An immigrants scheme based on environmental information for genetic algorithms in changing environments

2008 IEEE Congress on Evolutionary Computation, CEC 2008

Volumn , Issue , 2008, Pages 1141-1147

  Yu, Xin ^a   Tang, Ke ^a,b   Yao, Xin ^a  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b UNIVERSITY OF BIRMINGHAM   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BOOLEAN FUNCTIONS; DIESEL ENGINES; GENETIC ALGORITHMS;

CHALLENGING TASKS; CHANGING ENVIRONMENTS; COMPLEMENTATION; DESIGN DECISIONS; DYNAMIC OPTIMIZATION PROBLEMS; ENVIRONMENTAL INFORMATIONS; HYBRID SCHEMES; ON CURRENTS;

EVOLUTIONARY ALGORITHMS;

EID: 55749084033     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2008.4630940     Document Type: Conference Paper

References (15)

1. Y. Jin and J. Branke, "Evolutionary Optimization in Uncertain Environments: A Survey," IEEE Transactions on Evolutonary Computation, vol. 9, no, 3, pp. 303-317, 2005.
2. H. G. Cobb, "An Investigation into the Use of Hypermutation as An Adative Operator in Genetic Algorithms Having Continuous. Timedependent Nonstationary Environments," Naval Res. Lab., Washington, DC, Tech. Rep. AIC-90-001, 1990.
3. J. J. Grefenstette, "Genetic Algorithms for Changing Environments," Parallel Problem Solving from Nature, Elsevier Science Publishers, The Netherlands, vol. 2, pp. 137-144, 1992.
4. J. Branke, "Memory Enhanced Evolutionary Algorithms for Changing Optimization Problems," In Proceedings of the 1999 Congress on Evolutionary Computation, IEEE, vol. 3, pp. 1875-1882, 1999.
5. D. E. Goldberg and R. E. Smith, "Nonstationary Function Optimization Using Genetic Algorithms with Dominance and Diploidy," In Proceedings of the 2nd International Conference on Genetic Algorithms, Lawrence Erlbaum Associates, Mahwah, NJ, USA, pp. 59-68, 1987.
6. A. Ş. Uyar and A. E. Harmanci, "A New Population Based Adaptive Domination Change Mechanism for Diploid Genetic Algorithms in Dynamic Environments," Soft Computing, vol. 9. pp. 803-814, 2005.
7. D. Dasgupta and D. McGregor, "Nonstationary Function Optimization Using the Structured Genetic Algorithm," In Proceedings of the 2nd International Conference on Parallel Problem Solving from Nature, pp. 145-154, 1992.
8. S. Yang, "Non-stationary Problem Optimization Using the Primaldual Genetic Algorithm," In Proceedings of the 2003 Congress on Evolutionary Computation, vol. 3, pp. 2246-2253, 2003.
9. J. Branke, T. Kaußler, C. Schmidth, and H. Schmeck, "A Multipopulation Approach to Dynamic Optimization Problems." In Proceedings of the Adaptive Computing in Design and Manufacturing, pp. 299-308, 2000.
10. R. K. Ursem, "Multinational GAs: Multimodal Optimization Techniques in Dynamic Environments," In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 19-26, 2000.
11. S. Yang and X. Yao, "Experimental Study on Population-based Incremental Learning Algorithms for Dynamic Optimization Problems," Soft Computing, vol. 9, no. 11, pp. 815-834, 2005.
12. R. Tinós and S. Yang, "Genetic Algorithms with Self-Organized Criticality for Dynamic Optimization Problems," In Proceedings of the 2005 Congress on Evolutionary Computation, vol. 3, pp. 2816-2823, 2005.
13. S. Yang, "Memory-based Immigrants for Genetic Algorithms in Dynamic Environments," In Proceedings of the 2005 Genetic and Evolutionary Computation Conference, vol. 2, pp. 1115-1122, 2005.
14. S. Yang, "Genetic Algorithms with Elitism-based Immigrants for Changing Optimization Problems," Applications of Evolutionary Computing, Lecture Notes in Computer Science, Springer-Verlag, Berlin Heidelberg, vol. 4448, pp. 627-636, 2007.
15. S. Yang and R. Tinós, "A Hybrid Immigrants Scheme for Genetic Algorithms in Dynamic Environments," International Journal of Automation and Computing, vol. 4, no. 3, pp. 243-254, 2007