The Analysis and Improvement of Inverse Problem Simulated Annealing Algorithm about Concrete Temperature Field

2013 ◽  
Vol 275-277 ◽  
pp. 2611-2615
Author(s):  
Lun Yan Wang ◽  
Lei Guo ◽  
Hui Min Yuan
Keyword(s):  
Inverse Problem ◽  
Temperature Field ◽  
Simulated Annealing ◽  
Temperature Control ◽  
Simulated Annealing Algorithm ◽  
Simulated Annealing Method ◽  
Factors Affecting ◽  
Concrete Temperature ◽  
Annealing Algorithm ◽  
Annealing Method

The thermodynamic parameters and boundary conditions is one of the important factors affecting the simulation precision of concrete temperature control, and through the test way obtaining these parameters demands high cost, and often works with practical mismatch. This paper introduces the simulated annealing method, analyse and improve the simulated annealing method . The results show that, the improved of simulated annealing algorithm can be used for the study of concrete temperature field inverse.

scholarly journals A Knowledge-Based Simulated Annealing Algorithm to Multiple Satellites Mission Planning Problems

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Da-Wei Jin ◽  
Li-Ning Xing
Keyword(s):  
Simulated Annealing ◽  
Optimization Problem ◽  
Simulated Annealing Algorithm ◽  
Mission Planning ◽  
Knowledge Based ◽  
Combination Optimization ◽  
Annealing Algorithm ◽  
The Given ◽  
Planning Problems ◽  
Annealing Method

The multiple satellites mission planning is a complex combination optimization problem. A knowledge-based simulated annealing algorithm is proposed to the multiple satellites mission planning problems. The experimental results suggest that the proposed algorithm is effective to the given problem. The knowledge-based simulated annealing method will provide a useful reference for the improvement of existing optimization approaches.

Analysis on Factors Affecting the Employment of Landless Peasants Based on Simulated Annealing Genetic Algorithm

2014 ◽  
Vol 533 ◽  
pp. 536-543
Author(s):  
Zhong Hao Zhu
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Vulnerable Groups ◽  
National Plan ◽  
Land Expropriation ◽  
Factors Affecting ◽  
Simulated Annealing Genetic Algorithm ◽  
Process Of Urbanization ◽  
Annealing Algorithm

In national plan of twelfth five-year, orchestrating city-country development and accelerating process of urbanization will be one of the leading strategies. Large areas of farmland turn to non-agricultural irreversibly in the process of accelerating urbanization, the existing land expropriation system running by planned economic system damage farmers’ rights and incomes. Therefore, as vulnerable groups, landless peasants’ employments need more concern. The study takes Zhenjiang city for an example, proposes a factor selecting method based on the simulated annealing genetic algorithm (SAGA). The factor selecting method is proposed from each subspace, which combines the simulated annealing algorithm with the genetic algorithm in choosing different cross-over and mutation probabilities, as well as mutation individuals. Experimental results show that achieving a significant increase in the employment rate is possible using SAGA obtained from the proposed approach.

Protein Folding Simulation Based on Improved Simulated Annealing Algorithm

2012 ◽  
Vol 424-425 ◽  
pp. 246-249
Author(s):  
Jing Fa Liu ◽  
Zi Ling Zhou ◽  
Ze Xu Gao ◽  
Guo Jian Zhang
Keyword(s):  
Protein Folding ◽  
Simulated Annealing ◽  
Ground State ◽  
Lower Energy ◽  
Simulated Annealing Algorithm ◽  
Two Dimensional ◽  
Folding Simulation ◽  
Simulation Based ◽  
Annealing Algorithm ◽  
Annealing Method

Protein folding problem is one of the most important problems in bioinformatics. By combining simulated annealing method with pull moves which is a local move set and conformation update mechanism, we put forward an improved simulated annealing (ISA) algorithm for the two-dimensional hydrophobic- polar (2D HP) protein folding problem. Numerical results show that the ISA algorithm can find the known lowest-energy ground state more rapidly and efficiently than the genetic algorithm (GA) for the several given HP sequences. For the sequence with length 20, we obtain the lower-energy conformation than GA. The performance of the algorithm show ISA is an effective method for protein folding simulation

Sign in / Sign up

Export Citation Format

Share Document