An empirical comparison of three novel genetic algorithms

Engineering Computations (Swansea, Wales)

Volumn 17, Issue 8, 2000, Pages 981-1001

  Fan, Hui Yuan ^a   Lu, Jane Wei Zhen ^b   Xu, Zong Ben ^a  

^a XI'AN JIAOTONG UNIVERSITY   (China)

^b CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Genetic algorithms; Performance measurement; Strategy

Indexed keywords

BENCHMARKING; COMPUTER SIMULATION; FUNCTIONS; INTEGRAL EQUATIONS; OPTIMIZATION; PERFORMANCE; PROBABILITY DISTRIBUTIONS; ROBUSTNESS (CONTROL SYSTEMS); STRATEGIC PLANNING;

ARTIFICIAL TEST FUNCTIONS; GRADIENT-BASED METHODS; PERFORMANCE EVALUATION; STRATEGY;

GENETIC ALGORITHMS;

EID: 2442488198     PISSN: 02644401     EISSN: None     Source Type: Journal    
DOI: 10.1108/02644400010360901     Document Type: Article

References (14)

1. Back, T. (1996), Evolutionary Algorithms in Theory and Practice, Oxford University Press, Oxford.
2. Bramlette, M.F. (1991), "Initialization, mutation and selection methods in genetic algorithms for function optimization", Proceedings of the Fourth International Conference on Genetic Algorithms, Morgan Kaufmann, Los Altos, CA, pp. 100-7.
3. Davalos, R.V. and Pubinsky, B. (1996), "An evolutionary-genetic approach to heat transfer analysis", Trans. ASME J. Heat Transfer, Vol. 118, August, pp. 528-31.
4. Davis, L. (1990), Handbook of Genetic Algorithms, Van Nostrand Reinhold, New York, NY.
5. De Jong, K.A. (1975), "An analysis of the behavior of a class of genetic systems", doctoral thesis, Department of Computer and Comunication Science, University of Michigan, Ann Arbor, MI.
6. Fan, H.-Y. (2000), "Study of evolutionary-computation-based methods applied for design of stationary circular cascades in centrifugal compressors", PhD thesis, Xi'an Jiaotong University, Xi'an.
7. Fan, H.-Y., Xi, G. and Wang, S.J. (2000), "A dual fitness function genetic algorithm and application in aerodynamic inverse design", Inverse Problem in Enginering, Vol. 8 No. 4, in press.
8. Goldberg, D.E. (1989), Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, MA.
9. Greenwell, R.N., Angus, J.E. and Finck, M. (1995), "Optimal mutation probability for genetic algorithms", Mathl Comput. Modeling, Vol. 21 No. 8, pp. 1-11.
10. Holland, J H. (1975), Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, MI.
11. Schaffer, J.D., Garura, R.A., Eshelman, L.J. and Das, R. (1989), "A study of control parameters affecting on line performance of genetic algorithms for function optimization", Proceedings of the Third International Conference on Genetic Algorithms, Morgan Kaufmann, Los Altos, CA, pp. 51-60.
12. Schwefel, H.P. (1998), "Evolutionary learning optimum-seeking on parallel computer architectures", Proceedings of the International Symposium on Systems Analysis and Simulation 1998, 1: Theory and Fundations, Akademic-Verlag, Berlin, pp. 217-25.
13. Soremekun, G. (1996), "Improving genetic algorithm efficiency and reliability in the design and optimization of composite structures", AIAA Paper-96-4024-cp.
14. Yamamoto, K. and Inoue, O. (1995), "New evolutionary direction operator for genetic algorithms", AIAA Journal, Vol. 33 No. 10, pp. 1990-3.