rainfall-runoff modeling is most important component in the water resource management of river basins. the successful application of a conceptual rainfall-runoff model depends on how well it is calibrated. the degree of difficulty in solving the global optimization method is generally dependent on the dimensionality of the model and certain of the characteristics of object function. the purpose...

Recent day power system networks are having high risks of voltage instability problems and several network blackouts have been reported. This phenomenon tends to occur from lack of reactive power supports under heavily stressed operating conditions caused by increased load demand and the fast developing deregulation of power systems across the world. This paper proposes an application of Shuffl...

Stochastic search algorithms that take their inspiration from nature are gaining a great attention of many researchers to solve high dimension and non – linear complex optimization problems for which traditional methods fails. Shuffled frog – leaping algorithm (SFLA) is recent addition to the family of stochastic search algorithms that take its inspiration from the foraging process of frogs. SF...

There are various automatic programming models inspired by evolutionary computation techniques. Due to the importance of devising an automatic mechanism to explore the complicated search space of mathematical problems where numerical methods fails, evolutionary computations are widely studied and applied to solve real world problems. One of the famous algorithm in optimization problem is shuffl...

This paper proposes a study of quality of service (QoS) in cognitive radio networks. This study is based on a stochastic optimization method called shuffled frog leaping algorithm (SFLA). The interest of the SFLA algorithm is to guarantee a better solution in a multi-carrier context in order to satisfy the requirements of the secondary user (SU).

Abstract The differential evolution (DE) algorithm is an efficient random search based on swarm intelligence for solving optimization problems. It has the advantages of easy implementation, fast convergence, strong ability and good robustness. However, performance DE very sensitive to design different operators setting control parameters. To solve these key problems, this paper proposes improve...