SVSA: a Semi-Vortex Search Algorithm for solving optimization problems

Razavi, Seyedeh Fatemeh; Sajedi, Hedieh

doi:10.1007/s41060-018-0154-6

Cited by 6 publications

(1 citation statement)

References 18 publications

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“…Recently, a promissory metaheuristic optimization technique known as the vortex search algorithm (VSA) has emerged to solve complex nonlinear non-convex optimization problems in the continuous domain. Some of these approaches are optimal power flow in AC and DC networks [31][32][33], respectively; optimal selection of analog active filter components [34]; application of the VSA for numerical optimization [35][36][37]; optimal design of offshore and onshore natural gas liquefaction processes [38]; and optimal solution of the inverse kinematics problem of serial robot manipulators with offset wrist [39]; among others. It is worth mentioning that the main advantages of using the VSA in nonlinear optimization problems are the following: (i) its low standard deviation since it works with Gaussian distribution functions for exploring the solution space; (ii) its correct balance between exploration and exploitation of the solution space during the iteration procedure since the optimization search is guided by a variable radius applied on the Gaussian hypersphere that contains all the potential solutions of the current iteration; and (iii) its easy implementation for any programming language via sequential programming.…”

Section: Introductionmentioning

confidence: 99%

Optimal Selection and Location of Fixed-Step Capacitor Banks in Distribution Networks Using a Discrete Version of the Vortex Search Algorithm

et al. 2020

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This paper deals with the problem of the optimal selection of capacitor banks in electrical AC distribution systems for minimizing the costs of energy losses during a year of operation through a discrete version of the vortex search algorithm (DVSA). This algorithm works with a hypersphere with a variable radius defined by an exponential function where a Gaussian distribution is used to generate a set of candidate solutions uniformly distributed around the center of this hypersphere. This center corresponds to the best solution obtained at the iteration t, which is initialized at the center of the solution space at the iterative search beginning. The main advantage of combining the exponential function with the Gaussian distribution is the correct balance between the exploration and exploitation of the solution space, which allows reaching the global optimal solution of the optimization problem with a low standard deviation, i.e., guaranteeing repeatability at each simulation. Two classical distribution networks composed of 33 and 69 nodes were used to validate the proposed DVSA algorithm. They demonstrated that the DVSA improves numerical reports found in specialized literature regarding the optimal selection and location of fixed-step capacitor banks with a low computational burden. All the simulations were carried out in MATLAB software.

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Section: Introductionmentioning

confidence: 99%

Optimal Selection and Location of Fixed-Step Capacitor Banks in Distribution Networks Using a Discrete Version of the Vortex Search Algorithm

et al. 2020

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A parallel classification framework for protein fold recognition

2020

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Estimating the Parameters of a Three-Phase Induction Motor using the Vortex Search Algorithm

Montano,

Garzón,

Herrera-Jaramillo

et al. 2023

Iran J Sci Technol Trans Electr Eng

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In this paper, we present a new optimization method to estimate the parameters and torques of an induction motor (IM). The proposed method is known as the Vortex Search Algorithm (VSA), whose performance is based on the behavior of the vortices created by stirred fluids. This algorithm was compared with other four optimization methods reported in the specialized literature (grasshopper optimization algorithm, particle swarm optimization, salp swarm algorithm and sine cosine algorithm), and its solution quality, precision, and robustness were validated using two test motors. During the tests, we analyzed the minimum error between the estimated values and the values provided by the manufacturer, as well as the global error of each method and their required processing time. The results show that the VSA is an excellent alternative to estimate the parameters of an IM, as it exhibited the best performance when compared to the other optimization methods.

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SVSA: a Semi-Vortex Search Algorithm for solving optimization problems

Cited by 6 publications

References 18 publications

Optimal Selection and Location of Fixed-Step Capacitor Banks in Distribution Networks Using a Discrete Version of the Vortex Search Algorithm

Optimal Selection and Location of Fixed-Step Capacitor Banks in Distribution Networks Using a Discrete Version of the Vortex Search Algorithm

A parallel classification framework for protein fold recognition

Estimating the Parameters of a Three-Phase Induction Motor using the Vortex Search Algorithm

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