Evaluation of fast evolutionary programming, firefly algorithm and mutate-cuckoo search algorithm in single-objective optimization. International Journal of Electrical and Electronic Systems Research, 9 (1). pp. 1-5. ISSN 1985-5389 (2016)
Abstract
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.
| Item Type: | Article |
|---|---|
| Keywords: | Computational intelligence, Fast-Evolutionary programming (FEP), Firefly algorithm (FA) |
| Taxonomy: | By Subject > Computer & Mathematical Sciences > Computer Science By Subject > Computer & Mathematical Sciences > Mathematics |
| Local Content Hub: | Subjects > Computer and Mathematical Sciences |
| Depositing User: | Wan Hamid Wan Fatimah |
| Date Deposited: | 24 Feb 2021 07:40 |
| Last Modified: | 24 Feb 2021 07:40 |
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