Selfish Gene Algorithm Vs Genetic Algorithm: A Review

International Engineering Research and Innovation Symposium

Ariff, Norharyati Md^1 ; Khalid, Noor Elaiza Abdul^1 ; Hashim, Rathiah^2 ; Noor, Noorhayati Mohamed^1

Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Shah Alam, Selangor, Malaysia^1

Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Parit Raja, Malaysia^2

关键词: Darwinian theory;    Evolutionary algorithms (EAs);    Heterogeneous clusters;    Multi core;    Parallel processing;    Selfish genes;    Task partitioning;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/160/1/012098/pdf
DOI  :  10.1088/1757-899X/160/1/012098

来源: IOP

【 摘 要 】

Evolutionary algorithm is one of the algorithms inspired by the nature. Within little more than a decade hundreds of papers have reported successful applications of EAs. In this paper, the Selfish Gene Algorithms (SFGA), as one of the latest evolutionary algorithms (EAs) inspired from the Selfish Gene Theory which is an interpretation of Darwinian Theory ideas from the biologist Richards Dawkins on 1989. In this paper, following a brief introduction to the Selfish Gene Algorithm (SFGA), the chronology of its evolution is presented. It is the purpose of this paper is to present an overview of the concepts of Selfish Gene Algorithm (SFGA) as well as its opportunities and challenges. Accordingly, the history, step involves in the algorithm are discussed and its different applications together with an analysis of these applications are evaluated.