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Статті в журналах з теми "GRAVITATIONAL SEARCH ALGORITHM (GSA)"

Автор: Grafiati

Опубліковано: 26 жовтня 2023

Оновлено: 25 липня 2025

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1

Lenin, K. "A NOVEL HYBRIDIZED ALGORITHM FOR REDUCTION OF REAL POWER LOSS." International Journal of Research -GRANTHAALAYAH 5, no. 11 (2017): 316–24. http://dx.doi.org/10.29121/granthaalayah.v5.i11.2017.2358.

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Анотація:

This paper proposes Hybridization of Gravitational Search algorithm with Simulated Annealing algorithm (HGS) for solving optimal reactive power problem. Individual position modernize strategy in Gravitational Search Algorithm (GSA) may cause damage to the individual position and also the local search capability of GSA is very weak. The new HGS algorithm introduced the idea of Simulated Annealing (SA) into Gravitational Search Algorithm (GSA), which took the Metropolis-principle-based individual position modernize strategy to perk up the particle moves, & after the operation of gravitation,

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2

Dr.K.Lenin. "A NOVEL HYBRIDIZED ALGORITHM FOR REDUCTION OF REAL POWER LOSS." International Journal of Research - Granthaalayah 5, no. 11 (2017): 304–12. https://doi.org/10.5281/zenodo.1098401.

Повний текст джерела

Анотація:

This paper proposes Hybridization of Gravitational Search algorithm with Simulated Annealing algorithm (HGS) for solving optimal reactive power problem. Individual position modernize strategy in Gravitational Search Algorithm (GSA) may cause damage to the individual position and also the local search capability of GSA is very weak. The new HGS algorithm introduced the idea of Simulated Annealing (SA) into Gravitational Search Algorithm (GSA), which took the Metropolis-principle-based individual position modernize strategy to perk up the particle moves, & after the operation of gravitation,

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3

Lenin, K. "MINIMIZATION OF REAL POWER LOSS BY ENHANCED GRAVITATIONAL SEARCH ALGORITHM." International Journal of Research -GRANTHAALAYAH 5, no. 7 (2017): 623–30. http://dx.doi.org/10.29121/granthaalayah.v5.i7.2017.2171.

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Анотація:

In this paper, Enhanced Gravitational Search (EGS) algorithm is proposed to solve the reactive power problem. Gravitational search algorithm (GSA) results are improved by using artificial bee colony algorithm (ABC). In GSA, solutions are fascinated towards each other by applying gravitational forces, which depending on the masses assigned to the solutions, to each other. The heaviest mass will move slower than other masses and pull others. Due to nature of gravitation, GSA may pass global minimum if some solutions stuck to local minimum. ABC updates the positions of the best solutions that hav

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4

Dr.K.Lenin. "MINIMIZATION OF REAL POWER LOSS BY ENHANCED GRAVITATIONAL SEARCH ALGORITHM." International Journal of Research - Granthaalayah 5, no. 7 (2017): 523–30. https://doi.org/10.5281/zenodo.844717.

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Анотація:

In this paper, Enhanced Gravitational Search (EGS) algorithm is proposed to solve the reactive power problem. Gravitational search algorithm (GSA) results are improved by using artificial bee colony algorithm (ABC). In GSA, solutions are fascinated towards each other by applying gravitational forces, which depending on the masses assigned to the solutions, to each other. The heaviest mass will move slower than other masses and pull others. Due to nature of gravitation, GSA may pass global minimum if some solutions stuck to local minimum. ABC updates the positions of the best solutions that hav

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5

Rashedi, Esmat, Hossein Nezamabadi-pour, and Saeid Saryazdi. "GSA: A Gravitational Search Algorithm." Information Sciences 179, no. 13 (2009): 2232–48. http://dx.doi.org/10.1016/j.ins.2009.03.004.

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6

Shankar, Rajendran, Narayanan Ganesh, Robert Čep, Rama Chandran Narayanan, Subham Pal, and Kanak Kalita. "Hybridized Particle Swarm—Gravitational Search Algorithm for Process Optimization." Processes 10, no. 3 (2022): 616. http://dx.doi.org/10.3390/pr10030616.

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Анотація:

The optimization of industrial processes is a critical task for leveraging profitability and sustainability. To ensure the selection of optimum process parameter levels in any industrial process, numerous metaheuristic algorithms have been proposed so far. However, many algorithms are either computationally too expensive or become trapped in the pit of local optima. To counter these challenges, in this paper, a hybrid metaheuristic called PSO-GSA is employed that works by combining the iterative improvement capability of particle swarm optimization (PSO) and gravitational search algorithm (GSA

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7

Kamaruzaman, Anis Farhan, Azlan Mohd Zain, Suhaila Mohamed Yusuf, and Noordin Mohd Yusof. "Gravitational Search Algorithm for Engineering: A Review." Applied Mechanics and Materials 815 (November 2015): 417–20. http://dx.doi.org/10.4028/www.scientific.net/amm.815.417.

