Solving fluid flow problems using a real-coded genetic algorithm with uniform refinement

Advances in Fluid Mechanics

Volumn 40, Issue , 2004, Pages 63-72

  Bourisli, R ^a   Kaminski, D A ^a  

^a Department of Mechanical Engineering   (United States)

Author keywords

Contraction channel; Fluid flow; Genetic algorithm; Mutation; Numerical analysis; Population size; Potential flow; Real coded GA; Refinement

Indexed keywords

AERODYNAMICS; BOUNDARY VALUE PROBLEMS; CONSTRAINT THEORY; GENETIC ALGORITHMS; INVERSE PROBLEMS; NUMERICAL ANALYSIS; OPTIMIZATION; POPULATION STATISTICS; POTENTIAL FLOW; RANDOM PROCESSES;

CONTRACTION CHANNELS; MUTATION; POPULATION SIZE; REAL-CODED GA; REFINEMENT;

CHANNEL FLOW;

EID: 4644296373     PISSN: 1353808X     EISSN: None     Source Type: Book Series    
DOI: None     Document Type: Conference Paper

References (12)

1. Holland, J.H., Adaptation in Natural and Artificial Systems, University of Michigan Press: Ann Arbor, Michigan, 1975.
2. Jones, E.A & Joines, W.T., Genetic design of linear antenna arrays. IEEE Antenna and Propagation Magazine, 42(3), pp. 92-100, June 2000.
3. Fabri, G., A genetic algorithm for fin profile optimization. International Journal of Heat and Mass Transfer, 40(9), pp. 2165-2172, 1997.
4. Karr, C., Yakushinb, I. & Nicolosi, K., Solving inverse initial-value, boundary-value problems via genetic algorithm. Engineering Applications of Artificial Intelligence, 13, pp. 625-633, 2000.
5. Kim, H.-S. & Cho, S.-B., Application of interactive genetic algorithm to fashion design. Engineering Applications of Artificial Intelligence, 13, pp. 635-644, 2000.
6. Haupt, S.E. & Haupt, R.L., Optimizing complex systems. Proc. of the 1998 IEEE Aerospace Conference, Snowmass, Colorado, pp. 241-47, March 1998.
7. Milano, M. & Koumoutsakos, P., A clustering genetic algorithm for cylinder drag optimization. Journal of Computational Physics, 175, pp. 79107, 2002.
8. Davalos, R.V. & Rubinsky, B., An evolutionary-genetic approach to heat transfer analysis. Journal of Heat Transfer, Transactions of the ASME, 118(3), pp. 528-532, 1996.
9. Akin, S. & Demiral, B., Genetic algorithm for estimating multiphase flow functions from unsteady-state displacement experiments. Computers & Geosciences, 24(3), pp. 251-258, 1998.
10. Vuković, S. & Sopta, L., Binary-coded and real-coded genetic algorithm in pipeline flow optimization. Mathematical Comm., 4, pp. 35-42, 1999.
11. Fan, H-Y, Yam, R. & Dang, C., A preliminary study of the use of genetic algorithms in flowfield numerical analysis. Proceedings- Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 215(2), pp. 203-212, 2001.
12. Tate, D.M. & Smith, A.E., Expected allele coverage and the role of mutation in genetic algorithms, Proc. of the Fifth International Conference on Genetic Algorithms, Forrest, S. (Ed.), Morgan Kaufmann Publishers: San Mateo, CA, pp. 31-37, 1993.