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Raja Balachandar, S.
- Newton's Law of Gravity-based Search Algorithms
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Authors
Affiliations
1 Department of Mathematics, SASTRA University, Thanjavur, 613001, IN
1 Department of Mathematics, SASTRA University, Thanjavur, 613001, IN
Source
Indian Journal of Science and Technology, Vol 6, No 2 (2013), Pagination: 4141-4150Abstract
Many heuristic optimization methods have been developed in recent years that are derived from Nature. These methods take inspiration from physics, biology, social sciences, and use of repeated trials, randomization, and specific operators to solve NP-hard combinatorial optimization problems. In this paper we try to describe the main characteristics of heuristics derived from "Newton's law of gravitation", namely a gravitational emulation local search algorithm and a gravitational search algorithm. We also present the detailed survey of distinguishing properties, parameters and applications of these two algorithms.Keywords
Meta-Heuristic Algorithms, Gravitation, Newton's Law of Gravity, Combinatorial Optimization Problems, NP-HardReferences
- Abbas Bahrololoum, HosseinNezamabadi-pour, Hamid Bahrololoum, Masoud Saeed, (2012).A prototype classifier based on gravitational search algorithm. Applied Soft Computing. 2(2),819-825.
- Badr, A. and Fahmy, A.(2004).A proof of convergence for ant algorithms. Information Sciences 160, 267-279.
- Barzegar, B., Rahmani,A.M. and Far Kz(2009). Gravitational emulation local search algorithm for advanced reservation and scheduling in grid computing systems.fourth international conference on computer sciences and convergence information technology, 1240-1245.
- Beasley, J.E.(1990). OR-Library:Distributing Test Problems by Electronic Mail. Journal of Operational Research Society 41, 1069-1072.
- Behrang, M.A., Assareh, E., Ghalambaz, M., Assari, M.R, andNoghrehabadi, A.R (2011). Forecasting future oil demand in Iran using GSA (Gravitational Search Algorithm). Energy, 36(9), 5649-5654.
- Bergh, F.V.D. andEngelbrecht,A.P., (2006).A study of particle swarm optimization particle trajectories.Information Sciences, 176, 937-971.
- Binod Shaw, Mukherjee, V. and Ghoshal, S.P.(2012). A novel opposition-based gravitational search algorithm for combined economic and emission dispatch problems of power systems. Electrical Power and Energy Systems, 35(1), 21-33.
- Chaoshun Li and Jianzhong Zhou (2011).Parameters identification of hydraulic turbine governing system using improved gravitational search algorithm. Energy Conversion and Management, 52(1), 374-381.
- Dorigo, M., Maniezzo, V.and Colorni, A. (1996).The ant system: optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics – Part B, 26(1),29-41.
- Ellabib, I., Calamai, P. and Basir, O.(2007).Exchange strategies for multiple ant colony system. Information Sciences, 177, 1248-1264.
- Glover,F.(1989).Tabu search, part I. ORSA, Journal on Computing, 1(3), 190-206.
- Glover, F.(1990).Tabu search, part II. ORSA, Journal on Computing, 2, 4-32.
- Hamzaçebi, C.(2008).Improving genetic algorithms’ performance by local search for continuous function optimization. Applied Mathematics and Computation, 196(1), 309-317.
- Holliday, D, Resnick, R. and Walker, J.(1993). Fundamentals of physics. John Wiley and Sons.
- Hopfield,J. (1982).Neutral networks and physical systems with emergent collective computational abilities.proc.Natl. Acad.Sci.USA,Vol.81,3088-3092.
- Kirkpatrick, S., Gelatto, C.D. andVecchi, M.P.(1983). Optimization by simulated annealing. Science, 220, 671-680.
- Kennedy, J.and Eberhart, R.C.(1995). Particle swarm optimization. in: Proceedings of IEEE International Conference on Neural Networks, 4, 1942-1948.
- Lozano, M., Herrera, F. and Cano, J.R.(2008). Replacement strategies to preserve useful diversity in steady-state genetic algorithms. Information Sciences, 178, 4421-4433.
- Minghao Yin, Yanmei Hu, Fengqin Yang, Xiangtao Li, and WenxiangGu(2011). A novel hybrid K-harmonic means and gravitational search algorithm approach for clustering. Expert Systems with Applications, 38, 9319-9324.