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Анотація:

This paper presents a review on gravitational search algorithm (GSA). Nowadays, GSA has been used in various engineering studies such as production cost, production time, power consumption and emission. The GSA also mainly focuses to solve the problem related to optimization, modeling, scheduling and clustering. This paper also highlights the current researches using improved GSA.

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8

Kherabadi, Hossein Azadi, Sepehr Ebrahimi Mood, and Mohammad Masoud Javidi. "Mutation: A New Operator in Gravitational Search Algorithm Using Fuzzy Controller." Cybernetics and Information Technologies 17, no. 1 (2017): 72–86. http://dx.doi.org/10.1515/cait-2017-0006.

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Анотація:

Abstract Gravitational Search Algorithm (GSA) isanovel meta-heuristic algorithm. Despite it has high exploring ability, this algorithm faces premature convergence and gets trapped in some problems, therefore it has difficulty in finding the optimum solution for problems, which is considered as one of the disadvantages of GSA. In this paper, this problem has been solved through definingamutation function which uses fuzzy controller to control mutation parameter. The proposed method has been evaluated on standard benchmark functions including unimodal and multimodal functions; the obtained resul

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9

Siddique, Nazmul, and Hojjat Adeli. "Gravitational Search Algorithm and Its Variants." International Journal of Pattern Recognition and Artificial Intelligence 30, no. 08 (2016): 1639001. http://dx.doi.org/10.1142/s0218001416390018.

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Анотація:

Gravitational search algorithm (GSA) is a nature-inspired conceptual framework with roots in gravitational kinematics, a branch of physics that models the motion of masses moving under the influence of gravity. In GSA, a collection of objects interacts with each other under the Newtonian gravity and the laws of motion. The performances of objects are measured by masses. All these objects attract each other by the gravity force, while this force causes a global movement of all objects toward the objects with heavier masses. The position of the object corresponds to a solution of the problem. Th

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10

Ali, Ahmed F., and Mohamed A. Tawhid. "Direct Gravitational Search Algorithm for Global Optimisation Problems." East Asian Journal on Applied Mathematics 6, no. 3 (2016): 290–313. http://dx.doi.org/10.4208/eajam.030915.210416a.

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AbstractA gravitational search algorithm (GSA) is a meta-heuristic development that is modelled on the Newtonian law of gravity and mass interaction. Here we propose a new hybrid algorithm called the Direct Gravitational Search Algorithm (DGSA), which combines a GSA that can perform a wide exploration and deep exploitation with the Nelder-Mead method, as a promising direct method capable of an intensification search. The main drawback of a meta-heuristic algorithm is slow convergence, but in our DGSA the standard GSA is run for a number of iterations before the best solution obtained is passed

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11

SIDDIQUE, Nazmul, and Hojjat ADELI. "APPLICATIONS OF GRAVITATIONAL SEARCH ALGORITHM IN ENGINEERING." JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 22, no. 8 (2016): 981–90. http://dx.doi.org/10.3846/13923730.2016.1232306.

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Анотація:

Gravitational search algorithm (GSA) is a nature-inspired conceptual framework with roots in gravitational kinematics, a branch of physics that models the motion of masses moving under the influence of gravity. In a recent article the authors reviewed the principles of GSA. This article presents a review of applications of GSA in engineering including combinatorial optimization problems, economic load dispatch problem, economic and emission dispatch problem, optimal power flow problem, optimal reactive power dispatch problem, energy management system problem, clustering and classification prob

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12

Santra, D., A. Mukherjee, K. Sarker, and S. Mondal. "Hybrid Genetic Algorithm-Gravitational Search Algorithm to Optimize Multi-Scale Load Dispatch." International Journal of Applied Metaheuristic Computing 12, no. 3 (2021): 28–53. http://dx.doi.org/10.4018/ijamc.2021070102.

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Genetic algorithm (GA) and gravitational search algorithm (GSA) both have successfully been applied in solving ELD problems of electrical power generation systems. Each of these algorithms has their limitations and advantage. GA's global search and GSA's local search capability are their strong points while long execution period of GA and premature of convergence of GSA hinders the possibility of optimum result when applied separately in ELD problems. To mitigate these limitations, experiment is done for the first time by combining GA and GSA suitably and applying the hybrid in non-linear ELD

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13

Koay, Ying-Ying, Jian-Ding Tan, Chin-Wai Lim, Siaw-Paw Koh, Sieh-Kiong Tiong, and Kharudin Ali. "An adaptive gravitational search algorithm for global optimization." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 2 (2019): 724. http://dx.doi.org/10.11591/ijeecs.v16.i2.pp724-729.

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Анотація:

<span>Optimization algorithm has become one of the most studied branches in the fields of artificial intelligent and soft computing. Many powerful optimization algorithms with global search ability can be found in the literature. Gravitational Search Algorithm (GSA) is one of the relatively new population-based optimization algorithms. In this research, an Adaptive Gravitational Search Algorithm (AGSA) is proposed. The AGSA is enhanced with an adaptive search step local search mechanism. The adaptive search step begins the search with relatively larger step size, and automatically fine-t

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14

Can, Umit, and Bilal Alatas. "Automatic Mining of Quantitative Association Rules with Gravitational Search Algorithm." International Journal of Software Engineering and Knowledge Engineering 27, no. 03 (2017): 343–72. http://dx.doi.org/10.1142/s0218194017500127.

