A computational intelligence approach to optimization with unknown objective functions

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2130, Issue , 2001, Pages 73-80

  Nakayama, Hirotaka ^a   Arakawa, Masao ^b   Sasaki, Rie ^a  

^a KONAN UNIVERSITY   (Japan)

^b KAGAWA UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; GENETIC ALGORITHMS; NEURAL NETWORKS; NUMERICAL METHODS; THERMOANALYSIS;

DESIGN VARIABLES; NOT GIVEN; OBJECTIVE FUNCTIONS; OPTIMAL VALUES; PRACTICAL ENGINEERING; RADIAL BASIS FUNCTION NETWORKS (RBFN); THERMO DYNAMIC ANALYSIS; VALUE OF DESIGNS;

RADIAL BASIS FUNCTION NETWORKS;

EID: 0038281818     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44668-0_11     Document Type: Conference Paper

References (10)

1. Arakawa, M. and Hagiwara, I. (1997), Nonlinear Integer, Discrete and Continuous Optimization Using Adaptive Range Genetic Algorithms, Proc. of ASME Design Technical Conferences (in CD-ROM)
2. Haykin, S. (1994), Neural Networks:A Comprehensive Foundation, Macmillan College Publishing Company
3. Hsu, Y.H., Sun, T.L. and Leu, L.H. (1995), A Two-stage Sequential Approximation Method for Nonlinear Discrete Variable Optimization, ASME Design Engineering Technical Conference, Boston, MA, 197-202
4. Kannan, B.K. and Kramer, S.N. (1994), An Augmented Lagrange Multiplier Based Method for Mixed Integer Discrete Continuous Optimization and Its Appliations to Mechanical Design, Transactions of ASME, J. of Mechanical Design, Vol. 116, 405-411
5. Myers, R.H. and Montgomery D.C. (1995), Response Surface Methodology:Process and Product Optimization using Designed Experiments, Wiley
6. Nakayama, H., Yanagiuchi, S., Furukawa, K., Araki, Y., Suzuki, S. and Nakata, M. (1998), Additional Learning and Forgetting by RBF Networks and its Application to Design of Support Structures in Tunnel Construction Proc. International ICSC/IFAC Symposium on Neural Computation (NC’98), 544-550
7. Orr, M.J.L. (1996), Introduction to Radial Basis Function Networks, http://www.cns.ed.ac.uk/people/mark.html
8. Qian, Z., Yu, J. and Zhou, J. (1993), A Genetic Algorithm for Solving Mixed Discrete optimization Problems, DE-Vol. 65-1, Advances in Design Automation, Vol. 1, 499-503
9. Sandgren, E. (1990), Nonlinear Integer and Discrete Programming in Mechanical Engineering Systems, J. of Mechanical Design, Vol. 112, 223-229
10. Zhang, C. and Wang, H.P. (1993), Mixed-Discrete nonlinear Optimization with Simulated Annealing, Engineering Optimization, Vol. 21, 277-291