Approximate models for constraint functions in evolutionary constrained optimization

International Journal of Innovative Computing, Information and Control

Volumn 7, Issue 11, 2011, Pages 6585-6603

  Oh, Sanghoun ^a   Jin, Yaochu ^b   Jeon, Moongu ^a  

^a Gwangju Institute of Science and Technology (GIST)   (South Korea)

^b UNIVERSITY OF SURREY   (United Kingdom)

Author keywords

Approximate constraints; Evolution strategy; Genetic programming; Stochastic ranking selection; Synthesized constraints

Indexed keywords

APPROXIMATE CONSTRAINTS; APPROXIMATE MODEL; APPROXIMATION APPROACH; BENCH-MARK PROBLEMS; CONSTRAINED EVOLUTIONARY OPTIMIZATION; CONSTRAINED OPTIMIZATION PROBLEMS; CONSTRAINT FUNCTIONS; CONSTRAINT HANDLING; CONSTRAINT-HANDLING TECHNIQUES; ENGINEERING DESIGN OPTIMIZATION; ENGINEERING OPTIMIZATION PROBLEMS; ENGINEERING PROBLEMS; EVOLUTION STRATEGIES; FEASIBLE REGIONS; GLOBAL OPTIMUM; OPTIMAL SOLUTIONS; SEARCH SPACES; SIMULATION RESULT; STATE-OF-THE-ART ALGORITHMS; STOCHASTIC RANKING; SYNTHESIZED CONSTRAINTS; TEST PROBLEM;

BIOLOGY; CASCADES (FLUID MECHANICS); CONSTRAINED OPTIMIZATION; GENETIC PROGRAMMING; MODELS;

EVOLUTIONARY ALGORITHMS;

EID: 80054835892     PISSN: 13494198     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (34)

