GPU Accelerated Genetic Algorithm for Multiple Gravity-Assist and Impulsive V Maneuvers

2012 ◽  
Author(s):  
Sam Wagner ◽  
Brian Kaplinger ◽  
Bong Wie
Keyword(s):  
Genetic Algorithm ◽  
Gravity Assist

scholarly journals Use of a evolutionary algorithm to optimize interplanetary transfers

2021 ◽  
Vol 6 (3) ◽  
Author(s):  
Guilherme Marcos Neves ◽  
Denilson Paulo Souza dos Santos
Keyword(s):  
Genetic Algorithm ◽  
Numerical Methods ◽  
Space Vehicle ◽  
Close Approach ◽  
Low Thrust ◽  
Gravity Assist ◽  
Total Impulse ◽  
Gravity Assist Maneuver ◽  
The Cost ◽  
Interplanetary Missions

In this paper, it was studied the optimization of the cost of interplanetary missions with emphasis on reducing fuel consumption. To achieve this goal, a genetic algorithm was implemented to optimize the total impulse of orbital transfer. It was implemented a case of sending a space vehicle from Earth to a another planet using a gravity assist maneuver (swing by), in this paper it was chose sending a spacecraft from Earth to Mars with a close approach to the Venus. The method employed can be used for impulsive interplanetary missions in general, and so the solution found can become an initial solution for numerical methods of optimization of low thrust maneuvers

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

Sign in / Sign up

Export Citation Format

Share Document