Evaluation of Fast Evolutionary Programming, Firefly Algorithm and Mutate-Cuckoo Search Algorithm In Single-Objective Optimization

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.