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 Pro...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
UiTM Press
2016
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/62998/1/62998_1.pdf https://ir.uitm.edu.my/id/eprint/62998/ https://jeesr.uitm.edu.my/v1/ |
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| Institution: | Universiti Teknologi Mara |
| Language: | English |
| Summary: | — 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. |
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