Design Simulation Program of Runway Capacity Using Genetic Algorithm at Soekarno-Hatta

2011 ◽  
Vol 1 (2) ◽  
Author(s):  
Hoga Saragih ◽  
Indra Sulistyo Wibowo ◽  
Wisnu Darjono Tulodo Utomo ◽  
Rusdianto Roestam
Keyword(s):  
Genetic Algorithm ◽  
Simulation Program

scholarly journals Design Simulation Program of Runway Capacity Using Genetic Algorithm At Soekarno-Hatta Airport

2011 ◽  
Vol 5 (1) ◽  
pp. 11
Author(s):  
Hoga Saragih ◽  
Indra Sulistyo Wibowo ◽  
Wisnu Darjono Tulodo Utomo
Keyword(s):  
Genetic Algorithm ◽  
Key Words ◽  
Efficient Solution ◽  
Simulation Software ◽  
Simulation Program ◽  
Master Plan ◽  
Capacity Increase ◽  
Mathematical Calculation

The purposes of this research are to calculate the capacity of runway with runway capacity simulation software using Genetic Algorithm, and to analyze the efforts which have more profound effect.The result of the hourly runway capacity with the mathematical calculation is 42 operations for arrival only, 110 operations for departure only and 64 operations for mix. To enhance the runway capacity, some strategies are researched, such as reduction of separation to meet criteria set by FAA’s rule, addition of the exit taxiway, addition of the runway according to master plan of Soekamo-Hatta Airport and changing the runway utilization strategies. Out of the four strategies, the most efficient solution is changing the runway utilization strategies (with capacity increase of 35,9 %) and reduction in separation (with capacity increase of 34,4 %). However, the addition of runway has the highest capacity increase, that is 53,9 %..Key Words: genetic algorithm, simulation, runway capacity.

scholarly journals The influence of switched reluctance generator winding parameters on output power at different rotational speeds

2018 ◽  
Vol 19 ◽  
pp. 01031
Author(s):  
Artur Sliwiński ◽  
Krzysztof Wrobel ◽  
Krzysztof Tomczewski
Keyword(s):  
Genetic Algorithm ◽  
Output Power ◽  
Magnetic Circuit ◽  
Position Angle ◽  
Simulation Program ◽  
Computing Environment ◽  
Two Stage ◽  
Switched Reluctance ◽  
Rotor Position ◽  
Basic Parameters

The paper presents the influence of the winding parameters of a switched reluctance generator on output power at different rotational speeds. All tested generators were designed on the basis of the same magnetic circuit. In the paper the influence of windings parameters on current and torque dependence on the rotor position angle are shown. The calculations were performed in the authors’ own computing environment dedicated to optimisation, based on a two-stage genetic algorithm. A FEMM program was used for magnetostatic calculations, whereas the dynamic calculations were performed on the authors’ own simulation program. The basic parameters of the tested generators were determined during the study.

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.

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