scholarly journals A route optimization method based on simulated annealing algorithm for wind-assisted ships

2019 ◽  
Vol 295 ◽  
pp. 042074
Author(s):  
Yuankui Li ◽  
Chunfu Qiao
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Optimization Method ◽  
Route Optimization ◽  
Annealing Algorithm

Free Parameter Optimization of DTMDs Based on Improved Hybrid Genetic-Simulated Annealing Algorithm

2020 ◽  
Vol 20 (03) ◽  
pp. 2050031
Author(s):  
Qiang Han ◽  
Xuan Zhang ◽  
Kun Xu ◽  
Xiuli Du
Keyword(s):  
Simulated Annealing ◽  
Parameter Optimization ◽  
Free Parameter ◽  
Simulated Annealing Algorithm ◽  
Optimization Method ◽  
Design Parameters ◽  
Mass Ratio ◽  
Tuned Mass Dampers ◽  
Genetic Simulated Annealing Algorithm ◽  
Annealing Algorithm

The optimum design of distributed tuned mass dampers (DTMDs) is normally based on predefined restrictions, such as the location and/or mass ratio of the tuned mass dampers (TMDs). To further improve the control performance, a free parameter optimization method (FPOM) is proposed. This method only restricts the total mass of the DTMDs system and takes the installation position, mass ratio, stiffness and damping of each TMD as parameters to be optimized. An improved hybrid genetic-simulated annealing algorithm (IHGSA) is adopted to find the optimum values of the design parameters. This algorithm can solve the non-convexity and multimodality problems of the objective function and is quite effective in dealing with the large amount of computations in the free parameter optimization. A numerical benchmark model is adopted to compare the control efficiency of FPOM with conventional control scenarios, such as single TMD, multiple TMDs and DTMDs optimized through conventional methods. The results show that the DTMDs system optimized by using FPOM is superior to the other control scenarios for the same value of mass ratio.

The Application and Comparison of Two Different Optimization Algorithms in the Optimization Design of Hydrofoil

2012 ◽  
Vol 178-181 ◽  
pp. 2871-2876
Author(s):  
Chao Wang ◽  
Feng Feng ◽  
Xin Chang ◽  
Chun Yu Guo ◽  
Yang Hao Liu
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Optimization Design ◽  
Simulated Annealing Algorithm ◽  
Optimization Algorithms ◽  
Optimization Method ◽  
Flow Solver ◽  
Propeller Design ◽  
Section Design ◽  
Annealing Algorithm

Hydrofoil is the important part of ship design and diverse motion equipment. The optimization design of hydrofoil section on lift-to-drag radio with genetic algorithm (GA) and simulated annealing algorithm are demonstrated, and the method on the hydrofoil section design of the propeller design will be done. Objective function and fitness of every individual are provided by flow solver of panel method. The optimization method on design of hydrofoil section on lift-to-drag is successfully used. The optimization results show the combination of optimization algorithm is feasible at the optimal design of hydrofoil sections. What’s more, a comparison between two different optimization algorithms is made, a conclusion that the simulated annealing algorithm is better then the genetic algorithm is obtained.

Research on Optimal Deployment of HWSN Node Cost Based on Simulated Annealing Algorithm

2014 ◽  
Vol 651-653 ◽  
pp. 1921-1924
Author(s):  
Ji Tao Shen ◽  
Jun Yang Zhang
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Fault Tolerant ◽  
Monitoring Network ◽  
Optimization Method ◽  
Perception Model ◽  
Annealing Algorithm ◽  
Target Monitoring ◽  
The Cost ◽  
Network Fault Tolerance

An optimal heterogeneous sensor differentiated deployment schemes based on simulated annealing algorithm is proposed to solve the problems of the high density of distributing heterogeneity nodes in WSN and geographical irregularity of the sensed event. This method can not only apply to Boolean perception model of the node, but also apply to perception model. The algorithm uses the cost of sensors deployment as objective function in the context of assuring the coverage and fault tolerant of networks. The simulation results show that, the optimization method proposed in this paper can effectively convergence, under the premise to ensure network fault tolerance and robustness, reduces the cost of network deployment, improve the quality of target monitoring network.

Query Optimization Based on the Simulated Annealing and Particle Swarm Optimization

2012 ◽  
Vol 229-231 ◽  
pp. 1870-1873
Author(s):  
Ren Jie Song ◽  
Yan Wang
Keyword(s):  
Simulated Annealing ◽  
Query Optimization ◽  
Simulated Annealing Algorithm ◽  
Particle Swarm ◽  
Optimization Method ◽  
Particle Swarm Algorithm ◽  
Algorithm Optimization ◽  
Optimal Value ◽  
Global Optimal ◽  
Annealing Algorithm

In order to allow the user to quickly and accurately search the required information, a query optimization method based on a simulated annealing and particle swarm hybrid algorithm is proposed. The basic idea is: the query population into two flat sub populations, a sub population by using simulated annealing algorithm optimization, another sub populations by using particle swarm algorithm optimization, comparison of two adaptive values, to find the global optimal value. The experimental results show that the mixed algorithm, can further improve the precision and recall of query optimization.

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