Evaluation of fast evolutionary programming, firefly algorithm and mutate-cuckoo search algorithm in single-objective optimization / Muhammad Zakyizzuddin Rosselan, Shahril Irwan Sulaiman and Norhalida Othman

- In this study proposes an evaluation of different computational intelligences, i.e Fast-Evolutionary Algorithm (FEP), Firefly Algorithm (FA) and Mutate-Cuckoo Search Algorithm (MCSA) for solving single-objective optimization problem. FEP and MCSA are based on the conventional Evolutionary Programm...

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Main Authors: Rosselan, Muhammad Zakyizzuddin (Author), Sulaiman, Shahril Irwan (Author), Othman, Norhalida (Author)
Format: Book
Published: UiTM Press, 2016-12.
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100 1 0 |a Rosselan, Muhammad Zakyizzuddin  |e author 
700 1 0 |a Sulaiman, Shahril Irwan  |e author 
700 1 0 |a Othman, Norhalida  |e author 
245 0 0 |a Evaluation of fast evolutionary programming, firefly algorithm and mutate-cuckoo search algorithm in single-objective optimization / Muhammad Zakyizzuddin Rosselan, Shahril Irwan Sulaiman and Norhalida Othman 
260 |b UiTM Press,   |c 2016-12. 
500 |a https://ir.uitm.edu.my/id/eprint/62998/1/62998_1.pdf 
520 |a - In this study proposes an evaluation of different computational intelligences, i.e Fast-Evolutionary Algorithm (FEP), Firefly Algorithm (FA) and Mutate-Cuckoo Search Algorithm (MCSA) for solving single-objective optimization problem. FEP and MCSA are based on the conventional Evolutionary Programming (EP) and Cuckoo Search Algorithm (CSA) with modifications and adjustment to boost up their search ability. In this paper, four different benchmark functions were used to compare the optimization performance of these three algorithms. The results showed that MCSA is better compare with FEP and FA in term of fitness value while FEP is fastest algorithm in term of computational time compare with other two algorithms. 
546 |a en 
690 |a Computer engineering. Computer hardware 
655 7 |a Article  |2 local 
655 7 |a PeerReviewed  |2 local 
787 0 |n https://ir.uitm.edu.my/id/eprint/62998/ 
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