Hybrid optimization for a binary inverse problem
Richard Krahenbuhl, Yaoguo Li · 2004
We have developed a hybrid optimization algorithm for inversion of gravity data using a binary formulation. The new algorithm utilizes the Genetic Algorithm (GA) as a global search tool, while implementing Quenched Simulated Annealing (QSA) intermittently for local search. The hybrid has significantly decreased computational cost over GA or Simulated Annealing (SA) alone and has allowed for successful inversion of more realistic gravity problems. We illustrate the algorithm using a large 2½D model derived from the SEG/EAGE 3D salt model, which has a complex background density profile and a pronounced nil zone.