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Анотація:

The classical optimization algorithms are not efficient in solving complex search and optimization problems. Thus, some heuristic optimization algorithms have been proposed. In this paper, exploration of association rules within numerical databases with Gravitational Search Algorithm (GSA) has been firstly performed. GSA has been designed as search method for quantitative association rules from the databases which can be regarded as search space. Furthermore, determining the minimum values of confidence and support for every database which is a hard job has been eliminated by GSA. Apart from t

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15

Lin, Mingmin, Yingpei Zeng, Ting Wu, Qiuhua Wang, Linan Fang, and Shanqing Guo. "GSA-Fuzz: Optimize Seed Mutation with Gravitational Search Algorithm." Security and Communication Networks 2022 (July 15, 2022): 1–17. http://dx.doi.org/10.1155/2022/1505842.

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Mutation-based fuzzing is currently one of the most effective techniques to discover software vulnerabilities. It relies on mutation strategies to generate interesting seeds. As a state-of-the-art mutation-based fuzzer, AFL follows a mutation strategy with high randomization, which uses randomly selected mutation operators to mutate seeds at random offsets. Its strategy may ignore some efficient mutation operators and mutation positions. Therefore, in this paper, we propose a solution named GSA-Fuzz to improve the efficiency of seed mutation strategy with the gravitational search algorithm (GS

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16

Purwoharjono, Purwoharjono Purwoharjono. "Penerapan Metode Gravitational Search Algorithm Menggunakan Static VAR Compensator." Jurnal Sistem dan Teknologi Informasi (JustIN) 10, no. 1 (2022): 175. http://dx.doi.org/10.26418/justin.v10i1.50575.

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Анотація:

Penerapan metode Gravitational Search Algorithm (GSA) ini bertujuan memperbaiki profil tegangan tenaga listrik menggunakan Static VAR Compensator (SVC). Penelitian ini dibandingkan hasil simulasi sebelum pemasangan SVC menggunakan metode Newton Raphson (NR) dan sesudah pemasangan SVC menggunakan metode GSA. Lokasi implementasi penelitian ini adalah system kelistrikan Jawa-Bali 500 kV. Hasil simulasi sesudah pemasangan SVC menggunakan metode GSA ini lebih baik dibandingkan dengan hasil simulasi sebelum pemasangan SVC menggunakan metode NR. Hasil simulasi sesudah pemasangan SVC menggunakan metod

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17

Nobahari, Hadi, Mahdi Nikusokhan, and Patrick Siarry. "A Multi-Objective Gravitational Search Algorithm Based on Non-Dominated Sorting." International Journal of Swarm Intelligence Research 3, no. 3 (2012): 32–49. http://dx.doi.org/10.4018/jsir.2012070103.

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Анотація:

This paper proposes an extension of the Gravitational Search Algorithm (GSA) to multi-objective optimization problems. The new algorithm, called Non-dominated Sorting GSA (NSGSA), utilizes the non-dominated sorting concept to update the gravitational acceleration of the particles. An external archive is also used to store the Pareto optimal solutions and to provide some elitism. It also guides the search toward the non-crowding and the extreme regions of the Pareto front. A new criterion is proposed to update the external archive and two new mutation operators are also proposed to promote the

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18

Mutlag, Ammar Hussein, Omar Nameer Mohammed Salim, and Siraj Qays Mahdi. "Optimum PID controller for airplane wing tires based on gravitational search algorithm." Bulletin of Electrical Engineering and Informatics 10, no. 4 (2021): 1905–13. http://dx.doi.org/10.11591/eei.v10i4.2953.

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In this paper, the gravitational search algorithm (GSA) is proposed as a method for controlling the opening and closing of airplane wing tires. The GSA is used to find the optimum proportional-integral-derivative (PID) controller, which controls the wing tires during take-off and landing. In addition, the GSA is suggested as an approach for overcoming the absence of the transfer function, which is usually required to design the optimum PID. The use of the GSA is expected to improve the system. Two of the most popular optimisation algorithms-the harmony search algorithm (HSA) and the particle s

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19

Ammar, Hussein Mutlag, Nameer Mohammed Salim Omar, and Qays Mahdi Siraj. "Optimum PID controller for airplane wing tires based on gravitational search algorithm." Bulletin of Electrical Engineering and Informatics 10, no. 4 (2021): 1905~1913. https://doi.org/10.11591/eei.v10i4.2953.

