Evolutionary algorithms are the choice of many researchers for optimizing machining parameters. Even though evolutionary algorithms are commonly used for solving constrained optimization problems, however in practice sometimes they deliver only insignificant performance. The difficulty with evolutionary algorithms is that they start with random initial population and all its populations become ...

Firefly algorithm (FA) is a novel population-based stochastic optimization algorithm and has been shown to yield good performance for solving varieties of optimization problems. Meanwhile, it sustains premature convergence because it is easily to fall into the local optima which may generate a low accuracy of solution or even fail. To overcome this defect, a nonlinear time-varying step strategy...

In order to minimize the total active power loss and improve the voltage profile of the power system, several solutions have been proposed, including the integration of Distributed Generation (DG) in the radial distribution network. The location and size of DG are important, because a wrong choice has a negative impact on the system behavior. Several researchers have used many methods for solvi...

The Economic Load Dispatch (ELD) problems in power generation systems are to reduce the fuel cost by reducing the total cost for the generation of electric power. This paper presents an efficient Modified Firefly Algorithm (MFA), for solving ELD Problem. The main objective of the problems is to minimize the total fuel cost of the generating units having quadratic cost functions subjected to lim...

Firefly algorithm (FA) is one of the newly developed nature inspired optimisation algorithm, inspired by the flashing behaviour of fireflies that a firefly tends to be attracted towards other fireflies with higher brightness. Thus FA has two advantages: local attractions and automatic regrouping. Based on these good properties, a novel image watermarking method based on FA in discrete wavelet t...

A hybrid metaheuristic approach by hybridizing harmony search (HS) and firefly algorithm (FA), namely, HS/FA, is proposed to solve function optimization. In HS/FA, the exploration of HS and the exploitation of FA are fully exerted, so HS/FA has a faster convergence speed than HS and FA. Also, top fireflies scheme is introduced to reduce running time, and HS is utilized to mutate between firefli...

The firefly algorithm is a member of the swarm intelligence family of algorithms, which have recently showed impressive performances in solving optimization problems. The fire-fly algorithm, in particular, is applied for solving continuous and discrete optimization problems. In order to tackle different optimization problems efficiently and fast, many variants of the firefly algorithm have rece...

Electricity load forecasting is an important issue that is widely explored and examined in power systems operation literature and commercial transactions in electricity markets literature as well. Among the existing forecasting models, support vector regression (SVR) has gained much attention. Considering the performance of SVR highly depends on its parameters; this study proposed a firefly alg...

The study of inverse problems applied to radiative transfer has been the subject of numerous studies aiming many applications ranging from medicine to industry formulation for the parameter estimation inverse problems in radiative heat transfer is minimization of an objective function associated with the problem being analyzed. usually inspired by nature behaviors, have been shown effective in ...

For the past one decade, biclustering has become popular data mining technique not only in the field of biological data analysis but also in other applications like text mining, market data analysis with high-dimensional two-way datasets. Biclustering clusters both rows and columns of a dataset simultaneously, as opposed to traditional clustering which clusters either rows or columns of a datas...