A genetic algorithm and fuzzy approach (GAFA) for constrained nonlinear optimization in design

International Journal for Computational Methods in Engineering Science and Mechanics

Volumn 7, Issue 3, 2006, Pages 173-189

  Bhuvaneshwaran, Vijayakumar ^a   Langari, Reza ^a   Temponi, Cecilia ^b  

^a Texas A and M University   (United States)

^b TEXAS STATE UNIVERSITY   (United States)

Author keywords

Constrained Nonlinear Optimization; Engineering Design; Fuzzy Logic; Genetic Algorithm; Pareto optimality

Indexed keywords

APPROXIMATION THEORY; CONSTRAINT THEORY; NONLINEAR CONTROL SYSTEMS; OPTIMIZATION; PARETO PRINCIPLE;

COMPUTATIONAL EFFICIENCY; CONSTRAINED NONLINEAR OPTIMIZATION; ENGINEERING DESIGN; PARETO-OPTIMALITY;

GENETIC ALGORITHMS;

EID: 33645720809     PISSN: 15502287     EISSN: 15502295     Source Type: Journal    
DOI: 10.1080/15502280500388060     Document Type: Article

References (22)

1. Andrei, N., Advanced Mathematical Programming - Theory, Computational Methods, Applications, ICI Publishing House (1999).
2. Antonsson, E. K., and Otto, K. N., "Improving engineering design with fuzzy sets," http://design.mit.edu, January 10, 1995.
3. Coello, C. A., and Coello, C. A., "Treating constraints as objectives for single-objective evolutionary optimization," Engineering Optimization, 32(3), 275-308 (2000).
4. Coello, C. A., Coello, C. A., and Christiansen, A. D., "MOSES: A multi-objective optimization tool for engineering design," Engineering Optimization, 31(3), 337-368 (1999).
5. Coello, C. A., Christiansen, A. D., and Aguirre, A. H., "Using a new GA-based multi-objective optimization technique for the design of robot arms," Robotica, 16 (4), 401-414 (1998).
6. Deb, K., Multi-objective Optimization Using Evolutionary Algorithms, Wiley, Chichester (2001).
7. Yuan, W. G., and Quan, W. W., "Fuzzy optimum design of structures," Engineering Optimization, 8, 291-300 (1985).
8. Rao, S. S., "Multi-objective optimization of fuzzy structural systems," International Journal for Numerical Methods in Engineering, 24, 1157-1171 (1987).
9. Fonseca, C. M., and Fleming, P. J., "Multi-objective optimization and multiple constraint handling with evolutionary algorithms - Part II: Application example," IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 28(1), 38-47 (1998).
10. Gen, M., and Cheng, R., Genetic Algorithms and Engineering Design, John Wiley & Sons, New York, (1997).
11. Gill, P. E., and Murray, W., Numerical Methods for Constrained Optimization, Academic Press, New York, (1974).
12. Goldberg, D. E., Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley. Reading, Mass. (1989).
13. Haug, E. J., and Arora, J. S., Applied Optimal Design, John Wiley & Sons, (1979).
14. Herrera, F., Lozano, M., and Verdegay, J. L., "Tackling real-coded genetic algorithms: Operators and tools for behavioral analysis," Artificial Intelligence Review, 12, 265-319 (1998).
15. Homaifar, A., Lai, S. H. Y., and Qi, X., "Constrained optimization via genetic algorithms," Simulation, 62(4), 242-251 (1994).
16. Koza, J. R., Genetic Programming. On the Programming of Computers by Means of Natural Selection, The MIT Press, Boston (1992).
17. Pezeshk, S., Camp, C. V., and Chen, D., "Design of non-linear framed structures using genetic optimization," Journal of Structural Engineering, 382-388 (2000).
18. Sarma, K. C., and Adeli, H., "Fuzzy genetic algorithm for optimization of steel structures," Journal of Structural Engineering, 596-604 (2000).
19. Schaffer, J. D., Multiple Objective Optimization with Vector Evaluated Genetic Algorithm, Ph.D. thesis, Vanderbilt University, (1984).
20. Schnecke, V., and Vornberger, O., "Genetic design of VLSI-layouts," First IEE/IEEE International Conference GA's in Engineering Systems: Innovations and Application, 430-435, (1995).
21. Van Veldhuizen, D. A., and Lamont, G. B., "Evolutionary computation and convergence to a pareto front," Late Breaking Papers at the Genetic Programming Conference (1998).
22. Hsiao, F. -H., Chiang, W. -L., and Chen, C. -W., "Fuzzy control for nonlinear systems via neural-network-based approach," Int. J. Comp. Meth. Engng Sci. Mech., 6(3), 145-152 (2005).