Optimization Algorithms - Methods and Applications 2016
DOI: 10.5772/62472
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A Review and Comparative Study of Firefly Algorithm and its Modified Versions

Abstract: Firefly algorithm is one of the well-known swarm-based algorithms which gained popularity within a short time and has different applications. It is easy to understand and implement. The existing studies show that it is prone to premature convergence and suggest the relaxation of having constant parameters. To boost the performance of the algorithm, different modifications are done by several researchers. In this chapter, we will review these modifications done on the standard firefly algorithm based on paramet… Show more

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Cited by 40 publications
(35 citation statements)
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“…% of MWCNTs were added in the PVP polymeric matrices prior to the electrospinning process. MWCNTs have excellent thermal (1500–3000 W/m.°K) and electrical (10 4 S/cm) conductivity values; however, most of the polymers are thermally and electrically insulators [ 19 , 22 , 27 ]. The experimental results indicated that the addition of MWCNTs to the polymer matrices showed a significant increase in the thermal conductivity values of PVP nanocomposite fibers.…”
Section: Resultsmentioning
confidence: 99%
“…% of MWCNTs were added in the PVP polymeric matrices prior to the electrospinning process. MWCNTs have excellent thermal (1500–3000 W/m.°K) and electrical (10 4 S/cm) conductivity values; however, most of the polymers are thermally and electrically insulators [ 19 , 22 , 27 ]. The experimental results indicated that the addition of MWCNTs to the polymer matrices showed a significant increase in the thermal conductivity values of PVP nanocomposite fibers.…”
Section: Resultsmentioning
confidence: 99%
“…These updates of the location of reies continue with iteration until a termination criterion is met. The termination criterion can be maximum number of iterations, a tolerance from the optimum value if it is known or no improvement is achieved in consecutive iterations [178]. It was shown that the Firey Algorithm is potentially more powerful than other existing algorithms such as particle swarm optimization [352] but at the same time it was criticized as diering from the well-established PSO only in a negligible way [219].…”
Section: Swarm Intelligencementioning
confidence: 99%
“…The firefly position is updated based on its attractiveness, controlled by the brightness level. However, the FA is a memory-less algorithm (47). Therefore, the information is not conveyed from one iteration to other iteration.…”
Section: Memory In Swarm-based Metaheuristicsmentioning
confidence: 99%
“…This means that the firefly will not be able to attract other fireflies in successive iterations, because the position of this firefly will also be changed and its information lost (48). Modified versions of the FA were proposed by integrating a memory that records the fireflies with the best solution to be used in the next generation (49) and best solution found so far (47).…”
Section: Memory In Swarm-based Metaheuristicsmentioning
confidence: 99%