the gravitational search algorithm (gsa) is a novel optimization methodbased on the law of gravity and mass interactions. it has good ability to search forthe global optimum, but its searching speed is really slow in the last iterations. sothe hybridization of particle swarm optimization (pso) and gsa can resolve theaforementioned problem. in this paper, a modified pso, which the movement ofpar...

Due to the fact that the error surface of adaptive infinite impulse response (IIR) systems is generally nonlinear and multimodal, the conventional derivative based techniques fail when used in adaptive identification of such systems. In this case, global optimization techniques are required in order to avoid the local minima. Harmony search (HS), a musical inspired metaheuristic, is a recently ...

Data clustering is an ideal way of working with a huge amount of data and looking for a structure in the dataset. In other words, clustering is the classification of the same data; the similarity among the data in a cluster is maximum and the similarity among the data in the different clusters is minimal. The innovation of this paper is a clustering method based on the Crow Search Algorithm (CS...

In recent years, various heuristic optimization methods have been developed. Many of these methods are inspired by swarm behaviors in nature. In this paper, a new optimization algorithm based on the law of gravity and mass interactions is introduced. In the proposed algorithm, the searcher agents are a collection of masses which interact with each other based on the Newtonian gravity and the la...

plug-in hybrid electric vehicles (phev) technology shows great interest in the recent scientificliteratures. vehicle-to-grid (v2g) is a interconnection of energy storage of phevs and grid. byimplementation of v2g dependencies of the power system on small expensive conventional units canbe reduced, resulting in reduced operational cost. this paper represents an intelligent unitcommitment (uc) wi...

This article introduces two swarm intelligent algorithms, a group search optimizer (GSO) and an artificial fish swarm algorithm (AFSA). A single intelligent algorithm always has both merits in its specific formulation and deficiencies due to its inherent limitations. Therefore, we propose a mixture of these algorithms to create a new hybrid optimization algorithm known as the group search-artif...

Abstract The multi-strategy improved sparrow search algorithm (MSISSA) is proposed to address the problems that (SSA) not rich in population diversity, and prone fall into local optimality poor accuracy solving multi-dimensional functions. Firstly, Cat mapping used initialize SSA population. Secondly, an elite reverse learning strategy introduced increase diversity improve global ability of SSA...