Szczegóły publikacji
Opis bibliograficzny
Approximating landscape insensitivity regions in solving ill-conditioned inverse problems / Jakub SAWICKI, Marcin ŁOŚ, Maciej SMOŁKA, Robert SCHAEFER, Julen Álvarez-Aramberri // Memetic Computing ; ISSN 1865-9284. — 2018 — vol. 10 iss. 3, s. 279–289. — Bibliogr. s. 288–289, Abstr. — Publikacja dostępna online od: 2018-04-04
Autorzy (5)
- AGHSawicki Jakub
- AGHŁoś Marcin Mateusz
- AGHSmołka Maciej
- AGHSchaefer Robert
- Alvarez-Aramberri Julen
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 115739 |
|---|---|
| Data dodania do BaDAP | 2018-09-05 |
| Tekst źródłowy | URL |
| DOI | 10.1007/s12293-018-0258-5 |
| Rok publikacji | 2018 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Memetic Computing |
Abstract
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.
