch
Published online: 25 September 2017
Quite often Monte Carlo simulation studies require a multi phase-space optimization, a complicated task, heavily relying on the operator experience and judgment. Examples of such calculations are shielding calculations with stringent conditions in the cost, in residual dose, material properties and space available, or in the medical field optimizing the dose delivered to a patient under a hadron treatment. The present paper describes our implementation inside flair[1] the advanced user interface of FLUKA[2,3] of a multi-objective Genetic Algorithm[Erreur ! Source du renvoi introuvable.] to facilitate the search for the optimum solution.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
