Parametric optimization with evolutionary strategies in particle physics

Evolutionary strategies provide a generic means to find optimum solutions for large-scale numerical problems. The EVA library, an implementation of parallel Evolutionary Algorithms, adds the possibility to run the optimization in parallel on devices ranging from multi-processor machines over clusters to the world wide grid. This paper discusses the application of the EVA library to two distinct computationally expensive physics problems--the optimization of particle signals in histograms and the minimization procedure involved in analysing Dalitz plots