EpiGenetic Algorithm for Optimization: Application to Mobile Network Frequency Planning
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Dosyalar
Tarih
2016
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Heidelberg
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Genetic algorithms (GA) has been used as a successful algorithm for many problems. GA has been redesigned with different methods or used in hybrid algorithms to solve different problems and improve solutions. In this study, epigenetic algorithm (EGA) design has been made by adapting epigenetic concepts to the classical GA structure. GA is counted as a heuristic research algorithm, and there is randomness in the function of genetic operators. However, owing to some serious research in medical field, it has been shown that through the epigenetics, randomness of crossover and mutation operators can be defined. With regards to this information in the field of medicine, in this study design of EGA, how epicrossover, epimutation operators, and epigenetic factors are made and how they do work and also how the epigenetic inheritance is possible have been told. Our designed EGA has been applied on base stations' BCCH frequency planning in GSM network that is a constrained optimization problem. Real base station's data have been used in solving the problem. EGA and GA coding have been made by using C# programming. In order to analyze the success of EGA than the classical GA, both algorithms have been used in solving of this problem. Because of this, EGA gave better results in a shorter time and less iteration than classical GA's.
Açıklama
WOS: 000371252700010
Anahtar Kelimeler
Epigenetic, Epigenetic algorithm, Epicrossover, Epimutation, Epi-inheritance, Genetic algorithm, Optimization, Frequency planning
Kaynak
Arabian Journal For Science And Engineering
WoS Q Değeri
Q3
Scopus Q Değeri
Q1
Cilt
41
Sayı
3
