A novel weight design in multi-objective evolutionary algorithm

Proceedings - 2010 International Conference on Computational Intelligence and Security, CIS 2010

Volumn , Issue , 2010, Pages 137-141

  Gu, Fang Qing ^a   Liu, Hai Lin ^a  

^a GUANGDONG UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Evolutionary algorithm; Linear interpolation; Multi objective optimization; Uniformly distribution

Indexed keywords

LINEAR INTERPOLATION; MULTI OBJECTIVE; MULTI OBJECTIVE EVOLUTIONARY ALGORITHMS; PARETO FRONT; PARETO OPTIMAL SOLUTIONS; TEST FUNCTIONS; TEST INSTANCES; UNIFORMLY DISTRIBUTION; WEIGHT DESIGN;

ARTIFICIAL INTELLIGENCE; INTERPOLATION; MULTIOBJECTIVE OPTIMIZATION; NUMERICAL CONTROL SYSTEMS;

EVOLUTIONARY ALGORITHMS;

EID: 79951647729     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIS.2010.37     Document Type: Conference Paper

References (16)

1. K. Deb, "Multi-objective optimization using evolutionary algorithms", New York, Wiley, 2001.
2. C. A. C. Coello, D. A. V. Veldhuizen, and G.B.Lamont, "Evolutionary algorithms for solving multi-objective problems", Norwell, MA,Kluwer, 2002.
3. H-L. Liu, Y. Wang and Y-M. Cheung. A multiobjective evolutionary algorithm using min-max strategy and sphere coordinate transformation. Intelligent automation and soft computing, 2009, vol.15, pp.361-384.
4. H. Ishibuchi and T. Murata, "Multi-objective local search algorithm and its application to flowshop scheduling," IEEE Trans. Man, Cybern., vol. 28, pp. 392-403, Aug. 1998.
5. A. Jaszkiewicz, "On the performance of multiple-objective genetic local search on the 0/1 knapsack problem-A comparative experiment," IEEE Trans. Evol. Comput., vol. 6, no. 4, pp. 402-412, Aug. 2002.
6. H-L. Liu and X. Li, "The multiobjective evolutionary algorithm based on determined weight and sub-regional search" 2009 IEEE Congress on Evolutionary Computation, Norway, 18-21 May 2009 pp.1928-1934.
7. Y. Leung and Y. Wang, "Multiobjective programming using uniform design and genetic algorithm", IEEE Transactions on SMC, Part C, vol. 30, no. 3, pp. 293-304, Aug. 2000.
8. E. Zitzler and L. Thiele, "Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto Approach", IEEE Trans. Evol. Comput., vol. 3, no. 4, pp. 257-271, Nov. 1999.
9. E. Zitzler, M. Laumanns and L. Thiele, "SPEA2: improving the strength Pareto evolutionary algorithm", Technical Report: TIK-Report 103, Dept. of Electrical Engineering, Swiss Federal Institute of Technology, Zurich, Switzerland, May 2001.
10. K. Deb, A. Pratap, S. Agarwal and T. Meyarivan, "A fast and elitist multiobjective genetic algorithm: NSGA-II", IEEE Trans. Evol. Comput., vol. 6, no. 2, pp. 182-197, Apr. 2002.
11. Q. Zhang and H. Li, "MOEA/D: A multi-objective evolutionary algorithm based on decomposition", IEEE Trans. Evol. Comput., vol. 11, no. 6, pp. 712-731, Dec. 2007.
12. H. Li and Q. Zhang, "Multiobjective optimization problems with complicated Pareto Sets, MOEA/D and NSGA-II", IEEE Trans. Evol. Comput., vol. 12, no. 2, pp. 284-302, Apr. 2009.
13. C. A. C. Coello, G.T. Pulido, M.S. Lechuga, "Handling multiple objectives with particle swarm optimization", IEEE Trans. Evol. Comput., vol. 8, no. 3, pp. 256-279, Jun. 2004.
14. J. D. Knowles and D. W. Corne, "The Pareto archived evolution strategy: A new baseline algorithm for multiobjective optimization," in Proc. Congr. Evol. Comput., Washington, D.C., Jul. 1999. pp. 8-105.
15. S. Huband, P. Hingston, L. Barone and L. While, "A review of multiobjective test problems and a scalable test problem toolkit", IEEE Trans. Evol. Comput., vol. 10, no.5, pp. 477-506, Oct. 2006.
16. E. Zitzler, L. Thiele, M. Laumanns, C. M. Fonseca, and V. G. da Fonseca, "Performance assessment of multiobjective optimizers: an analysis and review." IEEE Trans. Evol. Comput., vol. 7, no. 2, pp. 117-132, Apr. 2003.