Abstract—Recently researchers have great interest in using multi-core processors for applications requiring intensive parallel computing. In this paper, an approach for the implementation of hybrid parallel Gravitational Search Algorithm (GSA) and Nelder-Mead (NM) algorithm using open MultiProcessing (OPEN-MP) on multi-core processors is proposed for beam-forming applications. The proposed para...

In this study, a multiobjective environmental economic power dispatch problem has been converted into a single-objective optimization problem using the weighted sum method. For the solution of the converted problem, the gravitational search algorithm (GSA), which is one of the latest algorithms, has been used. In order to increase the performance of the GSA, opposite positioning quality has bee...

In this paper, an efficient approach is proposed to address the problem of target tracking in wireless sensor network (WSN). The problem being tackled here uses adaptive dynamic clustering scheme for tracking the target. It is a specific problem in object tracking. The proposed adaptive dynamic clustering target tracking scheme uses three steps for target tracking. The first step deals with the...

this article proposes a new algorithm for finding a good approximate set of non-dominated solutions for solving generalized traveling salesman problem. Random gravitational emulation search algorithm (RGES (is presented for solving traveling salesman problem. The algorithm based on random search concepts, and uses two parameters, speed and force of gravity in physics. The proposed algorithm is ...

In this article, a newly hybrid nature-inspired approach (MGBPSO-GSA) is developed with a combination of Mean Gbest Particle Swarm Optimization (MGBPSO) and Gravitational Search Algorithm (GSA). The basic inspiration is to integrate the ability of exploitation in MGBPSO with the ability of exploration in GSA to synthesize the strength of both approaches. As a result, the presented approach has ...

This paper presents a Gravitational Search Algorithm (GSA) to tune optimal rule-base of a Fuzzy Power System Stabilizer (FPSS) which leads to damp low frequency oscillation following disturbances in power systems. Usually in a rule based fuzzy control system, selection of suitable rules is more difficult, because of its complexity. Thus, to reduce the design effort and find a better fuzzy syste...

In this paper a new hybrid design methodology for stable adaptive fuzzy controllers for a non-linear system is proposed. The proposed design strategy utilizes the gravitational search algorithm (GSA) based heuristic global search technique and Lyapunov theory based local adaptation. The objective is to design a self-adaptive fuzzy controller, optimizing the free parameters of the fuzzy controll...

This paper presents backstepping controller design for tracking purpose of nonlinear system. Since the performance of the designed controller depends on the value of control parameters, gravitational search algorithm (GSA) and particle swarm optimization (PSO) techniques are used to optimise these parameters in order to achieve a predefined system performance. The performance is evaluated based...

Evolutionary computation tools are able to process real valued numerical sets in order to extract suboptimal solution of designed problem. Data clustering algorithms have been intensively used for image segmentation in remote sensing applications. Despite of wide usage of evolutionary algorithms on data clustering, their clustering performances have been scarcely studied by using clustering val...

Early detection of breast cancer cells can be predicted through a precise feature extraction technique that produce efficient features. The application Gabor filters, gray level co-occurrence matrices (GLCM) and other textural techniques have proven to achieve promising results but were often characterized by high false-positive rate (FPR) false-negative (FNR) with computational complexities. T...