scholarly journals AUTONOMOUS GENETIC ALGORITHM FOR FUNCTIONAL OPTIMIZATION

2007 ◽  
Vol 72 ◽  
pp. 253-268 ◽  
Author(s):  
Zhiqi Meng
Keyword(s):  
Genetic Algorithm ◽  
Functional Optimization

scholarly journals THE MATHEMATICAL AND SOFTWARE OF DECISION SUPPORT MAKING DURING THE PROCESS OF FORMATION THE SCHEDULE OF EDUCATION ACTIVITIES

2019 ◽  
Vol 2018 (2) ◽  
pp. 9-20
Author(s):  
Людмила Козак ◽  
Lyudmila Kozak ◽  
Ольга Сташкова ◽  
Olga Stashkova ◽  
Елена Гарбузняк ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Decision Support ◽  
Optimization Problems ◽  
Educational Institution ◽  
Optimal Schedule ◽  
Adaptive Search ◽  
Search Methods ◽  
Functional Optimization ◽  
Software Product ◽  
The Subject

The article entitled “The mathematical and software of decision support making during the process of formation the schedule of education activities” is devoted to the problem of automating the formation of a classroom schedule in a higher educational institution. The article consists of an introduction, five sections, conclusions and references. The first section provides a justification for the choice of implementation method. The second section is devoted to the description of the algorithms used. The third section indicates the means of implementing a software product, presents an information-logical database model for the “Schedule” system. The fourth section describes the logical structure of the software product. The fifth section presents the results of the implementation and testing of the software product. The purpose of the study is the development and implementation of a software system designed to automate the process of compiling a classroom schedule in the branch of the Transdniestrian State University. T.G. Shevchenko in Rybnitsa. The object of the study is the automation of the formation of the schedule of classrooms. The subject of the research is the implementation of a genetic algorithm as one of the adaptive search methods for solving functional optimization problems in order to automate the generation of a schedule. At the stage of the research of the subject area, the methodology of scheduling in universities was studied. There are not so many developments in the automation of scheduling tasks. This suggests that this task is relevant and unified approaches to its solution still does not exist. A new approach to the implementation of solving the problem of finding the optimal schedule was the application of an expert approach based on the use of a genetic algorithm. The authors describe the feasibility of using the genetic algorithm as one of the adaptive search methods for solving functional optimization problems in order to automate the formation of the schedule. Evaluating the work as a whole, it can be argued that the practical significance and prospects of development of this research direction is obvious.

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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