An agent-oriented hierarchic strategy for solving inverse problems - Smołka, Maciej; Schaefer, Robert; Paszyński, Maciej; Pardo, David; Álvarez-Aramberri, Julen (Zielona Góra: Uniwersytet Zielonogórski)
The paper discusses the complex, agent-oriented hierarchic memetic strategy (HMS) dedicated to solving inverse parametric problems. The strategy goes beyond the idea of two-phase global optimization algorithms. The global search performed by a tree of dependent demes is dynamically alternated with local, steepest descent searches. The strategy offers exceptionally low computational costs, mainly because the direct solver accuracy (performed by the hp-adaptive finite element method) is dynamically adjusted for each inverse search step.
Keywords: inverse problems; hybrid optimization methods; memetic algorithms; multi-agent systems; magnetotelluric data inversion