Creator:
Smołka, Maciej ; Schaefer, Robert ; Paszyński, Maciej ; Pardo, David ; Álvarez-Aramberri, Julen
Contributor:
Byrski, Aleksander - ed. ; Kisiel-Dorohinicki, Marek - ed. ; Dobrowolski, Grzegorz - ed.
Title:
An agent-oriented hierarchic strategy for solving inverse problems
Subtitle:
Group publication title:
Subject and Keywords:
inverse problems ; hybrid optimization methods ; memetic algorithms ; multi-agent systems ; magnetotelluric data inversion
Abstract:
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. ; The computational cost is further decreased by the strategy employed for solution inter-processing and fitness deterioration. The HMS efficiency is compared with the results of a standard evolutionary technique, as well as with the multi-start strategy on benchmarks that exhibit typical inverse problems` difficulties. Finally, an HMS application to a real-life engineering problem leading to the identification of oil deposits by inverting magnetotelluric measurements is presented. The HMS applicability to the inversion of magnetotelluric data is also mathematically verified.
Publisher:
Zielona Góra: Uniwersytet Zielonogórski
Resource Type:
DOI:
Pages:
Source:
AMCS, volume 25, number 3 (2015) ; click here to follow the link