Open Access
Int. J. Simul. Multidisci. Des. Optim.
Volume 4, Number 1, January 2010
Page(s) 27 - 32
Published online 21 July 2011
  1. J. Behnamian, S.M.T. Fatemi Ghomi. Development of a PSO-SA hybrid metaheuristic for a new comprehensive regression model to time-series forecasting, Expert Systems with Applications, 974-984, (2010).
  2. V. Savsani, R.V. Rao, D.P. Vakharia. Optimal weight design of a gear train using particle swarm optimization and simulated annealing algorithms, Mechanism and Machine Theory, 531-541, (2010).
  3. M.M. Ali, M.N. Gabere. A simulated annealing driven multi-start algorithm for bound constrained global optimization, Journal of Computational and Applied Mathematics, 2661-2674, (2010).
  4. T. Niknam, B. Amiri, J. Olamaei, A. Arefi. An efficient hybrid evolutionary optimization algorithm based on PSO and SA for clustering, Journal of Zhejiang University SCIENCE, 512-519, (2009).
  5. S. Sitarz. Ant algorithms and simulated annealing for multicriteria dynamic programming, Computers & Operations Research, 433-441, (2009).
  6. Y. Zhaoa, W. Zub, H. Zeng. A modified oarticle swarm optimization via particle visual modelling analysis, Computers and Mathematics with Applications, 2022-2029, (2009).
  7. M.H. Alrefaei, A.H. Diabat. A simulated annealing technique for multi-objective simulation optimization, Applied Mathematics and Computation, 3029-3035, (2009).
  8. M. Bahrepour, E. Mahdipour, R. Cheloi, M. Yaghoobi. SUPER SAPSO: A Nex SA-Based PSO Algorithm, Appllications of Soft Computing, 423-430, (2009).
  9. W. Du, B. Li. Multi-strategy ensemble particle swarm optimization for dynamic optimization, Information Sciences, 3096-3109, (2008).
  10. L. Lamberti. An efficient simulated annealing algorithm for design optimization of truss structures, Computers and Structures, 1936-1953, (2008).
  11. S.W. Lin, T.Y. Tseng, S.Y. Chou, S.C. Chen. A simulated-annealing-based approach for simultaneous parameter optimization and feature selection of back-propagation networks, Expert Systems with Applications, 1491-1499, (2008).
  12. L.L. Li, D.H. Zhou, L. Wang. Fault Diagnosis of Nonlinear Systems based on hybrid PSOSA optimization algorithm, International Journal of Automation and Computing, 183-188, (2007).
  13. B. Liu, L. Wang, Y.H. Jin. An effective hybrid particle swarm optimization for no wait flow shop scheduling, Int. J. Adv. Manuf. Technol., 1001-1011, (2007).
  14. F. Zhao, Y. Hong, D. Yu, Y. Yang, Q. Zhang, H. Yi. A hybrid algorithm based on particle swarm optimization and simulated annealing to holon task allocation for holonic manufacturing system, Int. J. Adv. Manuf. Technol., 1021-1032, (2007).
  15. P.S. Shelokar, P. Siarry, V.K. Jayaraman, B.D. Kulkarni. Particle swarm and ant colony algorithms hybridized for improved continuous optimization, Applied Mathematics and Computation, 129-142, (2007).
  16. R. Brits, A.P. Engelbrecht, F. Van Den Bergh. Locating multiple optima using particle swarm optimization, Applied Mathematics and Computation, 1859-1883, (2007).
  17. Y. Jiang, T. Hu, C. Huang, X. Wu. An improved particle swarm optimization algorithm, Applied Mathematics and Computation, 231-239, (2007).
  18. Y. Liu, Z. Qin, Z. Shi, J. Lu. center particle swarm optimization, Neurocomputing, 672-679, (2007).
  19. B. Bochenek, P. Forys. Structural optimization for post buckling behavior using particle swarms, Struct. Multidisc. Optim., 521-531, (2006).
  20. D. Chaojin, Q. Zulian. Particle swarm optimization algorithm based on the idea of simulated annealing, International Journal of Computer Science and Network Security 6 (10), (2006).
  21. W.J. Xia, Z.M. Wu. A hybrid particle swarm approach for the job shop scheduling problem, Int. J. Adv. Manuf. Technol., 360-366, (2006).
  22. R.C. Eberhart, J. Kennedy. A new optimizer using particle swarm theory, Proceedings Sixth Symposium on Micro Machine and Human Science, IEEE Service Center, Piscataway, NJ, 39-43, (1995).

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