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Анотація:

In this paper, the gravitational search algorithm (GSA) is proposed as a method for controlling the opening and closing of airplane wing tires. The GSA is used to find the optimum proportional-integral-derivative (PID) controller, which controls the wing tires during take-off and landing. In addition, the GSA is suggested as an approach for overcoming the absence of the transfer function, which is usually required to design the optimum PID. The use of the GSA is expected to improve the system. Two of the most popular optimisation algorithms-the harmony search algorithm (HSA) and the particle s

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20

Hu, Hongping, Xiaxia Cui, and Yanping Bai. "Two Kinds of Classifications Based on Improved Gravitational Search Algorithm and Particle Swarm Optimization Algorithm." Advances in Mathematical Physics 2017 (2017): 1–7. http://dx.doi.org/10.1155/2017/2131862.

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Анотація:

Gravitational Search Algorithm (GSA) is a widely used metaheuristic algorithm. Although fewer parameters in GSA were adjusted, GSA has a slow convergence rate. In this paper, we change the constant acceleration coefficients to be the exponential function on the basis of combination of GSA and PSO (PSO-GSA) and propose an improved PSO-GSA algorithm (written as I-PSO-GSA) for solving two kinds of classifications: surface water quality and the moving direction of robots. I-PSO-GSA is employed to optimize weights and biases of backpropagation (BP) neural network. The experimental results show that

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21

Wang, Tongxiang, Xianglin Wei, Jianhua Fan, and Tao Liang. "Jammer Localization in Multihop Wireless Networks Based on Gravitational Search." Security and Communication Networks 2018 (2018): 1–11. http://dx.doi.org/10.1155/2018/7670939.

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Анотація:

Multihop Wireless Networks (MHWNs) can be easily attacked by the jammer for their shared nature and open access to the wireless medium. The jamming attack may prevent the normal communication through occupying the same wireless channel of legal nodes. It is critical to locate the jammer accurately, which may provide necessary message for the implementation of antijamming mechanisms. However, current range-free methods are sensitive to the distribution of nodes and parameters of the jammer. In order to improve the localization accuracy, this article proposes a jammer localization method based o

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22

Yu, Xiaobing, Xianrui Yu, and Xueying Zhang. "Case-based reasoning adaptation based on fuzzy gravitational search algorithm for disaster emergency plan." Journal of Intelligent & Fuzzy Systems 40, no. 6 (2021): 11007–22. http://dx.doi.org/10.3233/jifs-202132.

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Анотація:

Disasters can result in substantial destructive damages to the world. Emergency plan is vital to deal with these disasters. It is still difficult for the traditional CBR to generate emergency plans to meet requirements of rapid responses. An integrated system including Case-based reasoning (CBR) and gravitational search algorithm (GSA) is proposed to generate the disaster emergency plan. Fuzzy GSA (FGSA) is developed to enhance the convergence ability and accomplish the case adaptation in CBR. The proposed algorithm dynamically updates the main parameters of GSA by introducing a fuzzy system.

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23

Wu, Yi, Qiu Hua Tang, Li Ping Zhang, Zi Xiang Li, and Xiao Jun Cao. "Solving Two–Sided Assembly Line Balancing Problem via Gravitational Search Algorithm." Applied Mechanics and Materials 697 (November 2014): 450–55. http://dx.doi.org/10.4028/www.scientific.net/amm.697.450.

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Two-sided assembly lines are widely applied in plants for producing large-sized high volume products, such as trucks and buses. Since the two-sided assembly line balancing problem (TALBP) is NP-hard, it is difficult to get an optimal solution in polynomial time. Therefore, a novel swarm based heuristic algorithm named gravitational search algorithm (GSA) is proposed to solve this problem with the objective of minimizing the number of mated-stations and the number of stations simultaneously. In order to apply GSA to solving the TALBP, an encoding scheme based on the random-keys method is used t

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24

Falah, Miftahul, Dian Palupi Rini, and Iwan Pahendra. "Kombinasi Algoritma Backpropagation Neural Network dengan Gravitational Search Algorithm Dalam Meningkatkan Akurasi." JURNAL MEDIA INFORMATIKA BUDIDARMA 5, no. 1 (2021): 90. http://dx.doi.org/10.30865/mib.v5i1.2597.

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Predicting disease is usually done based on the experience and knowledge of the doctor. Diagnosis of such a disease is traditionally less effective. The development of medical diagnosis based on machine learning in terms of disease prediction provides a more accurate diagnosis than the traditional way. In terms of predicting disease can use artificial neural networks. The artificial neural network consists of various algorithms, one of which is the Backpropagation Algorithm. In this paper it is proposed that disease prediction systems use the Backpropagation algorithm. Backpropagation algorith

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25

Tian, Mengnan, Junhua Liu, Wei Yue, and Jie Zhou. "A Novel Integrated Heuristic Optimizer Using a Water Cycle Algorithm and Gravitational Search Algorithm for Optimization Problems." Mathematics 11, no. 8 (2023): 1880. http://dx.doi.org/10.3390/math11081880.

