A New P System Based Genetic Algorithm

2016 ◽  
Vol 4 (1) ◽  
pp. 165
Author(s):  
Caiping Hou ◽  
Xiyu Liu
Keyword(s):  
Genetic Algorithm ◽  
Genetic Drift ◽  
Parallel Mechanism ◽  
Membrane Computing ◽  
P System

<p>For the “early convergence” or the “genetic drift” of the genetic algorithm, this paper proposes a new genetic algorithm based on P system. Based on the parallel mechanism of P system in membrane computing, we put forward the new P system based genetic algorithm (PBGA). So that we can improve the performance of GA.</p>

Constructing Attractors via the Improved Eugenics Genetic Algorithm

2014 ◽  
Vol 989-994 ◽  
pp. 1786-1789
Author(s):  
Li Ming Du ◽  
Feng Ying Wang ◽  
Zi Yang Han
Keyword(s):  
Genetic Algorithm ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Genetic Drift ◽  
Chaotic Attractors ◽  
Parameter Vector ◽  
Distance Limit

The paper introduces Monte Carlo method and Eugenics genetic algorithm, which be used to generate a great diversity of chaotic attractors firstly. By an analysis of their algorithms, a improved eugenics genetic algorithm is presented to avoid the "genetic drift" phenomenon in attractor graphics. A parameter vector distance limit is adopted to solve the problem and lots of experiments applying equivalent mappings of frieze group are finished to validate effectiveness for algorithm.

Optimal Design of 6-UPU Parallel Mechanism

2011 ◽  
Vol 480-481 ◽  
pp. 1055-1060
Author(s):  
Guang Hua Wu ◽  
Lie Hang Gong ◽  
Xin Wei Ji ◽  
Zhong Jun Wu ◽  
Yong Jun Gai
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Optimal Design ◽  
Objective Function ◽  
Parallel Mechanism ◽  
Design Space ◽  
Jacobian Matrix ◽  
Optimal Model ◽  
The Real ◽  
Universal Joints

The methodology of the optimal design for the 6-UPU parallel mechanism (PM) is presented based on genetic algorithms. The optimal index which expressed by Jacobian matrix of the PM is first deduced. An optimal model is established, in which the kinematic dexterity of a parallel mechanism is considered as the objective function. The design space, the limiting length of the electric actuators and the limit angles of universal joints are taken as constraints. The real-encoding genetic algorithm is applied to the optimal design of a parallel mechanism, which is proved the validity and advantage for the optimal design of a similar mechanism.

A genetic algorithm calibration method based on convergence due to genetic drift

2008 ◽  
Vol 178 (14) ◽  
pp. 2857-2869 ◽  
Author(s):  
Matthew S. Gibbs ◽  
Graeme C. Dandy ◽  
Holger R. Maier
Keyword(s):  
Genetic Algorithm ◽  
Genetic Drift ◽  
Calibration Method
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