Performance and parameterization of the algorithm Simplified Generalized Simulated Annealing
Saved in:
| Main Author: | |
|---|---|
| Publication Date: | 2004 |
| Other Authors: | , , |
| Format: | Article |
| Language: | eng |
| Source: | Repositório Institucional da UnB |
| Download full: | http://repositorio.unb.br/handle/10482/26286 https://dx.doi.org/10.1590/S1415-47572004000400024 |
Summary: | The main goal of this study is to find the most effective set of parameters for the Simplified Generalized Simulated Annealing algorithm, SGSA, when applied to distinct cost function as well as to find a possible correlation between the values of these parameters sets and some topological characteristics of the hypersurface of the respective cost function. The SGSA algorithm is an extended and simplified derivative of the GSA algorithm, a Markovian stochastic process based on Tsallis statistics that has been used in many classes of problems, in particular, in biological molecular systems optimization. In all but one of the studied cost functions, the global minimum was found in 100% of the 50 runs. For these functions the best visiting parameter, qV, belongs to the interval [1.2, 1.7]. Also, the temperature decaying parameter, qT, should be increased when better precision is required. Moreover, the similarity in the locus of optimal parameter sets observed in some functions indicates that possibly one could extract topological information about the cost functions from these sets. |
Similar Items: Performance and parameterization of the algorithm Simplified Generalized Simulated Annealing
- Modelo neural recozido para a representação semântica de documentos por meio de vetores contínuos
- Generalized vector equilibrium problems and algorithms for variational inequality in hadamard manifolds
- Estimation results for the Generalized Langevin Equation with Lévy Jumps
- A participação de atores e atrizes na simulação realística, em medicina : uma experiência com pacientes simulados em Brasília/DF
- A simplified Excel® algorithm for estimating the least limiting water range of soils
- Comparative Study of Optimization Algorithms for Parameter Identification Of the Sigmoid Model in MR Dampers