Title :
Design and application of an enhanced GA
Author :
Elgothamy, Hatem ; Zohdy, Mohamed A. ; Abdel-Aty-Zohdy, Hoda S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Oakland Univ., Rochester, MI, USA
Abstract :
This paper introduces an enhanced Genetic Algorithm GA that is faster and more efficient than the standard one. A simple 3D convex surface is optimized using different methods, Brute-Force, standard GA, and the enhanced GA. The enhanced GA is able to find the global minima within a certain range by using the least possible number of calculations, which, means less processing time and is robust to parameter selections. Special software was developed using Java for this purpose; also, MS-Excel was used to represent the data map as charts.
Keywords :
Java; genetic algorithms; mathematics computing; 3D convex surface optimization; Brute-Force method; Java; MS-Excel; data map representation; enhanced GA method; enhanced genetic algorithm application; enhanced genetic algorithm design; parameter selections; software development; standard GA method; Algorithm design and analysis; Equations; Genetic algorithms; Java; Mathematical model; Sociology; Standards; bio inspired system; evolutionary algorithm; genetic algorithm; weighted roulette wheel;
Conference_Titel :
Circuits and Systems (MWSCAS), 2014 IEEE 57th International Midwest Symposium on
Conference_Location :
College Station, TX
Print_ISBN :
978-1-4799-4134-6
DOI :
10.1109/MWSCAS.2014.6908552
