Physics Commons^™

Innovative Applications Of Genetic Algorithms To Problems In Accelerator Physics, Alicia Hofler, Balša Terzić, Matthew Kramer, Anton Zvezdin, Vasiliy Morozov, Yves Roblin, Fanglei Lin, Colin Jarvis

Physics Faculty Publications

The genetic algorithm (GA) is a powerful technique that implements the principles nature uses in biological evolution to optimize a multidimensional nonlinear problem. The GA works especially well for problems with a large number of local extrema, where traditional methods (such as conjugate gradient, steepest descent, and others) fail or, at best, underperform. The field of accelerator physics, among others, abounds with problems which lend themselves to optimization via GAs. In this paper, we report on the successful application of GAs in several problems related to the existing Continuous Electron Beam Accelerator Facility nuclear physics machine, the proposed Medium-energy Electron-Ion …