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Анотація:

This paper presents a novel composite heuristic algorithm for global optimization by organically integrating the merits of a water cycle algorithm (WCA) and gravitational search algorithm (GSA). To effectively reinforce the exploration and exploitation of algorithms and reasonably achieve their balance, a modified WCA is first put forward to strengthen its search performance by introducing the concept of the basin, where the position of the solution is also considered into the assignment of the sea or river and its streams, and the number of the guider solutions is adaptively reduced during th

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26

Rather, Sajad Ahmad, and P. Shanthi Bala. "Swarm-based chaotic gravitational search algorithm for solving mechanical engineering design problems." World Journal of Engineering 17, no. 1 (2020): 97–114. http://dx.doi.org/10.1108/wje-09-2019-0254.

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Анотація:

Purpose The purpose of this paper is to investigate the performance of chaotic gravitational search algorithm (CGSA) in solving mechanical engineering design frameworks including welded beam design (WBD), compression spring design (CSD) and pressure vessel design (PVD). Design/methodology/approach In this study, ten chaotic maps were combined with gravitational constant to increase the exploitation power of gravitational search algorithm (GSA). Also, CGSA has been used for maintaining the adaptive capability of gravitational constant. Furthermore, chaotic maps were used for overcoming prematur

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27

Saher, Albatran, I. Alomoush Muwaffaq, and M. Koran Ahmed. "Gravitational-Search Algorithm for Optimal Controllers Design of Doubly-fed Induction Generator." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 2 (2018): 780–92. https://doi.org/10.11591/ijece.v8i2.pp780-792.

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Анотація:

Recently, the Gravitational-Search Algorithm (GSA) has been presented as a promising physics-inspired stochastic global optimization technique. It takes its derivation and features from laws of gravitation. This paper applies the GSA to design optimal controllers of a nonlinear system consisting of a doubly-fed induction generator (DFIG) driven by a wind turbine. Both the active and the reactive power are controlled and processed through a back-to-back converter. The active power control loop consists of two cascaded proportional integral (PI) controllers. Another PI controller is used to set

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28

Sarjila, R., K. Ravi, J. Belwin Edward, K. Sathish Kumar, and Avagaddi Prasad. "Parameter Extraction of Solar Photovoltaic Modules Using Gravitational Search Algorithm." Journal of Electrical and Computer Engineering 2016 (2016): 1–6. http://dx.doi.org/10.1155/2016/2143572.

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Parameter extraction of a solar photovoltaic system is a nonlinear problem. Many optimization algorithms are implemented for this purpose, which failed in giving better results at low irradiance levels. This article presents a novel method for parameter extraction using gravitational search algorithm. The proposed method evaluates the parameters of different PV panels at various irradiance levels. A critical evaluation and comparison of gravitational search algorithm with other optimization techniques such as genetic algorithm are given. Extensive simulation analyses are carried out on the pro

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29

Albatran, Saher, Muwaffaq I. Alomoush, and Ahmed M. Koran. "Gravitational-Search Algorithm for Optimal Controllers Design of Doubly-fed Induction Generator." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 2 (2018): 780. http://dx.doi.org/10.11591/ijece.v8i2.pp780-792.

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Анотація:

Recently, the Gravitational-Search Algorithm (GSA) has been presented as a promising physics-inspired stochastic global optimization technique. It takes its derivation and features from laws of gravitation. This paper applies the GSA to design optimal controllers of a nonlinear system consisting of a doubly-fed induction generator (DFIG) driven by a wind turbine. Both the active and the reactive power are controlled and processed through a back-to-back converter. The active power control loop consists of two cascaded proportional integral (PI) controllers. Another PI controller is used to set

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30

Rather, Sajad Ahmad, and P. Shanthi Bala. "Levy Flight and Chaos Theory-Based Gravitational Search Algorithm for Global Optimization." International Journal of Applied Metaheuristic Computing 13, no. 1 (2022): 1–57. http://dx.doi.org/10.4018/ijamc.292496.

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Анотація:

The Gravitational Search Algorithm (GSA) is one of the highly regarded population-based algorithms. It has been reported that GSA has a powerful global exploration capability but suffers from the limitations of getting stuck in local optima and slow convergence speed. In order to resolve the aforementioned issues, a modified version of GSA has been proposed based on levy flight distribution and chaotic maps (LCGSA). In LCGSA, the diversification is performed by utilizing the high step size value of levy flight distribution while exploitation is carried out by chaotic maps. The LCGSA is tested

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31

Acherjee, Bappa, Debanjan Maity, and Arunanshu S. Kuar. "Ultrasonic Machining Process Optimization by Cuckoo Search and Chicken Swarm Optimization Algorithms." International Journal of Applied Metaheuristic Computing 11, no. 2 (2020): 1–26. http://dx.doi.org/10.4018/ijamc.2020040101.

