Global optimization using hybrid approach

WSEAS Transactions on Mathematics

Volumn 7, Issue 5, 2008, Pages 254-262

  Chen, Ting Yu ^a   Cheng, Yi Liang ^a  

^a NATIONAL CHUNG HSING UNIVERSITY   (Taiwan)

Author keywords

Evolution strategy; Global optimization algorithm; Hybrid approach

Indexed keywords

BIOELECTRIC PHENOMENA; EVOLUTIONARY ALGORITHMS; MATHEMATICAL PROGRAMMING; NONLINEAR PROGRAMMING; OPTIMIZATION; QUADRATIC PROGRAMMING; SOLUTIONS; TESTING;

EVOLUTION STRATEGY; EXACT SOLUTIONS; GLOBAL OPTIMIZATION ALGORITHM; GLOBAL OPTIMIZATION ALGORITHMS; GLOBAL SEARCH CAPABILITY; HYBRID APPROACH; HYBRID APPROACHES; MULTI-MODAL PROBLEMS; NEAR-OPTIMAL SOLUTIONS; SEQUENTIAL QUADRATIC PROGRAMMING; TEST PROBLEMS;

GLOBAL OPTIMIZATION;

EID: 48849112593     PISSN: 11092769     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (18)

1. Z. Tu and Y Lu, A robust stochastic genetic algorithm(StGA) for global numerical optimization, IEEE Transactions on Evolutionary Computation, Vol. 8, No. 5, 2004, pp. 456-470.
2. M. D. Toksari, Ant colony optimization for finding the global minimum, Applied Mathematics and Computation, vol. 176, 2006, pp. 308-316.
3. J.J. Liang, A.K. Qin, P.N. Suganthan and S. Baskar, Comprehensive learning particle swarm optimizer for global optimization of multimodal functions, IEEE transactions on Evolutionary Computation, Vol. 10, No. 3,2006, pp, 281-295.
4. Q. Zhang, J. Sun, E. Tsang and J, Ford, Hybrid estimation of distribution algorithm for global optimization, Engineering Computations, Vol. 21, No. 1, 2004, pp. 91-107.
5. Rechenberg, Evolutionsstrategie: Optimierung technisher systeme nach prinzipien der biologischen evolution, Frommann-Holzboog Verlag, Stuttgart, 1973.
6. H.-P. Schwefel, Numerical optimization of computer models, John Wiley & sons Ltd, Chichester, U.K, 1977.
7. H.C. Chen, Discrete and mixed-variable evolution strategy, Master's thesis, Department of Mechanical Engineering, National Chung Hsing University, Taiwan, 2006.
8. Z. Michalewicz, Genetic algorithms + Data structures = Evolution program, third edition, Springer-Verlag, 1996.
9. A. J. Keane, Experiences with optimizers in structural design, Proc. Conf. Adaptive Computing in Engineering Design and Control, 1994, pp. 14-27,
10. C.C. Lee, Reproducing kernel approximation method for structural optimization using genetic algorithms, Ph D dissertation, National Taiwan University, 2006.
11. J. Branke and C.Schmidt, Faster convergence by means of fitness estimation, Soft Computing, Vol. 9, 2005, pp. 13-20.
12. D. Buche, N.N. Schraudolph and P. Koumoutsakos, Accelerating evolutionary algorithms with Guassian process fitness function models, IEEE transactions on Systems, Man, and cybernetics-Part C: Applications and Reviews, Vol. 35, No. 2,2005, pp. 183-194.
13. C. A. Floudas and P. M. Pardalos, Recent advances in global optimization, Princetion Series in Computer Science, Princeton University Press, Princeton, NJ, 1992.
14. W. Hock and K. Schittkowsi, Test examples for nonlinear programming codes, Lecture Notes in Economics and Mathematical Systems, Vol. 187, Springer-Verlag, 1981.
15. D.M. Himmebleau, Applied nonlinear programming, McGraw-Hill, New York, 1972.
16. A. Homaifar, S.H.Y Lai and X. Qi, Constrained optimization via genetic algorithms, Simulation, Vol. 62, No. 4, 1994, pp. 242-254.
17. M. Gen and R. Cheng, A survey of penalty techniques in genetic algorithms, In Toshio Fukuda and Takeshi Furuhashi, editors, Proceedings of the 1996 International Conference on Evolutionary Computation IEEE, Nagoya, Japan, 1996, pp. 804-809.
18. C. A. C. Coello, Self-adaptive penalties for GA-based optimization, Evolutionary Computation, Vol. 1, 1999, pp. 573-580.