Compact Genetic Algorithms using belief vectors

Applied Soft Computing Journal

Volumn 11, Issue 4, 2011, Pages 3385-3401

  Lee, Joon Yong ^a   Kim, Min Soeng ^b   Lee, Ju Jang ^a  

^a Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

^b SK Telecom   (South Korea)

Author keywords

Belief vectors (BVs); Compact Genetic Algorithms (cGAs); Entropy; Genetic diversity

Indexed keywords

ADDITIONAL CONTROL; BELIEF VECTORS (BVS); COMPACT GENETIC ALGORITHM; COMPACT GENETIC ALGORITHMS (CGAS); CONTROL PARAMETERS; CONVERGENCE SPEED; CROSSOVER AND MUTATION; FAST CONVERGENCE; GENETIC DIVERSITY; GENETIC OPERATORS; LOW QUALITIES; MEMORY REQUIREMENTS; PARAMETER CONTROL; PARAMETER-TUNING; PREMATURE CONVERGENCE; PROBABILITY VECTOR; QUALITY OF SOLUTION;

BIODIVERSITY; ENTROPY; GENETIC ALGORITHMS; MATHEMATICAL OPERATORS; PROBABILISTIC LOGICS; PROBABILITY DISTRIBUTIONS; VECTORS;

CONVERGENCE OF NUMERICAL METHODS;

EID: 79954617714     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2011.01.010     Document Type: Article

References (24)

1. G.R. Harik, F.G. Lobo, and D.E. Goldberg The compact genetic algorithm IEEE Transactions on Evolutionary Computation 3 4 1999 287 297
2. C.W. Ahn, K.P. Kim, and R.S. Ramakrishna A memory-efficient elitist genetic algorithm Lecture Notes in Computer Science 2004 552 559
3. J.C. Gallagher, S. Vigraham, and G. Kramer A family of compact genetic algorithms for intrinsic evolvable hardware IEEE Transactions on Evolutionary Computation 8 2 2004 367 385
4. J.I. Hidalgo, J. Lanchares, A. Ibarra, and R. Hermida A hybrid evolutionary algorithm for multi-FPGA systems design Euromicro Symp. on Digital System Design (DSD) Dortmund, Germany 2002 60 67
5. J.I. Hidalgo, M. Prieto, J. Lanchares, R. Baraglia, F. Tirado, and O. Garnica Hybrid parallelization of a compact genetic algorithm Proceedings. 11th Euromicro Conference on Parallel, Distributed and Network-Based Processing Genova, Italy 2003 449 455
6. R. Baraglia, J.I. Hidalgo, and R. Perego A hybrid heuristic for the traveling salesman problem IEEE Transactions on Evolutionary Computation 5 6 2001 613 622 (Pubitemid 34091919)
7. E. Mininno, F. Cupertino, and D. Naso Real-valued compact genetic algorithms for embedded microcontroller optimization IEEE Transactions on Evolutionary Computation 12 2 2008 203 219 doi:10.1109/TEVC.2007.896689 (Pubitemid 351546695)
8. M.H. Jin, W.Z. Liu, D.F. Hsu, and C.Y. Kao Compact genetic algorithm for performance improvement in hierarchical sensor networks management ISPAN '05: Proceedings of the 8th International Symposium on Parallel Architectures, Algorithms and Networks Las Vegas, USA 2005 406 413
9. C.W. Ahn, and R.S. Ramakrishna Elitism-based compact genetic algorithms IEEE Transactions on Evolutionary Computation 7 4 2003 367 385
10. C. Zhou, K. Meng, and Z. Qiu Compact genetic algorithm mutated by bit Proceedings of the 4th World Congress on Intelligent Control and Automation Shanghai, China 2002 1836 1839
11. J.Y. Lee, S.M. Im, and J.J. Lee Bayesian network-based non-parametric compact genetic algorithm INDIN 2008. 6th IEEE International Conference on Industrial Informatics 2008 359 364
12. G.R. Harik, Linkage learning via probabilistic modeling in the ecga, IlliGAL Report No. 99010, 1999.
13. C.W. Ahn, and R.S. Ramakrishna Augmented compact genetic algorithm Lecture Notes in Computer Science 3019 2004 560 565
14. S. Rimcharoen, D. Sutivong, and P. Chongstitvatana Updating strategy in compact genetic algorithm using moving average approach in:2006 IEEE Conference on Cybernetics and Intelligent Systems (CIS2006) Bangkok, Thailand 2006 1 6
15. A. Ekart, and S. Nemeth Maintaining the diversity of genetic programs Proceedings of the 5th European Conference on Genetic Programming London, UK 2002 162 171
16. S. Rudlof, and M. Koppen Stochastic hill climbing with learning by vectors of normal distributions The first Online Workshop on Soft Computing Nagoya, Japan 1996
17. M. Pelikan, Hierarchical Bayesian Optimization Algorithm 2005 Springer Berlin Heidelberg/St. Louis, USA
18. J.P. Rosca Entropy-driven adaptive representation Workshop Genetic Programming: From Theory to Real-World Applications Tahoe City, CA 1995 23 32
19. D. Chen, and C. Zhao Particle swarm optimization with adaptive population size and its application Applied Soft Computing 9 1 2009 39 48 doi:10.1016/j.asoc.2008.03.001
20. W.H. Press, S.A. Teukolsky, W.T. Vetterling, B.P. Flannery, Numerical Recipes in C++: The Art of Scientific Computing 2nd ed. February 2002 Cambridge University Press
21. S.-H. Liu, M. Mernik, and B.R. Bryant Entropy-driven parameter control for evolutionary algorithms Informatica 31 1 2007 41 50 (Pubitemid 46683736)
22. H. Pohlheim, Geatbx: Example functions (single and multi-objective functions) 2 parametric optimization (October, 2006). http://www.geatbx.com/ docu/fcnindex-01.html.
23. D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning 1989 Addison-Wesley
24. J. Gibbons, and S. Chakraborti Nonparametric Statistical Inference 2003 CRC