Population-based incremental learning for multiobjective optimisation

Advances in Soft Computing

Volumn 39, Issue , 2007, Pages 223-232

  Bureerat, Sujin ^a   Sriworamas, Krit ^a  

^a KHON KAEN UNIVERSITY   (Thailand)

Author keywords

Multiobjective evolutionary optimisation; Non dominated solutions; Pareto archive; Performance comparison; Population based incremental learning

Indexed keywords

EID: 40649122987     PISSN: 16153871     EISSN: 18600794     Source Type: Book Series    
DOI: 10.1007/978-3-540-70706-6_21     Document Type: Article

References (22)

1. Baluja S (1994) Population-based incremental learning: A method for integrating genetic search based function optimization and competitive learning. Technical Report CMU_CS_95_163, Carnegie Mellon University
2. Bureerat S, Cooper JE (1998) Evolutionary methods for the optimisation of engineering systems. In: IEE Colloquium Optimisation in Control: Methods and Applications, IEE, London, Uk, pp 1/1-1/10
3. Bureerat S, Limtragool J (2006) Performance enhancement of evolutionary search for structural topology optimization, Finite Element in Analysis and Design, 42:547-566
4. Coello CC, Romero CEM (2002) Evolutionary algorithms and multiple objective optimization. multicriteria optimization. Ehrgott, Matthias; Gandibleux, Xavier (Eds.), pp 277-331
5. Deb K, Pratap A, Meyarivan T: Constrained test problems for multi-objective evolutionary optimization. KanGAL Report No. 200002, Kanpur Genetic Algorithms Laboratory (Kan-GAL), Indian Institute of Technology, Kanpur, India.
6. Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGAII. IEEE Trans. On Evolutionary Computation 6(2):182-197
7. Fonseca CM, Fleming PJ (1993) Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization. In: Proc. of the 5th Inter. Conf. on Gas, pp 416-423
8. Fyfe C (1999) Structured population-based incremental learning. Soft Computing 2(4): 91-198
9. Grandhi RV, Bharatram, G (1993) Multiobjective optimization of large-scale structures. AIAA 31(7):1329-1337
10. Horn J, Nafpliotis N (1993) Multiobjective optimization using niched Pareto genetic algorithm. Tech. Report I11iGA1 Report 93005, UIUC
11. Horn J, Nafpliotis N, Goldberg DE (1994) A niched pareto genetic algorithm for multiobjective optimization. In: The 1st IEEE Conf. on Evolutionary Computation, pp 82-87
12. Ivvan S, Pena V, Rionda SB, Aguirre AH (2005) Multiobjective shape optimization using estimation distribution algorithms and correlated information. In: EMO2005, pp 664-676
13. Knowles JD, Corne DW (2000) Approximating the non-dominated front using the Pareto archive evolution strategy. Evolutionary Computation 8(2):149-172.
14. Kunakote T (2004) Topology optimization using evolutionary algorithms: comparison of the evolutionary methods and checkerboard suppression technique. Master thesis, Khon Kaen University
15. Messac A, Ismail-Yahaya A, Mattson CA (2003) The normalized normal constraint method for generating the Pareto frontier. Structural and Multidisciplinary Optimization 25(2):86-98
16. Schaffer JD (1985) Multiobjective optimization with vector evaluated genetic algorithms. In: GAs and their Application: Proc. of 1st Inter Conf. on Gas, pp 93-100
17. Sebag M, Ducoulombier A (1998) Extending population-based incremental learning to continuous search spaces. Lecture Notes in Computer Science 1498: 418
18. Srinivas N, Deb K (1994) Multiobjective optimization using non-dominated genetic algorithms. Evolutionary Computation 2(3):221-248
19. Yuan B, Gallagher M (2003) Playing in continuous spaces: Some analysis and extension of population-based incremental learning. In: Proceedings of the 2003 Congress on Evolutionary Computation, IEEE, Canberra, Australia, pp 443-450
20. Zitzler E, Deb K, Thiele L (2000) Comparison of multiobjective evolutionary algorithms: Empirical results. Evolutionary Computation 8(2):173-195
21. Zitzler E, Laumanns M, Thiele L (2002) SPEA2: Improving the strength Pareto evolutionary algorithm for multiobjective optimization. In: Evolutionary Methods for Design, Optimization and Control, Barcelona, Spain
22. Zitzler E, Thiele L, Laumanns M, Fonseca CM, Fonseca VG (2003) Performance assessment of multiobjective optimizers: An analysis and review. IEEE Trans. on Evolutionary Computation 7(2):117-132