1. Y. Guo, X. Cao and J. Zhang, Constraint handling based multiobjective evolutionary algorithm for aircraft landing scheduling, International Journal of Innovative Computing, Information and Control, vol.5, no.8, pp.2229-2238, 2009.
2. T. Uno, H. Katagiri and K. Kato, An evolutionary multi-agent based search method for stackel-berg solutions of bilevel facility location problems, International Journal of Innovative Computing, Information and Control, vol.4, no.5, pp.1033-1042, 2008.
3. C. Liu, An evolutionary algorithm for solving dynamic nonlinear constrained optimization, ICIC Express Letters, vol.4, no.3, pp. 1039-1044, 2010.
4. Z. Michalewicz and M. Schoenauer, Evolutionary algorithms for constrained parameter optimization problems, Evolutionary Computation, vol.4, no.l, pp. 1-32, 1996.
5. C. A. C. Coello, Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: A survey of the state of the art, Computer Methods in Applied Mechanics and Engineering, vol.191, no.11-12, pp.1245-1287, 2002.
6. T. Runarsson and X. Yao, Stochastic ranking for constrained evolutionary optimization, IEEE Transactions on Evolutionary Computation, vol.4, no.3, pp.284-294, 2000.
7. C. A. C. Coello and E. M. Montes, Constraint-handling in genetic algorithms through the use of dominance-based tournament selection, Advanced Engineering Informatics, vol.16, no.3, pp. 193-203, 2002.
8. J. Horn, N. Nafpliotis and D. E. Goldberg, A niched pareto genetic algorithm for multiobjective optimization, Proc. of the 1st IEEE Conf. on Evolutionary Computation, IEEE World Congress on Computational Intelligence, Orlando, FL, pp.82-87, 1994.
9. E. M. Montes and C. A. C. Coello, A simple multimembered evolution strategy to solve constrained optimization problems, IEEE Transactions on Evolutionary Computation, vol.9, no.l, pp.1-17, 2005.
10. L. D. Davis, Handbook of Genetic Algorithms, Van Nostrand Reinhold, New York, 1991.
11. J. Bean, Genetic algorithms and random keys for sequencing and optimization, ORSA Journal on Computing, vol.6, pp.154-160, 1994.
12. Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs, Springer-Verlag, Berlin Heidelberg, New York, 1996.
13. R. Kowalczyk, Constraint consistent genetic algorithms, Proc. of IEEE International Conference on Evolutionary Computation, Indianapolis, pp.343-348, 1997.
14. F. Glover and G. A. Kochenberger, Critical event tabu search for multidimensional knapsack problems, in Meta Heuristics: Theory and Applications, I. H. Osman and J. P. Kelly (eds.), Dordrecht, Kluwer Academic Publishers, 1996.
15. S. Koziel and Z. Michalewicz, Evolutionary algorithms, homomorphous mappings, and constrained parameter optimization, Evolutionary Computation, vol.7, no.l, pp.19-44, 1999.
16. H. Adeli and N.-T. Cheng, Augmented lagrangian genetic algorithm for structural optimization, Journal of Aerospace Engineering, vol.7, no.l, pp.104-118, 1994.
17. S. V. Belur, Core: Constrained optimization by random evolution, Late Breaking Papers at the Genetic Programming 1997 Conference, Stanford University California, pp.280-286, 1997.
18. T. V. Le, A fuzzy evolutionary approach to constrained optimization problems, Proc. of IEEE International Conference on Evolutionary Computation, Nagoya, Japan, pp.274-278, 1996.
19. R. E. Smith, S. Forrest and A. S. Perelson, Searching for diverse, cooperative populations with genetic algorithms, Evolutionary Computation, vol.1, no.2, pp.127-149, 1993.
20. R. G. Reynolds, An introduction to cultural algorithms, Proc. of the 3rd Annual Conference on Evolutionary Programming, pp. 131-139, 1994.
21. X. Zhang, Q. Lu and S. Wen, A modified differential evolution for constrained optimization, ICIC Express Letters, vol.2, no.2, pp. 181-186, 2008.
22. M. Dorigo and L. M. Gambardella, Ant colony system: A cooperative learning approach to the traveling salesman problem, IEEE Transactions on Evolutionary Computation, vol.1, no.l, pp.5366, 1997.
23. Y. Jin, S. Oh and M. Jeon, Incremental approximation of nonlinear constraints functions for evolutionary constrained optimization, Proc. of IEEE Conference on Evolutionary Computation, Barcelona, Spain, pp. 1-8, 2010.
24. S. Hamida and M. Schoenauer, Aschea: New results using adaptive segregational constraint handling, Proc. of IEEE Conference on Evolutionary Computation, Honolulu, HI, pp.82-87, 2002.
25. Y. Jin and J. Branke, Evolutionary optimization in uncertain environments - A survey, IEEE Transactions on Evolutionary Computation, vol.9, no.3, pp.303-317, 2005.
26. S. Oh, S. Lee and M. Jeon, Evolutionary optimization programming with probabilistic models, Proc. of the 4th International Conference on Bio-Inspired Computing, Beijing, China, pp.1-6, 2009.
27. J. J. Liang, T. P. Runarsson, E. Mezura-Montes, M. Clerc, P. N. Suganthan, C. A. C. Coello and K. Deb, Problem definitions and evaluation criteria for the CEC 2006 special session on constrained real-parameter optimization, Technical Report, Nanyang Technological University, Singapore, 2006.
28. R. Farmani and J. Wright, Self-adaptive fitness formulation for constrained optimization, IEEE Transactions on Evolutionary Computation, vol.7, no.5, pp.445-455, 2005.
29. Y. Wang, Z. Cai, Y. Zhou and W. Zeng, An adaptive tradeoff model for constrained evolutionary-optimization, IEEE Transactions on Evolutionary Computation, vol.12, no.l, pp.80-92, 2008.
30. C. A. C. Coello, Use of a self-adaptive penalty approach for engineering optimization problems, Computers in Industry, vol.41, no.2, pp.113-127, 2000.
31. X. Hu, R. C. Eberhart and Y. Shi, Engineering optimization with particle swarm, Proc. of the IEEE Swarm Intelligence Symposium, Indianapolis, IN, pp.53-57, 2003.
32. Q. He and L. Wang, An effective co-evolutionary particle swarm optimization for constrained engineering design problems, Engineering Applications of Artificial Intelligence, vol.20, no.l, pp.89-99, 2007.
33. Q. He and L. Wang, A hybrid particle swarm optimization with a feasibility-based rule for constrained optimization, Applied Mathematics and Computation, vol.186, no.2, pp. 1407-1422, 2007.
34. E. Zahara and Y. T. Kao, Hybrid neldermead simplex search and particle swarm optimization for constrained engineering design problem, Expert systems with application vol; 36, no, 2 pp-3880-3886, 2009