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Анотація:

The ultrasonic machining (USM) process has been analyzed in the present study to obtain the desired process responses by optimizing machining parameters using cuckoo search (CS) and chicken swarm optimization (CSO), two powerful nature-inspired, population and swarm-intelligence-based metaheuristic algorithms. The CS and CSO algorithms have been compared with other non-conventional optimization techniques in terms of optimal results, convergence, accuracy, and computational time. It is found that CS and CSO algorithms predict superior single and multi-objective optimization results than gravit

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Pramana, Setia, and Imam Habib Pamungkas. "Improvement Method of Fuzzy Geographically Weighted Clustering using Gravitational Search Algorithm." Jurnal Ilmu Komputer dan Informasi 11, no. 1 (2018): 10. http://dx.doi.org/10.21609/jiki.v11i1.580.

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Geo-demographic analysis (GDA) is a useful method to analyze information based on location, utilizing several spatial analysis explicitly. One of the most efficient and commonly used method is Fuzzy Geographically Weighted Clustering (FGWC). However, it has a limitation in obtaining local optimal solution in the centroid initialization. A novel approach integrating Gravitational Search Algorithm (GSA) with FGWC is proposed to obtain global optimal solution leading to better cluster quality. Several cluster validity indexes are used to compare the proposed methods with the FGWC using other opti

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Patel, Nilesh M., N. Thangadurai, and Chirag Patel. "Analysis of Optimal Power Flow Using Combined PSO-GSA Technique." ITM Web of Conferences 65 (2024): 04003. http://dx.doi.org/10.1051/itmconf/20246504003.

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Using a hybrid approach that incorporates both particle swarm optimization (PSO) and gravitational search algorithms (GSA), this project aims to find the best way for power systems to distribute their energy. A novel heuristic search optimization technique, the GSA is works on the law of gravity. While this strategy has many advantages, it suffers from sluggish search performance and memory constraints. In order to discover a solution to this problem, the PSO technique was utilized. PSO and GSA, were utilized in this investigation to discover the optimal power flow utilizing a combination of t

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Aditya Sharma. "Comparative Analysis of Gravitational Search Algorithm and Particle Swarm Optimization for Solar MPPT." Journal of Electrical Systems 20, no. 9s (2024): 1710–18. http://dx.doi.org/10.52783/jes.4680.

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This work delves into the optimization of Maximum Power Point Tracking (MPPT) for photovoltaic (PV) systems through a comparative analysis of two advanced algorithms: the Gravitational Search Algorithm (GSA) and Particle Swarm Optimization (PSO). With the escalating demand for renewable energy sources, enhancing the efficiency of solar panels has become crucial. MPPT techniques are pivotal in maximizing the power output from solar panels by adjusting to varying environmental conditions. This work implements GSA and PSO within a MATLAB environment to track the MPP of a solar cell array efficien

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Lin, Zefeng, and Jianmei Xiao. "Reconfiguration of distributed power distribution networks based on improved gravitational search algorithms." Journal of Physics: Conference Series 2741, no. 1 (2024): 012054. http://dx.doi.org/10.1088/1742-6596/2741/1/012054.

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Анотація:

Abstract In order to solve the problem of weak global search ability and premature convergence of GSA, a hybrid algorithm combining GSA and PSO is proposed. This algorithm can effectively use the advantages of PSO in global search. In addition, the update strategy of the gravitational constant is optimized, which improves the early search ability of the algorithm. Taking the reduction of network loss as the objective function, the improved algorithm is used to reconstruct the distribution network with distributed generation. The simulation results of the IEEE33 system show that this algorithm

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Jiang, Shanhe, Chaolong Zhang, and Shijun Chen. "Sequential Hybrid Particle Swarm Optimization and Gravitational Search Algorithm with Dependent Random Coefficients." Mathematical Problems in Engineering 2020 (April 21, 2020): 1–17. http://dx.doi.org/10.1155/2020/1957812.

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Анотація:

Particle swarm optimization (PSO) has been proven to show good performance for solving various optimization problems. However, it tends to suffer from premature stagnation and loses exploration ability in the later evolution period when solving complex problems. This paper presents a sequential hybrid particle swarm optimization and gravitational search algorithm with dependent random coefficients called HPSO-GSA, which first incorporates the gravitational search algorithm (GSA) with the PSO by means of a sequential operating mode and then adopts three learning strategies in the hybridization

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Worasucheep, Chukiat. "Enhancement of Gravitational Search Algorithm using A Differential Mutation Operator and Its Application on Reconstructing Gene Regulatory Network." ECTI Transactions on Computer and Information Technology (ECTI-CIT) 12, no. 2 (2019): 176–86. http://dx.doi.org/10.37936/ecti-cit.2018122.134980.

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Gravitational Search Algorithm (GSA) is a recent stochastic search algorithm that is inspired from the concepts of gravity rule and law of motion in physics. Despite its success and attractiveness, it has some coefficients and parameters that should be properly tuned to improve its performance. This paper studies the performance of GSA by varying the parameters that controls its gravitational force. Then a new differential mutation operator is proposed to enhance performance of GSA by accelerating its convergence. The proposed algorithm, namely DMGSA, is evaluated using 15 well-known benchmark

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Jiang, Shanhe, Chaolong Zhang, Wenjin Wu, and Shijun Chen. "Combined Economic and Emission Dispatch Problem of Wind-Thermal Power System Using Gravitational Particle Swarm Optimization Algorithm." Mathematical Problems in Engineering 2019 (November 21, 2019): 1–19. http://dx.doi.org/10.1155/2019/5679361.

