Global optimization using a multipoint type quasi-chaotic optimization method

Applied Soft Computing Journal

Volumn 13, Issue 2, 2013, Pages 1247-1264

  Okamoto, Takashi ^a   Hirata, Hironori ^a  

^a CHIBA UNIVERSITY   (Japan)

Author keywords

Approximation; Chaos; Coupled dynamics; Global optimization; Multipoint search; Simultaneous perturbation gradien

Indexed keywords

CHAOS THEORY; GLOBAL OPTIMIZATION; HEURISTIC METHODS; PROBLEM SOLVING;

APPROXIMATION; COUPLED DYNAMICS; GLOBAL OPTIMIZATION METHOD; GRADIENT APPROXIMATION; MULTIPOINT SEARCH; OBJECTIVE FUNCTION VALUES; SIMULTANEOUS PERTURBATION; UNCONSTRAINED OPTIMIZATION PROBLEMS;

OPTIMIZATION;

EID: 84881552974     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2012.10.025     Document Type: Article

References (26)

1. K. Aihara, T. Takabe, M. Toyoda, Chaotic neural networks, Physics Letters A 144 (1990) 333-340.
2. S. Bhatnagar, Simultaneous perturbation and finite difference methods, in: Wiley Encyclopedia of Operations Research and Management Science, John Wiley &Sons, Inc., Hoboken, NJ, 2011.
3. H.F. Chen, T.E. Duncan, B. Pasik-Duncan, A stochastic approximation algorithm with random differences, in: Proc. of IFAC the 13th Triennal World Congress, IFAC, Laxenburg, Austria, 1996, pp. 493-496.
4. L. Gerencser, Z. Vago, SPSA in noise free optimization, in: Proc. of American Control Conference 2000, AACC, Danvers, MA, 2000, pp. 3284-3288. (Pubitemid 32027960)
5. F. Glover, M. Laguna, Tabu Search, Kluwer Academic Publishers, Netherlands, 1997.
6. W. Gong, Z. Cai, C. Ling, DE/BBO: a hybrid differential evolution with biogeography-based optimization for global numerical optimization, Soft Computing 15 (2011) 645-665.
7. J. Kennedy, R.C. Eberhart, Particle swarm optimization, in: Proc. of IEEE Int. Conf. Neural Networks, IEEE, Washington, DC, 1995, pp. 1942-1948.
8. J. Kennedy, R.C. Eberhart, Y. Shi, Swarm Intelligence, Morgan Kaufmann Publishers, San Francisco, CA, 2001.
9. S. Kiranyaz, T. Ince, M. Gabbouj, Stochastic approximation driven particle swarm optimization with simultaneous perturbation - who will guide the guide? Applied Soft Computing 11 (2011) 2334-2347.
10. S. Kiranyaz, T. Ince, A. Yildirim, M. Gabbouj, Fractional particle swarm optimization in multidimensional search space, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 40 (2010) 298-319.
11. J. Liang, S. Baskar, P. Suganthan, A. Qin, Performance evaluation of multiagent genetic algorithm, Natural Computing 5 (2006) 83-96. (Pubitemid 43125850)
12. J.J. Liang, P.N. Suganthan, K. Deb, Novel composition test functions for numerical global optimization, in: Proc. of Swarm Intelligence Symposium 2005 (SIS 2005), IEEE, Washington, DC, 2005, pp. 68-75.
13. Y. Maeda, M. Wakamura, Simultaneous perturbation learning rule for recurrent neural networks and its FPGA implementation, IEEE Transactions on Neural Networks 16 (2005) 1664-1672. (Pubitemid 41714996)
14. J.L. Maryak, D.C. Chin, Global random optimization by simultaneous perturbation stochastic approximation, Johns Hopkins APL Technical Digest 25 (2004) 91-100.
15. J.L. Maryak, D.C. Chin, Global random optimization by simultaneous perturbation stochastic approximation, IEEE Transactions on Automatic Control 53 (2008) 780-783. (Pubitemid 351597184)
16. J.L. Maryak, J.C. Spall, Simultaneous perturbation optimization for efficient image restoration, IEEE Transactions on Aerospace and Electronic Systems 41 (2005) 356-361. (Pubitemid 40679239)
17. K. Masuda, E. Aiyoshi, Global optimization method using choas of discrete gradient dynamics, in: Proc. of IFAC Workshops ALCOSP &PSYCO 2004, IFAC, Laxenburg, Austria, 2004, pp. 825-830.
18. M. Mizukami, M. Hirano, K. Shinjo, Simultaneous alignment of multiple optical axes in a multistage optical system using Hamiltonian algorithm, Optical Engineering 40 (2001) 448-454. (Pubitemid 32426949)
19. N. Nusawardhana, S.H. Zak, Simultaneous perturbation extremum seeking method for dynamic optimization problems, in: Proc. of American Control Conference 2004, AACC, Danvers, MA, 2004, pp. 2805-2810.
20. T. Okamoto, E. Aiyoshi, Global optimization using a synchronization of multiple search points autonomously driven by a chaotic dynamic model, Journal of Global Optimization 41 (2008) 219-244. (Pubitemid 351614319)
21. A. Pikovsky, M. Rosenblum, J. Kurths, R.C. Hilborn, Synchronization: A Universal Concept in Nonlinear Science, Cambridge University Press, Cambridge, UK, 2002.
22. K. Price, R.M. Storn, J.A. Lampinen, Differential Evolution - A Practical Approach to Global Optimization, Springer, New York, NY, 2005.
23. J.C. Spall, Introduction to Stochastic Search and Optimization: Estimation Simulation and Control, Wiley-Interscience, Hoboken, NJ, 2003.
24. R. Storn, K. Price, Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces, Journal of Global Optimization 11 (1997) 341-359. (Pubitemid 127502202)
25. I. Tokuda, K. Onodera, R. Tokunaga, K. Aihara, T. Nagashima, Global bifurcation scenario for chaotic dynamical systems that solve optimization problems and analysis of their optimization capability, Electronics and Communications in Japan (Part III: Fundamental Electronic Science) 81 (1998) 1-12. (Pubitemid 128588411)
26. H. Ying, M.C. Fu, S.I. Marcus, Convergence of simultaneous perturbation stochastic approximation for nondifferentiable optimization, IEEE Transactions on Automatic Control 48 (2003) 1459-1463