Due to its robust search mechanism, Gravitational algorithm (GSA) has achieved a lot of popularity in different research communities. However, stagnation reduces searchability towards global optima for rigid and complex multi-modal problems. This paper proposes GSA variant that incorporates chaos-embedded opposition-based learning into the basic stagnation-free search. Additionally, sine-cosine...

In this paper we are presenting a modification of the Gravitational Search Algorithm (GSA) using type-2 fuzzy logic to dynamically change the alpha parameter and provide a different gravitation and acceleration values to each agent in order to improve its performance. We test this approach with benchmark mathematical functions. Simulation results show the advantages of the proposed approach.

Ti6Al4V alloy is widely used in aerospace and medical applications. It classified as a difficult to machine material due its low thermal conductivity high chemical reactivity. In this study, hybrid intelligent models have been developed predict surface roughness when end milling with Physical Vapor Deposition PVD coated tool under dry cutting conditions. Back propagation neural network (BPNN) h...

A hybrid meta-heuristic optimization method is introduced to efficiently find the optimal shape of concrete gravity dams including dam-water-foundation rock interaction subjected to earthquake loading. The hybrid meta-heuristic optimization method is based on a hybrid of gravitational search algorithm (GSA) and particle swarm optimization (PSO), which is called GSA-PSO. The operation of GSA-PSO...

The Gravitational Search Algorithm (GSA) is a novel optimization method based on the law of gravity and mass interactions. It has good ability to search for the global optimum, but its searching speed is really slow in the last iterations. So the hybridization of Particle Swarm Optimization (PSO) and GSA can resolve the aforementioned problem. In this paper, a modified PSO, which the movement o...

The development of electricity networks towards the future smart grids is naturally accompanied by increasing complexity of technical, economic and environmental problems. The new challenges require the development of new techniques and optimization methods, including specific approaches to multiobjective optimization problems. This paper focuses on basic and multiobjective optimization methods...

The present paper proposes a novel feature selection scheme for face recognition problems, employing a new modified version of the gravitational search algorithm, a recently proposed metaheuristic optimization algorithm. The feature selection scheme, which reduces the dimensionality of the set of extracted features by choosing the features with high discriminative power, has been employed in co...

This paper presents aspects concerning the implementation of an adaptive Gravitational Search Algorithm (GSA) in the optimal tuning of fuzzy controllers. Takagi-Sugeno-Kang proportionalintegral fuzzy controllers (TSK PI-FCs) are designed and tuned for a class of nonlinear servo systems. The adaptive GSA is based on five stages to solve the optimization problems with objective functions which de...

This paper represents the Gravitational Search Algorithm (GSA) that can be used to determine the optimal location and rating of Thyristor controlled Series Capacitor (TCSC). TCSC is equipment used to regulate and improve power flow in power system. The method used in this study was GSA. TCSC were the implemented on 500kV Java-Bali Power System. Loadflow results before optimization using Newton ...

In this paper, a novel approach called GSA-DenseNet121-COVID-19 based on hybrid convolutional neural network (CNN) architecture is proposed using an optimization algorithm. The CNN that was used DenseNet121 and the algorithm gravitational search (GSA). GSA adapted to determine best values for hyperparameters of architecture, achieve high level accuracy in diagnosing COVID-19 disease through che...