
handle: 20.500.11824/105
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 3 km under the Earth's surface, where two misfit functions are related to distinct frequencies of the electric and magnetic waves.
Inverse problems, multi-objective optimization methods, inverse problems, Memetic algorithms, Multi-objective optimization methods, memetic algorithms
Inverse problems, multi-objective optimization methods, inverse problems, Memetic algorithms, Multi-objective optimization methods, memetic algorithms
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