It’s of great significance for wind power integration into grid to forecast wind power. Based on forecasting wind power by BP neural network, the article introduces global optimization algorithm, Imperialist Competitive Algorithm (ICA) to provide optimized initial weights of BP neural network. Thus, it can overcome the entrapment in local optical optimum of BP neural network. Compared with BP n...

One of the most important obstacles in the deployment of the clean technologies such as photovoltaic modules in the distribution system is their indefinite future in the coming years after the installation due to their intermittent nature in power generation because of the dependency to solar radiance profile. The authors in this study aim to analyze the economic, technical and environmental ef...

This paper proposes an Imperialist Competitive Algorithm (ICA) for optimal multiple distributed generations (DGs) placement and sizing in a distribution system. The objective is to minimize the total real power losses and improve the voltage profile within real and reactive power generation and voltage limits. Three types of DG are considered and the ICA is used to find the better sizes and loc...

In this work a strong framework is presented for solving the constrained nonlinear optimization problem that is a relatively complicated problem. These problems arise in a diverse range of sciences. There are a number of different approaches have been proposed. In this work, we employ the imperialist competitive algorithm (ICA) for solving constrained nonlinear optimization problems. Some well-...

The spatial distribution of petrophysical properties within the reservoirs is one of the most important factors in reservoir characterization. Flow units are the continuous body over a specific reservoir volume within which the geological and petrophysical properties are the same. Accordingly, an accurate prediction of flow units is a major task to achieve a reliable petrophysical description o...

Recently, the particle swarm algorithm (PSO) has demonstrated its effectiveness in solving multi-objective optimization problems. However, performance of most existing algorithms depends largely on global or individual best particles. Moreover, due to rapid convergence PSO single objective problems, is prone poorly distributed indicators when dealing with To solve above we propose a competitive...

This paper deal with the problem of no-wait hybrid flow shop which sequence dependent setup times, ready time and machine availability constraint. Minimizing the mean tardiness is considered as the objective to develop the optimal scheduling algorithm. To do so, an efficient hybrid imperialist competitive algorithm (HICA) is proposed to tackle this problem. Our proposed algorithm is compared to...

This paper deal with the problem of no-wait hybrid flow shop which sequence dependent setup times, ready time and machine availability constraint. Minimizing the mean tardiness is considered as the objective to develop the optimal scheduling algorithm. To do so, an efficient hybrid imperialist competitive algorithm (HICA) is proposed to tackle this problem. Our proposed algorithm is compared to...