- Tytuł:
- Advances in development of dedicated evolutionary algorithms for large non-linear constrained optimization problems
- Autorzy:
-
Głowacki, M.
Orkisz, J. - Powiązania:
- https://bibliotekanauki.pl/articles/31343110.pdf
- Data publikacji:
- 2013
- Wydawca:
- Instytut Podstawowych Problemów Techniki PAN
- Tematy:
-
evolutionary algorithms
large non-linear constrained optimization
solution efficiency increase
algorytmy ewolucyjne - Opis:
- Efficient optimization algorithms are of great importance in many scientific and engineering applications. This paper considers development of dedicated Evolutionary Algorithms (EA) based approach for solving large, non-linear, constrained optimization problems. The EA are precisely understood here as decimal-coded Genetic Algorithms consisting of three basic operators: selection, crossover and mutation, followed by several newly developed calculation speed-up techniques. Efficiency increase of the EA computations may be obtained in several ways, including simple concepts proposed here like: solution smoothing and balancing, a posteriori solution error analysis, non-standard use of distributed and parallel calculations, and step-by-step mesh refinement. Efficiency of the proposed techniques has been evaluated using several benchmark tests. These preliminary tests indicate significant speed-up of the large optimization processes involved. Considered are applications of the EA to the sample problem of residual stresses analysis in elastic-plastic bodies being under cyclic loadings, and to a wide class of problems resulting from the Physically Based Approximation (PBA) of experimental data.
- Źródło:
-
IPPT Reports on Fundamental Technological Research; 2013, 4; 25-29
2299-3657 - Pojawia się w:
- IPPT Reports on Fundamental Technological Research
- Dostawca treści:
- Biblioteka Nauki