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In this paper, a novel hybrid optimization approach, namely, gravitational particle swarm optimization algorithm (GPSOA), is introduced based on particle swarm optimization (PSO) and gravitational search algorithm (GSA) to solve combined economic and emission dispatch (CEED) problem considering wind power availability for the wind-thermal power system. The proposed algorithm shows an interesting hybrid strategy and perfectly integrates the collective behaviors of PSO with the Newtonian gravitation laws of GSA. GPSOA updates particle’s velocity caused by the dependent random cooperation of GSA

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Amer, Noor Hafizah, Nurhidayati Ahmad, and Amar Faiz Zainal Abidin. "Weight Minimization of Helical Compression Spring Using Gravitational Search Algorithm (GSA)." Applied Mechanics and Materials 773-774 (July 2015): 277–81. http://dx.doi.org/10.4028/www.scientific.net/amm.773-774.277.

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Compression spring is one of the most common mechanical componet being used in most mechanisms. Many criteria and constraints should be considered in designing and specifying the spring dimensions. Therefore, it has been one of the standard case studies considered to test a new optimisation algorithm. This paper introduced an optimization method named Gravitational search Algorithm (GSA) to solve the problem of weight minimization of spring. From previous studies, weight minimization of a spring has been investigated by many researcher using various optimization algorithm technique. The result

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Zhang, Daming, Fangjin Sun, Tiantian Liu, and Zhonghao Xu. "Mixture Ratio Design Optimization of Coal Gangue-Based Geopolymer Concrete Based on Modified Gravitational Search Algorithm." Advances in Civil Engineering 2021 (April 19, 2021): 1–11. http://dx.doi.org/10.1155/2021/6620853.

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Анотація:

A green concrete, new type of coal gangue-based geopolymer concrete, was prepared. Coal gangue geopolymer concrete contains many mineral admixtures and alkaline activators; the concrete mixture ratio design has always been a complex problem. The framework of the mix design optimization by the proposed method is established in this work. The paper aims to minimize the economic cost under the premise of ensuring the strength and workability of coal gangue-based geopolymer concrete. Gravitational search algorithm (GSA) has the advantages of faster convergence speed and stronger exploitation perfo

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Sidhu, D. S., J. S. Dhillon, and Dalvir Kaur. "Design of Digital IIR Filter with Conflicting Objectives Using Hybrid Gravitational Search Algorithm." Mathematical Problems in Engineering 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/282809.

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In the recent years, the digital IIR filter design as a single objective optimization problem using evolutionary algorithms has gained much attention. In this paper, the digital IIR filter design is treated as a multiobjective problem by minimizing the magnitude response error, linear phase response error and optimal order simultaneously along with meeting the stability criterion. Hybrid gravitational search algorithm (HGSA) has been applied to design the digital IIR filter. GSA technique is hybridized with binary successive approximation (BSA) based evolutionary search method for exploring th

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Hota, Prakash Kumar, and Nakul Charan Sahu. "Non-Convex Economic Dispatch with Prohibited Operating Zones through Gravitational Search Algorithm." International Journal of Electrical and Computer Engineering (IJECE) 5, no. 6 (2015): 1234. http://dx.doi.org/10.11591/ijece.v5i6.pp1234-1244.

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This paper presents a new approach to the solution of optimal power generation for economic load dispatch (ELD) using gravitational search algorithm (GSA) when all the generators include valve point effects and some/all of the generators have prohibited operating zones. In this paper a gravitational search algorithm is suggested that deals with equality and inequality constraints in ELD problems. A constraint treatment mechanism is also discussed to accelerate the optimization process<strong>. </strong>To verify the robustness and superiority of the proposed GSA based approach, a p

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Le, Dinh-Viet, Ngoc-Phuong Pham, Quang-Phuc Nguyen, and Cao-Tho Phan. "Proposing Binary Gravitational Search Algorithm Parameters for Back-calculation of Road Pavement Moduli." IOP Conference Series: Materials Science and Engineering 1289, no. 1 (2023): 012061. http://dx.doi.org/10.1088/1757-899x/1289/1/012061.

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Abstract A Falling Weight Deflectometer is popular equipment to measure surface deflections under imposed loadings, providing the necessary parameters for back-calculating the elastic moduli of road pavements. There are several back-calculation programs available that accurately back-calculate pavement layer moduli. The Gravitational Search Algorithm (GSA), a metaheuristic optimization algorithm inspired by Newton’s law of universal gravitation, is one such algorithm. The Binary Gravitational Search Algorithm (BGSA) is an enhancement algorithm based on GSA that can be used as an efficient sear

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Haeri, Ali, and Mohammad Javad Fadaee. "The Gravitational Search Algorithm in Antiresonance Layer Optimization of Laminated Composite Plates." International Journal of Computational Methods 14, no. 06 (2017): 1750070. http://dx.doi.org/10.1142/s0219876217500700.

