Multi-objective Hierarchic Memetic Solver for Inverse Parametric Problems

We propose a multi-objective approach for solving challenging inverse parametric problems. The objectives are misfits for several physical descriptions of a phenomenon under consideration, whereas their domain is a common set of admissible parameters. The resulting Pareto set, or parameters close to...

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Bibliographic Details
Published in:Procedia computer science Vol. 51; pp. 974 - 983
Main Authors: Gajda-Zagórska, Ewa, Smołka, Maciej, Schaefer, Robert, Pardo, David, Álvarez-Aramberri, Julen
Format: Journal Article
Language:English
Published: Elsevier B.V 2015
Subjects:
inverse problems
memetic algorithms
multi-objective optimization methods
memetic algorithms
multi-objective optimization methods
inverse problems
ISSN:1877-0509, 1877-0509
Online Access:Get full text
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Summary:We propose a multi-objective approach for solving challenging inverse parametric problems. The objectives are misfits for several physical descriptions of a phenomenon under consideration, whereas their domain is a common set of admissible parameters. The resulting Pareto set, or parameters close to it, constitute various alternatives of minimizing individual misfits. A special type of selection applied to the memetic solution of the multi-objective problem narrows the set of alternatives to the ones that are sufficiently coherent. The proposed strategy is exemplified by solving a real-world engineering problem consisting of the magnetotelluric measurement inversion that leads to identification of oil deposits located about 3km under the Earth's surface, where two misfit functions are related to distinct frequencies of the electric and magnetic waves.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2015.05.239