- Raja,Balachandar S. andKannan, K.(2007) Randomized gravitational emulation search algorithm for symmetric traveling salesman problem. Applied Mathematics and Computation, 192,413-421.
- Raja,Balachandar S.and Kannan, K.(2009). A Meta-heuristic algorithm for Vertex covering problem Based on Gravity. International Journal of Computational and Mathematical Sciences, 3(7), 332-336.
- Raja,Balachandar S. and Kannan, K.(2010). A Meta-heuristic algorithm for Set covering problem Based on Gravity. International Journal of Computational and Mathematical Sciences. 4(5), 223-228.
- Rashedi, E.(2007). Gravitational Search Algorithm, M.Sc. Thesis. ShahidBahonar University of Kerman, Kerman, Iran.
- Rashedi,E.et al.(2009). GSA: A Gravitational Search Algorithm. Information Sciences, 179, 2232-2248.
- Rashedi, E., HosseinNezamabadi-pour and SaeidSaryazdi (2010).BGSA: binary gravitational search algorithm. Natural Computing, 9, 727-745.
- Rashedi, E., HossienNezamabadi-pour and SaeidSaryazdi( 2011). Filter modeling using gravitational search algorithm. Engineering applications of Artificial Intelligence, 24, 117-122.
- Righini,G. (1992).Modelli di retineurali per otimisizzazione combination.RicercaOperativa, 62, 29-67.
- Sarafrazi, S., Nezamabadi-pour, H.and Saryazdi, S.(2011). Disruption: A new operator in gravitational search algorithm. ScientiaIranica, Transactions D: Computer Science & Engineering and Electrical Engineering, 18, 539-548.
- Schutz, B.(2003). Gravity from the Ground Up, Cambridge University Press.
- Sears,Francis W., Mark W.Zemansky and Hugh D. Young(1987). University Physics,7th ed.Reading, MA. Addison- Wesley.
- SoroorSarafrazi andHosseinNezamabadi-pour (2013). Facing the classification of binary problems with a GSA-SVM hybrid system. Mathematical and Computer Modeling, 57(1–2), 270-278.
- Tang, K.S., Man, K.F., Kwong, S. and He, Q. (1996). Genetic algorithms and their applications. IEEE Signal Processing Magazine, 13(6), 22-37.
- Tripathi, P.K., Bandyopadhyay, S. and Pal, S.K. (2007). Multi-objective particle swarm optimization with time variant inertia and acceleration coefficients. Information Sciences, 177, 5033-5049.
- Voudouris,Chris and Edward Tsang(1995), “Guided Local Search”. Technical Report CSM-247, Department of Computer Science, University of Essex,UK.
- Webster, B. L.(2004).Solving combinatorial optimization problems using a new algorithm based on gravitational attraction, Ph.D. thesis, Florida Institute of Technology, Melbourne, FL.
- Yao, X., Liu, Y. and Lin, G.(1999).Evolutionary programming made faster. IEEE Transactions on Evolutionary Computation, 3, 82-102.
- Wavelet Solution for Class of Nonlinear Integro-differential Equations
Abstract Views :330 |
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Authors
Affiliations
1 Department of Mathematics, School of Humanities and Sciences, SASTRA University, Thanjavur-613401, Tamilnadu, IN
1 Department of Mathematics, School of Humanities and Sciences, SASTRA University, Thanjavur-613401, Tamilnadu, IN
Source
Indian Journal of Science and Technology, Vol 6, No 6 (2013), Pagination: 4670-4677Abstract
The aim of this work is to study the Legendre wavelets for the solution of a class of nonlinear Volterra integro-differential equation. The properties of Legendre wavelets together with the Gaussian integration method are used to reduce the problem to the solution of nonlinear algebraic equations. Also a reliable approach for convergence of the Legendre wavelet method when applied to nonlinear Volterra equations is discussed. Illustrative examples have been discussed to demonstrate the validity and applicability of the technique and the results obtained by Legendre wavelet method is very nearest to the exact solution. The results demonstrate reliability and efficiency of the proposed method.Keywords
Legendre Wavelets, Integro-differential Equations, Gaussian Integration, Legendre Wavelet Method, Convergence AnalysisReferences
- Abbasbandy S (2006a). Numerical solutions of the integral equations: homotopy perturbation method and Adomian’s decomposition method, Applied Mathematics and Computation, vol 173(1), 493-500.
- Abbasbandy S (2006b). Application of He’s homotopy perturbation method for Laplace transform, Chaos Solitons & Fractals, vol 30(5), 1206-1212.
