An Improved Genetic Algorithm Approach on Mechanism Kinematic Structure Enumeration with Intelligent Manufacturing

2017 ◽  
Vol 89 (3-4) ◽  
pp. 343-350 ◽  
Author(s):  
Hao Liu ◽  
Shunyi Shi ◽  
Ping Yang ◽  
Jianming Yang
Keyword(s):  
Genetic Algorithm ◽  
Intelligent Manufacturing ◽  
Kinematic Structure ◽  
Improved Genetic Algorithm ◽  
Genetic Algorithm Approach ◽  
Mechanism Kinematic ◽  
Structure Enumeration

Intelligent Design of Mechanism Kinematic Chains by Advanced Optimal Methods

2011 ◽  
Vol 201-203 ◽  
pp. 2182-2185
Author(s):  
Miao Zhang ◽  
Ning Bo Liao ◽  
Chen Zhou ◽  
Xi Tao
Keyword(s):  
Graph Theory ◽  
Intelligent Design ◽  
Kinematic Structure ◽  
Kinematic Chains ◽  
Complicated Problem ◽  
Optimal Methods ◽  
Advantages And Disadvantages ◽  
Mechanism Kinematic ◽  
Isomorphism Identification ◽  
Structure Enumeration

When using graph theory to conduct intelligent design for kinematic structure enumeration, the isomorphism identification of graphs is an important and complicated problem. In this paper, the methodology of transferring isomorphism identification into optimization issue was introduced. Then the recent development of applying advanced optimal methods for isomorphism identification was reviewed, the advantages and disadvantages of there methods were discussed.

An improved genetic algorithm approach for on-line optimisation problems

2011 ◽  
Vol 22 (8) ◽  
pp. 742-753 ◽  
Author(s):  
Benoît Saenz de Ugarte ◽  
Robert Pellerin ◽  
Abdelhakim Artiba
Keyword(s):  
Genetic Algorithm ◽  
Improved Genetic Algorithm ◽  
On Line ◽  
Genetic Algorithm Approach

Optimization of Fuzzy Logic Rules Based on Improved Genetic Algorithm

2010 ◽  
Vol 44-47 ◽  
pp. 1496-1499 ◽  
Author(s):  
Rui Zhen Gao ◽  
Zhi Qiang Xu ◽  
Jing Jun Zhang
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Suspension System ◽  
System Model ◽  
Improved Genetic Algorithm ◽  
Matlab Simulink ◽  
Passive Suspension ◽  
Car Suspension ◽  
Genetic Algorithm Approach

This paper completes a full car semi-active suspension system model, using improved genetic algorithm approach to optimize the fuzzy logic rules and the co-simulation were carried out in the environment of Matlab/Simulink. The results of being compared with the passive suspension demonstrate is that this developed fuzzy logic controller based on genetic algorithm enhances the performance of the full car suspension system significantly.

An Improved Genetic Algorithm Approach to the Unit Commitment/Economic Dispatch Problem

2020 ◽  
Vol 35 (5) ◽  
pp. 4005-4013
Author(s):  
Roberto Ponciroli ◽  
Nicolas E. Stauff ◽  
Jackson Ramsey ◽  
Francesco Ganda ◽  
Richard B. Vilim
Keyword(s):  
Genetic Algorithm ◽  
Unit Commitment ◽  
Economic Dispatch ◽  
Improved Genetic Algorithm ◽  
Genetic Algorithm Approach ◽  
Economic Dispatch Problem

Studying of Fuzzy Logic Control for Semi-Active Suspension Based on Improved Genetic Algorithm

2010 ◽  
Vol 143-144 ◽  
pp. 929-932
Author(s):  
Jing Jun Zhang ◽  
Zhi Qiang Xu
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Active Suspension ◽  
Suspension System ◽  
Improved Genetic Algorithm ◽  
Logic Control ◽  
Car Suspension ◽  
Genetic Algorithm Approach

Establishing a 2-DOFs of 1/4 semi-active suspension system model, using genetic algorithm approach, to design fuzzy logic controller of the semi-active suspension and simulate in the environment of Matlab/Simulink. The results of being compared with the passive suspension demonstrate is that this developed fuzzy logic controller based on genetic algorithm enhances the performance of the full car suspension system significantly.

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