Chaos-based Vortex Search algorithm for solving inverse kinematics problem of serial robot manipulators with offset wrist

Toz, Metin

doi:10.1016/j.asoc.2020.106074

Cited by 34 publications

(21 citation statements)

References 34 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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“…For the development of the chaos-based VS algorithm proposed in the study, 10 logistic maps were used. Fifty benchmark functions were used to measure the performance of CVS algorithm and to make comparisons between algorithms [49].…”

Section: Rosenbrockmentioning

confidence: 99%

Chaos in metaheuristic based artificial intelligence algorithms: a short review

Atali¹,

Pehlivan²,

Gürevin³

et al. 2021

Turkish Journal of Electrical Engineering and Computer Sciences

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Metaheuristic based artificial intelligence algorithms are commonly used in the solution of optimization problems. Another area -besides engineering systems-where chaos theory is widely employed is optimization problems.Being applied easily and not trapping in local optima, chaos-based search algorithms have attracted great attention. For example, it has been reported that when random number sequences generated from different chaotic systems are replaced with parameter values in bioinspired and swarm intelligence algorithms, an increase in the performance of metaheuristic algorithms is observed. Many scientific studies on developing hybrid algorithms in which metaheuristic algorithms and chaos theory are used together are already in process.In this article, scientific studies that cover the most popular metaheuristic algorithms in the literature in recent years and chaos theory subtopics together are examined. Great number of studies on metaheuristic algorithms and chaos issues exist in scientific literature. This article, hitherto, had to be limited to the most common meta-heuristic algorithms. In chaos-based metaheuristic algorithms, some advantages such as easy implementation, short application time and search acceleration have been addressed.This article is believed to contribute to two groups of researchers: The first group includes researchers already using meta-heuristic algorithms and who will come to understand that they can even improve their current techniques with chaos theory subarguments. The second group includes those who currently utilize chaotic analysis and methods in areas like nonlinear prediction modeling design and who will realize that they can make their existing methods even smarter with metaheuristic methods. Some metaheuristic algorithms use chaotic maps to solve problems such as trapping in local optimal solutions and premature convergence. In this study, such algorithms are examined through the benchmark functions they use. In addition, PSO, FA, ABC, WO algorithms are compared in terms of their common features, and algorithms with the best success rate are presented.

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“…Ali, Qyyum, Qadeer ve Lee karışık soğutucu doğal gaz sıvılaştırma işlemi için enerji optimizasyonunda VS algoritmasını kullanmışlardır [23]. Toz, seri robot manipülatörlerin ters kinematik problemini çözmek için VS algoritmasını kullanmıştır [24]. Fathy, Elaziz ve Alharbi proton değişim membranı yakıt hücresinin optimal parametrelerini tespit etmek için VS algoritmasını kullanmışlardır [25].…”

Section: Vs Algoritması Ile Yapılan Diğer çAlışmalarunclassified

A new model based on vortex search algorithm for estimating energy demand of Turkey

Özkış¹

2020

Pamukkale J Eng Sci

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Bu çalışmada, Türkiye'nin enerji talebini tahmin etmek amacıyla Girdap Arama (Vortex Search, VS) algoritması temelli yeni bir doğrusal regresyon modeli geliştirilmiştir. Modelde Türkiye'deki gayri safi yurtiçi hâsıla (GSYİH), nüfus, ithalat ve ihracat verileri girdi parametrelerini; ortaya çıkan enerji talebi ise tahmin edilecek çıktıyı ifade etmektedir. 1979-2005 ve 1979-2011 yılları arasındaki veriler kullanılarak geliştirilen iki farklı tahmin modeli literatürdeki benzer çalışmalarla karşılaştırılmıştır. Elde edilen sonuçlar, geliştirilen VS modellerinin karşılaştırma yapılan modellerden daha başarılı veya rekabetçi sonuçlar elde ettiğini göstermiştir. Çalışmada son olarak, Türkiye'nin 2030 yılına kadar talep edeceği enerji miktarı, VS ve diğer modeller ile 3 farklı senaryo üzerinden tahmin edilmiştir. In this study, a new linear regression model based on Vortex Search (VS) algorithm was developed for estimating Turkey's energy demand. In this model, Turkey's gross domestic product (GDP), population, import and export data refer to input parameters; resulting energy demand refers to output to be estimated. Two different estimation models developed by using data between 1979-2005 and 1979-2011 were compared with similar studies in the literature. The results showed that the developed VS models obtained more successful or competitive results than the compared models. Finally in this study, the amount of energy that will be demanded in Turkey until 2030 was projected with VS and other models according to 3 different scenarios.

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Chaos-based Vortex Search algorithm for solving inverse kinematics problem of serial robot manipulators with offset wrist

Cited by 34 publications

References 34 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

Chaos in metaheuristic based artificial intelligence algorithms: a short review

A new model based on vortex search algorithm for estimating energy demand of Turkey

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