Multilevel scheme parameters optimization of the PO-ML-BSP method by using a simulated annealing algorithm

2007 ◽  
Author(s):  
Javier G. Meana ◽  
Fernando Las-Heras ◽  
Jose A. Martinez
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Parameters Optimization ◽  
Annealing Algorithm

Structural Parameters Optimization of Waveform Generator Based on LS-SVM and Simulated Annealing Algorithm

2012 ◽  
Vol 268-270 ◽  
pp. 871-874
Author(s):  
Yu Liang Yang ◽  
Jun Qi Qin ◽  
Chang Chun Di ◽  
Yan Feng Yang
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Regularization Parameter ◽  
Design Method ◽  
Orthogonal Design ◽  
Structural Parameters ◽  
Parameters Optimization ◽  
Waveform Generator ◽  
Sample Data ◽  
Annealing Algorithm

For the structural design problem of waveform generator, selected diameter of rubber block, hardness and thickness of block 1 and block 2 as five design variables. Firstly, adopted orthogonal design method, and built initial sample data. Secondly, adopted LS-SVM to exercise the sample data, and selected regularization parameter and kernel function width of LS-SVM based on QPSO algorithm. Finally, optimized the structural parameters of waveform generator based on simulated annealing algorithm. The research provided a theoretic basis for the design of waveform generator.

scholarly journals The Parameters Optimization of MCR-WPT System Based on the Improved Genetic Simulated Annealing Algorithm

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Sheng Lu ◽  
Chenyang Zuo ◽  
Changhao Piao
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Global Optimum ◽  
Parameters Optimization ◽  
Selection Strategy ◽  
Local Optimum ◽  
Penalty Function Method ◽  
Genetic Simulated Annealing Algorithm ◽  
Annealing Algorithm ◽  
Optimum Solution

To solve the problem of parameter selection during the design of magnetically coupled resonant wireless power transmission system (MCR-WPT), this paper proposed an improved genetic simulated annealing algorithm. Firstly, the equivalent circuit of the system is analysis in this study and a nonlinear programming mathematical model is built. Secondly, in place of the penalty function method in the genetic algorithm, the selection strategy based on the distance between individuals is adopted to select individual. In this way, it reduces the excess empirical parameters. Meanwhile, it can improve the convergence rate and the searching ability by calculating crossover probability and mutation probability according to the variance of population’s fitness. At last, the simulated annealing operator is added to increase local search ability of the method. The simulation shows that the improved method can break the limit of the local optimum solution and get the global optimum solution faster. The optimized system can achieve the practical requirements.

A New Solution for Maxterm Problem in Trigonometric Functions by Simulated Annealing Algorithm

2013 ◽  
Vol 4 (2) ◽  
pp. 20-28
Author(s):  
Farhad Soleimanian Gharehchopogh ◽  
Hadi Najafi ◽  
Kourosh Farahkhah
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Trigonometric Functions ◽  
Matlab Software ◽  
Annealing Algorithm ◽  
Do So

The present paper is an attempt to get total minimum of trigonometric Functions by Simulated Annealing. To do so the researchers ran Simulated Annealing. Sample trigonometric functions and showed the results through Matlab software. According the Simulated Annealing Solves the problem of getting stuck in a local Maxterm and one can always get the best result through the Algorithm.

Sign in / Sign up

Export Citation Format

Share Document