# An agent-oriented hierarchic strategy for solving inverse problems

Maciej Smołka; Robert Schaefer; Maciej Paszyński; David Pardo; Julen Álvarez-Aramberri

International Journal of Applied Mathematics and Computer Science (2015)

- Volume: 25, Issue: 3, page 483-498
- ISSN: 1641-876X

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topMaciej Smołka, et al. "An agent-oriented hierarchic strategy for solving inverse problems." International Journal of Applied Mathematics and Computer Science 25.3 (2015): 483-498. <http://eudml.org/doc/271762>.

@article{MaciejSmołka2015,

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.},

author = {Maciej Smołka, Robert Schaefer, Maciej Paszyński, David Pardo, Julen Álvarez-Aramberri},

journal = {International Journal of Applied Mathematics and Computer Science},

keywords = {inverse problems; hybrid optimization methods; memetic algorithms; multi-agent systems; magnetotelluric data inversion},

language = {eng},

number = {3},

pages = {483-498},

title = {An agent-oriented hierarchic strategy for solving inverse problems},

url = {http://eudml.org/doc/271762},

volume = {25},

year = {2015},

}

TY - JOUR

AU - Maciej Smołka

AU - Robert Schaefer

AU - Maciej Paszyński

AU - David Pardo

AU - Julen Álvarez-Aramberri

TI - An agent-oriented hierarchic strategy for solving inverse problems

JO - International Journal of Applied Mathematics and Computer Science

PY - 2015

VL - 25

IS - 3

SP - 483

EP - 498

AB - 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.

LA - eng

KW - inverse problems; hybrid optimization methods; memetic algorithms; multi-agent systems; magnetotelluric data inversion

UR - http://eudml.org/doc/271762

ER -

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