Nature is the principal source for proposing new optimization methods such as genetic algorithms (GA) and simulated annealing (SA) methods. All traditional evolutionary algorithms are heuristic population-based search procedures that incorporate random variation and selection. The main contribution of this study is that it proposes a novel optimization method that relies on one of the theories ...

Development of Electrical Vehicles (EVs) has been created many challenges and also advantages for grids. One of the most important subjects is capability of which as energy storage device. In this paper, role of EVs has been studied as useful element in microgrids as energy storage device to reduce the on-peak load in microgrid and decrease the total cost of microgrid. For this goal the problem...

Nowadays, the most generated electrical energy is consumed by three-phase induction motors. Thus, in order to carry out preventive measurements and maintenances and eventually employing high-efficiency motors, the efficiency evaluation of induction motors is vital. In this paper, a novel and efficient method based on Improved Big Bang-Big Crunch (I-BB-BC) Algorithm is presented for efficiency e...

Metal oxide surge arrester accurate modeling and its parameter identification are very important for insulation coordination studies, arrester allocation and system reliability. Since quality and reliability of lightning performance studies can be improved with the more efficient representation of the arresters´ dynamic behavior. In this paper, Big Bang – Big Crunch and Hybrid Big Bang – Big Cr...

Over the past decades, several techniques have been employed to improve the applicability of the metaheuristic optimization methods. One of the solutions for improving the capability of metaheuristic methods is the hybrid of algorithms. This study proposes a new optimization algorithm called HPBA which is based on the hybrid of two optimization algorithms; Big Bang-Big Crunch (BB-BC) inspired b...

This paper empirically evaluates four meta-heuristic search techniques namely particle swarm optimization, artificial bee colony algorithm, Genetic Algorithm and Big Bang Big Crunch Algorithm for automatic test data generation for procedure oriented programs using structural symbolic testing method. Test data is generated for each feasible path of the programs. Experiments on ten benchmark prog...

In the present study the efficiency of Big Bang-Big Crunch (BB-BC) algorithm is investigated in discrete structural design optimization. It is shown that a standard version of the BB-BC algorithm is sometimes unable to produce reasonable solutions to problems from discrete structural design optimization. Two reformulations of the algorithm, which are referred to as modified BB-BC (MBB-BC) and e...

This paper presents an efficient optimization procedure to find the optimal shapes of double curvature  arch  dams  considering  fluid–structure  interaction  subject  to  earthquake  loading. The optimization is carried out using a combination of the magnetic charged system search, big bang-big crunch algorithm and artificial neural network methods. Performing the finite element  analysis  dur...

The basic property of an antenna is to transmit and receive energy signal in one/all direction. This fundamental property is directivity. This paper employs big bang crunch algorithm optimization method for the synthesis of broadside linear antenna array. In this paper optimum value of current of each antenna element is determined which produces radiation pattern with minimum side lobe level. O...