Approximating landscape insensitivity regions in solving ill-conditioned inverse problems
| Autor: | Robert Schaefer, Jakub Sawicki, Julen Álvarez-Aramberri, Maciej Smołka, Marcin Łoś |
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| Rok vydání: | 2018 |
| Předmět: |
Control and Optimization
General Computer Science Computer science Complex system Inversion (meteorology) 02 engineering and technology Inverse problem Tumor tissue Magnetotellurics 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Cluster analysis Algorithm Metaheuristic Global optimization problem |
| Zdroj: | Memetic Computing. 10:279-289 |
| ISSN: | 1865-9292 1865-9284 |
| DOI: | 10.1007/s12293-018-0258-5 |
| Popis: | Solving ill-posed continuous, global optimization problems is challenging. No well-established methods are available to handle the objective intensity that appears when studying the inversion of non-invasive tumor tissue diagnosis or geophysical applications. The paper presents a complex metaheuristic method that identifies regions of objective function’s insensitivity (plateaus). It is composed of a multi-deme hierarchic memetic strategy coupled with random sample clustering, cluster integration, and a special kind of local evolution processes using the multiwinner selection that allows to breed the demes to cover each plateau separately. The final phase consists in a smooth local objective approximation which determines the shape of the plateaus by analyzing the objective level sets. We test the method on benchmarks with multiple non-convex plateaus and in an actual geophysical application of magnetotelluric data inversion. |
| Databáze: | OpenAIRE |
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