Genetic algorithm design inspired by organizational theory: Pilot study of dependency structure matrix driven genetic algorithm

Intelligent Engineering Systems Through Artificial Neural Networks

Volumn 13, Issue , 2003, Pages 327-332

  Yu, Tian Li ^a   Goldberg, David E ^a   Yassine, Ali A ^a   Chen, Ying Ping ^a  

^a University of Illinois at Urbana Champaign   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BUILDING BLOCK (BB); DEPENDENCY STRUCTURE MATRIX (DSM); DEPENDENCY STRUCTURE MATRIX DRIVEN GENETIC ALGORITHM (DSMDGA); MINIMUM DESCRIPTION LENGTH (MDL); SIMPLE GENETIC ALGORITHM (SGA);

FUNCTIONS; GENETIC ALGORITHMS; MATHEMATICAL OPERATORS; MATRIX ALGEBRA; OPTICAL DESIGN; OPTIMIZATION; PERTURBATION TECHNIQUES;

IIR FILTERS;

EID: 2442538832     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (21)

1. Holland, J.H.: Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor, MI (1975)
2. Goldberg, D.E.: Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Reading, MA (1989)
3. Goldberg, D.E., Korb, B., Deb, K.: Messy genetic algorithms: Motivation, analysis, and first results. Complex Systems 3 (1989) 493-530
4. Goldberg, D.E., Deb, K., Kargupta, H., Harik, G.: Rapid, accurate optimization of difficult problems using fast messy genetic algorithms. Proceedings of the Fifth International Conference on Genetic Algorithms (1993) 56-64
5. Kargupta, H.: The performance of the gene expression messy genetic algorithm on real test functions. Proceedings of 1996 IEEE International Conference on Evolutionary Computation (1996) 631-636
6. Munetomo, M., Goldberg, D.E.: Identifying linkage groups by nonlinearity/non-monotonicity detection. Proceedings of the Genetic and Evolutionary Computation Conference 1999: Volume 1 (1999)433-440
7. Harik, G.R., Goldberg, D.E.: Learning linkage. Foundations of Genetic Algorithms 4 (1996) 247-262
8. Smith, J.: On appropriate adaptation levels for the learning of gene linkage. Journal of Genetic Programming and Evolvable Machines 3 (2002) 129-155
9. Bosman, P.A.N., Thierens, D.: Linkage information processing in distribution estimation algorithms. Proceedings of the Genetic and Evolutionary Computation Conference 1999: Volume 1 (1999) 60-67
10. Harik, G.: Linkage Learning via Probabilistic Modeling in the ECGA. IlliGAL Report No. 99010, University of Illinois at Urbana-Champaign, Urbana, IL (1999)
11. Pelikan, M., Goldberg, D.E., Cantú-Paz, E.: BOA: The Bayesian optimization algorithm. Proceedings of the Genetic and Evolutionary Computation Conference GECCO-99 I (1999) 525532
12. Steward, D.V.: The design structure system: A method for managing the design of complex systems. IEEE Transactions on Engineering Managment 28 (1981) 77-74
13. Yassine, A., Falkenburg, D.R., Chelst, K.: Engineering design management: An informatoin structure approach. International Journal of production research 37 (1999) 2957-2975
14. Femandez, C.: Integration Analysis of Product Architecture to Support Effective Team Colocation. Master thesis, Massachusetts Institute of Technology (1998)
15. Sharman, D., Yassine, A., Carlile, P.: Characterizing modular architectures. ASME 14th International Conference, DTM-34024 (2002)
16. Yu, T.L., Yassine, A., Goldberg, D.E.: A genetic algorithm for developing modular product architectures. Proceedings of the 15th international Conference on Design Theory and Methodology (DTM) (to appear)
17. Rethenberg, I.: Evolutions Strategie Optimierung technischer systeme nach prinzipien der biologischen evolution. Friedrich Frommann Verlag, Stuttgart-Bad Cannstatt (1973)
18. Mercer, R.E., Sampson, J.R.: Adaptive search using a reproductive meta-plan. Kybernetes 7 (1978) 215-228
19. Hartigen, J.A., Wong, M.A.: A k-means clustering algorithm. Applied Statistics 28 (1979) 10-108
20. Harik, G., Cantú-Paz, E., Goldberg, D.E., Miller, B.L.: The gambler's ruin problem, genetic algorithms, and the sizing of populations. Proceedings of 1997 IEEE International Conference on Evolutionary Computation (1997) 7-12
21. Miller, B.L.: Noise, sampling, and efficient genetic algorithms. Doctoral dissertation, University of Illinois at Urbana-Champaign, Urbana (1997)