Autor: Steffen, Jr, V. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: A new multi-objective optimization algorithm based on differential evolution and neighborhood exploring evolution strategy
Autorzy:: Lobato, F. S.
Steffen, Jr, V.
Powiązania:: https://bibliotekanauki.pl/articles/91590.pdf
Data publikacji:: 2011
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: multi-objective optimization
differential evolution
neighborhood exploring
evolution strategy
sorting strategy
Opis:: In this paper a new optimization algorithm based on Differential Evolution, non-dominated sorting strategy and neighborhood exploration strategy for guaranteeing convergence and diversity through the generation of neighborhoods of different sizes to potential candidates in the population is presented. The performance of the algorithm proposed is validated by using standard test functions and metrics commonly adopted in the specialized literature. The sensitivity analysis of some relevant parameters of the algorithm is performed and compared with the classical DE algorithm without the strategy of neighborhood exploration and with other state-of-the-art evolutionary algorithms.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2011, 1, 4; 259-267
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Solution of singular optimal control problems using the improved differential evolution algorithm
Autorzy:: Lobato, F. S.
Steffen, Jr, V.
Silva Neto, A. J.
Powiązania:: https://bibliotekanauki.pl/articles/91654.pdf
Data publikacji:: 2011
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: differential evolution algorithm
optimal control
dynamic updating
population
convergence rate
mechanical engineering
chemical engineering
Opis:: The Differential Evolution algorithm, like other evolutionary techniques, presents as main disadvantage the high number of objective function evaluations as compared with classical methods. To overcome this disadvantage, this work proposes a new strategy for the dynamic updating of the population size to reduce the number of objective function evaluations. This strategy is based on the definition of convergence rate to evaluate the homogeneity of the population in the evolutionary process. The methodology is applied to the solution of singular optimal control problems in chemical and mechanical engineering. The results demonstrated that the methodology proposed represents a promising alternative as compared with other competing strategies.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2011, 1, 3; 195-206
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

Artykuł

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