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In the present study, Gravitational Search Algorithm (GSA) is combined with Finite Element Method (FEM) for optimizing laminated composites vibration behavior. The fiber orientation angle of layers is considered as design variable. The 8-layerd and 12-layerd plates with both of square and rectangular shapes are investigated. Twenty distinct boundary conditions and [Formula: see text] of fiber angle increment are considered. The results of the proposed method are in good agreement with reference methods, and in some cases the GSA-FEM is more efficient. Moreover, the simple structure of GSA and

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Wan, Youchuan, Mingwei Wang, Zhiwei Ye, and Xudong Lai. "A “Tuned” Mask Learnt Approach Based on Gravitational Search Algorithm." Computational Intelligence and Neuroscience 2016 (2016): 1–16. http://dx.doi.org/10.1155/2016/8179670.

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Texture image classification is an important topic in many applications in machine vision and image analysis. Texture feature extracted from the original texture image by using “Tuned” mask is one of the simplest and most effective methods. However, hill climbing based training methods could not acquire the satisfying mask at a time; on the other hand, some commonly used evolutionary algorithms like genetic algorithm (GA) and particle swarm optimization (PSO) easily fall into the local optimum. A novel approach for texture image classification exemplified with recognition of residential area i

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Dr.K.Lenin. "AMENDED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR REAL POWER LOSS REDUCTION AND STATIC VOLTAGE STABILITY MARGIN INDEX ENHANCEMENT." International Journal of Research - Granthaalayah 6, no. 2 (2018): 146–56. https://doi.org/10.5281/zenodo.1189217.

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In this paper, Amended Particle Swarm Optimization Algorithm (APSOA) is proposed with the combination of Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) for solving the optimal reactive power dispatch Problem. PSO is one of the most widely used evolutionary algorithms in hybrid methods due to its simplicity, convergence speed, an ability of searching Global optimum. GSA has many advantages such as, adaptive learning rate, memory-less algorithm and, good and fast convergence. Proposed hybridized algorithm is aimed at reduce the probability of trapping in local optimum

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Cheema, Sikander Singh, Amardeep Singh, and Hassène Gritli. "Optimal Crop Selection Using Gravitational Search Algorithm." Mathematical Problems in Engineering 2021 (April 19, 2021): 1–14. http://dx.doi.org/10.1155/2021/5549992.

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For the economic growth of the crop, the optimal utilization of soil is found to be an open area of research. An efficient utilization includes various advantages such as watershed insurance, expanded biodiversity, and reduction of provincial destitution. Generally, soils present synthetic confinements for crop improvement. Therefore, in this paper, a novel diversified crop model is proposed to predict the suitable soil for good production of the crop. The proposed model utilizes a quantum value-based gravitational search algorithm (GSA) to optimize the best solution. Various features of soil

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Milovanović, Miloš, Jordan Radosavljević, and Bojan Perović. "Optimal Distributed Generation Allocation in Distribution Systems with Non-Linear Loads Using a New Hybrid Meta-Heuristic Algorithm." B&H Electrical Engineering 13, no. 1 (2019): 4–13. http://dx.doi.org/10.2478/bhee-2019-0001.

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Abstract This paper presents a new hybrid meta-heuristic algorithm based on the Phasor Particle Swarm Optimization (PPSO) and Gravitational Search Algorithm (GSA) for optimal allocation of distributed generation (DG) in distribution systems with non-linear loads. Performance of the algorithm is evaluated on the IEEE 69-bus system with the aim of reducing power losses, as well as improving voltage profile and power quality. Results, obtained using the proposed algorithm, are compared with those obtained using the original PSO, PPSO, GSA and PSOGSA algorithms. It is found that the proposed algor

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Muhammad, Badaruddin, Zuwairie Ibrahim, Mohd Falfazli Mat Jusof, Nor Azlina Ab Aziz, Nor Hidayati Abd Aziz, and Norrima Mokhtar. "A Hybrid Simulated Kalman Filter - Gravitational Search Algorithm (SKF-GSA)." Proceedings of International Conference on Artificial Life and Robotics 22 (January 19, 2017): 707–10. http://dx.doi.org/10.5954/icarob.2017.gs11-5.

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Durairaj, M., and S. Gowri. "Gravitational Search Algorithm - Based Optimization of Process Parameters in Micro Turning Process." Applied Mechanics and Materials 592-594 (July 2014): 391–94. http://dx.doi.org/10.4028/www.scientific.net/amm.592-594.391.

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Micro turning is a scaled down version of conventional turning process, but operating on the micro scale of machining parameters to produce micro components. This paper deals with CNC Micro turning of Inconel 600 alloy with titanium carbide coated tool. Two conflicting objectives, surface roughness and tool flank wear, are simultaneously optimized. Full factorial experiments were taken with several combinations of cutting speed, feed and depth of cut. In this report, a new optimization algorithm based on the law of gravitation and mass interactions, namely Gravitational Search Algorithm (GSA)

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