Fast and accurate reaction dynamics via multiobjective genetic algorithm optimization of semiempirical potentials

The document describes research into using multiobjective genetic algorithms to optimize semiempirical potentials for fast and accurate reaction dynamics simulations. The researchers developed a method to tune semiempirical parameters using a limited set of ab initio calculations to better describe excited state potential energy surfaces. They found that multiobjective optimization was able to find globally accurate potential energy surfaces more efficiently than weighted single-objective optimizations. Analysis of the optimized parameter sets showed they produced stable and physically reasonable results.