- Abbasbandy S (2007). Application of He’s homotopy perturbation method to functional integral equations, Chaos Solitons & Fractals, vol 31(5), 1243-1247.
- Avudainayagam A, and Vani C (2000). Wavelet-Galerkin method for integro-differential equations, Applied Numerical Mathematics, vol 32(3), 247-254.
- Beylkin G, Coifman R et al. (1991). Fast wavelet transforms and numerical algorithms I, Communications on Pure and Applied Mathematics, vol 44(2), 141-183.
- Chui C K (1997). Wavelets: A mathematical tool for signal analysis, SIAM, Philadelphia, PA.
- El-Shahed M (2005). Application of He’s homotopy perturbation method to Volterra’s integro-differential equation, International Journal of Nonlinear Sciences and Numerical Simulation, vol 6(2), 163-168.
- Ghasemi M, Kajani C M T et al. (2006). Numerical solution of linear integro-differential equations by using sine-cosine wavelet method, Applied Mathematics and Computation, vol 180(2), 569-574.
- Ghasemi M, Kajani C M T et al. (2007a). Comparison between wavelet Galerkin method and homotopy perturbation method for the nonlinear integro-differential equations, Computers Mathematics with Applications, vol 54, 1162-1168.
- Ghasemi M, Kajani C M T et al. (2007b). Comparison between the homotopy perturbation method and the sine-cosine wavelet method for solving linear integro-differential equations, Computers Mathematics with Applications, vol 54(7-8), 1162-1168.
- Ghasemi M, Kajani C M T et al. (2007c). Numerical solutions of the nonlinear integro-differential equations: Wavelet-Galerkin method and homotopy perturbation method, Applied Mathematics and Computation, vol 188(1), 450-455.
- Ghasemi M, Kajani C M T et al. (2007d). Application of He’s homotopy perturbation method to nonlinear integro-differential equations, Applied Mathematics and Computation, vol 188(1), 538-548.
- He J H (2000). Variational iteration method for autonomous ordinary differential systems, Applied Mathematics and Computation, vol 114(2-3), 115-123.
- He J H (2004). Comparison of homotopy perturbation method and homotopy analysis method, Applied Mathematics and Computation, vol 156(2), 527-539.
- He J H, and Wu X H (2006). Construction of solitary solution and compacton-like solution by variational iteration method, Chaos Solitons & Fractals, vol 29(1), 108-113.
- Lepik U (2006). Haar wavelet method for nonlinear integro-differential equations, Applied Mathematics and Computation, vol 176(1), 324-333.
- Maleknejad K, Basirat B et al. (2011). Hybrid Legendre polynomials and block-pulse functions approach for nonlinear Volterra-Fredholm integro-differential equations, Computers & Mathematics with applications, vol 61(9), 2821-2828.
- Alizadeh S R S, Domairry G G et al. (2008). An approximation of the analytical solution of the linear and nonlinear integro-differential equations by homotopy perturbation method, Acta Applicandae Mathematics, vol 104(3), 355-366.
- Venkatesh S G, Ayyaswamy S K et al. (2012a). The Legendre wavelet method for solving initial value problems of Bratu-type, Computers & Mathematics with Applications, vol 63(8), 1287-1295.
- Venkatesh S G, Ayyaswamy S K et al. (2012b). Convergence analysis of Legendre wavelets method for solving Fredholm integral equations, Applied Mathematical Sciences, vol 6, No. 6, 2289-2296.
- Venkatesh S G, Ayyaswamy S K et al. (2012c). Legendre approximation solution for a class of higher order Volterra integro-differential equations, Ain Shams Engineering Journal, vol 3(4), 417-422.
- Venkatesh S G, Ayyaswamy S K et al. (2012d). Legendre wavelets method for Cauchy problems, Applied Mathematical Sciences, vol 6, No. 126, 6281-6286.
- Wazwaz A M (2001). A reliable algorithm for solving boundary value problems for higher-order integro-differential equations, Applied Mathematics and Computation, vol 118(2-3), 327-342.
- Yusufoglu E (Agadjanov) (2009). Numerical solving initial value problem for Fredholm type linear integro-differential equation system, Journal of the Franklin Institute, vol 346(6), 636-649.
- Zhao J, and Corless R M (2006). Compact finite difference method for integro-differential equations, Applied Mathematics and Computation, vol 177, 271-288.