Information Technology in an Improved Quantum Genetic Algorithm Based on Dynamic Adjustment of Quantum Rotation Angle

2013 ◽  
Vol 859 ◽  
pp. 577-581
Author(s):  
Hui Xia Li ◽  
Yun Can Xue ◽  
Jian Qiang Zhang ◽  
Qi Wen Yang
Keyword(s):  
Genetic Algorithm ◽  
Information Technology ◽  
Rotation Angle ◽  
Local Optimum ◽  
Dynamic Adjustment ◽  
Excellent Performance ◽  
Simulation Experiments ◽  
Standard Quantum ◽  
Quantum Genetic Algorithm ◽  
Chaos Search

To overcome the shortcomings of precocity and being easily trapped into local optimum of the standard quantum genetic algorithm (QGA) , Information Technology in An Improved Quantum Genetic Algorithm based on dynamic adjustment of the quantum rotation angle of quantum gate (DAAQGA) was proposed. Mutation operation using the quantum not-gate is also introduced to enhance the diversity of population. Chaos search are also introduced into the modified algorithm to improve the search accuracy. Simulation experiments have been carried and the results show that the improved algorithm has excellent performance both in the preventing premature ability and in the search accuracy.

scholarly journals Optimization of Network Coding Resources Based on Improved Quantum Genetic Algorithm

Photonics ◽  
2021 ◽  
Vol 8 (11) ◽  
pp. 502
Author(s):  
Tianyang Liu ◽  
Qiang Sun ◽  
Huachun Zhou ◽  
Qi Wei
Keyword(s):  
Genetic Algorithm ◽  
Network Coding ◽  
Topological Structure ◽  
Rotation Angle ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Resource Optimization ◽  
Quantum Genetic Algorithm ◽  
Adjustment Mechanism ◽  
Adaptive Adjustment

The problem of network coding resource optimization with a known topological structure is NP-hard. Traditional quantum genetic algorithms have the disadvantages of slow convergence and difficulty in finding the optimal solution when dealing with this problem. To overcome these disadvantages, this paper proposes an adaptive quantum genetic algorithm based on the cooperative mutation of gene number and fitness (GNF-QGA). This GNF-QGA adopts the rotation angle adaptive adjustment mechanism. To avoid excessive illegal individuals, an illegal solution adjustment mechanism is added to the GNF-QGA. A solid demonstration was provided that the proposed algorithm has a fast convergence speed and good optimization capability when solving network coding resource optimization problems.

scholarly journals Application of Improved Quantum Genetic Algorithm in Optimization for Surface to Air Anti-Radiation Hybrid Group Force Deployment

2019 ◽  
Vol 37 (5) ◽  
pp. 992-999
Author(s):  
Junliang Ji ◽  
Minle Wang ◽  
Chang'an Shang ◽  
Jiale Gao
Keyword(s):  
Genetic Algorithm ◽  
Radiation Hybrid ◽  
Rotation Angle ◽  
Target Function ◽  
Quantum Genetic Algorithm ◽  
Quantum Vortex ◽  
Support Force ◽  
Electronic Support ◽  
The Relationship ◽  
Hybrid Group

In this paper, the concept and force deployment needs for anti-electronic jamming and defensing air of surface to air anti-radiation hybrid group was presented, the relationship between shield angle, deployment distance and effective electronic interference etc, were analyzed in the background of air raid battle which is with electronic support, force deployment optimization model of surface to air anti-radiation hybrid group was built based on the kill zone target function. In terms of the characteristic of hybrid group force deployment, quantum genetic algorithm (QGA) was improved with self-adaption rotation angle, the problem which was based on a living example was solved with improved QGA. By contrast, the improved QGA is better in the respects of global optimization, rate of convergence and stability than QGA, particle swarm optimization algorithm and quantum vortex algorithm in the problem of optimization for surface to air anti-radiation hybrid group force deployment.

A Novel Quantum Genetic Algorithm for Continuous Function Optimization

2013 ◽  
Vol 816-817 ◽  
pp. 907-914
Author(s):  
Hao Li ◽  
Shi Yong Li
Keyword(s):  
Genetic Algorithm ◽  
Continuous Function ◽  
Global Convergence ◽  
Local Search ◽  
Rotation Angle ◽  
Binary Solution ◽  
Function Optimization ◽  
Quantum Genetic Algorithm ◽  
Function Extremum ◽  
Angle Of Rotation

In this paper, a novel quantum genetic algorithm is proposed. This algorithm compares the probability expectation of the quantum chromosome with the best binary solution to determine rotation angle of rotation gate. Different individual in population evolve with different rate to complete local search and global search simultaneously. Hε gate is used to prevent the algorithm from premature convergence. After analyzing the algorithm and its global convergence, applying this approach to the optimization of function extremum, and comparing with the simple genetic algorithm and the quantum genetic algorithm, the simulation result illustrates that the algorithm has the characteristic of quick convergence speed and high solution precision.

A Novel Quantum Genetic Algorithm Based on Potential

2012 ◽  
Vol 532-533 ◽  
pp. 1434-1439
Author(s):  
Xiao Lei Li ◽  
Fei Meng
Keyword(s):  
Genetic Algorithm ◽  
Convergence Rate ◽  
Experimental Test ◽  
Chromosome Evolution ◽  
Rotation Angle ◽  
Chromosome Length ◽  
Quantum Bit ◽  
Quantum Genetic Algorithm ◽  
Total Potential ◽  
Effective Intensity

Considering different quantum bit having different effective intensity in chromosome evolution, a novel quantum genetic algorithm based on potential is proposed. It makes the magnitude of rotation angle depending on the potential of a quantum bit. It generates the orientation of rotation angle according to the total potential of quantum bit in the chromosome. The character of quantum entangled interference based on potential is introduced. And convergence analysis and rationality analysis are implemented. Experimental test shows that, it can obtain better convergence rate and have less runtime on smaller population size and shorter chromosome length.

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