A new fitness evaluation method based on fuzzy logic in multiobjective evolutionary algorithms

2012 IEEE Congress on Evolutionary Computation, CEC 2012

Volumn , Issue , 2012, Pages

  He, Zhenan ^a   Yen, Gary G ^a  

^a OKLAHOMA STATE UNIVERSITY   (United States)

Author keywords

fuzzy logic; multiobjective evolutionary algorithm; NSGA II; Pareto optimality

Indexed keywords

FAST CONVERGENCE; FITNESS EVALUATIONS; FUZZY CONCEPT; MULTI OBJECTIVE EVOLUTIONARY ALGORITHMS; MULTI-OBJECTIVE OPTIMIZATION PROBLEM; NSGA-II; OPTIMALITY; OPTIMIZATION PROBLEMS; PARETO DOMINANCE; PARETO-OPTIMALITY; SELECTION PRESSURES;

EVOLUTIONARY ALGORITHMS; FUZZY LOGIC; MULTIOBJECTIVE OPTIMIZATION; PROBLEM SOLVING;

PARETO PRINCIPLE;

EID: 84866881796     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2012.6256534     Document Type: Conference Paper

References (23)

1. H. Ishibuchi, N. Tsukamoto, and Y. Nojima, "Evolutionary many-objective optimization: a short review," in Proceedings of IEEE Congress on Evolutionary Computation, Hong Kong, China, pp. 2424-2431, 2008.
2. K. Deb, L. Thiele, M. Laumanns, and E. Zitzler, "Scalable multiobjective optimization test problems," in Proceedings of IEEE Congress on Evolutionary Computation, Honolulu, HI, pp. 825-830, 2002.
3. D. Brockhoff and E. Zitzler, "Objective reduction in evolutionary multiobjective optimization: theory and applications," Evolutionary Computation, vol. 17, pp. 135-166, 2009.
4. K. Deb and D. Saxena, "On finding Pareto-optimal solutions through dimensionality reduction for certain largedimensional multi-objective optimization problems," Technical Report KanGAL No. 2005011, 2005.
5. H. Singh, A. Isaacs, and T. Ray, "A Pareto corner search evolutionary algorithm and dimensionality reduction in many-objective optimization problems," IEEE Transactions on Evolutionary Computation, vol. 15, pp.539-556, 2011.
6. L. Ben Said, S. Bechikh, and K. Ghedira, "The r-dominance: a new dominance relation for interactive evolutionary multicriteria decision making," IEEE Transactions on Evolutionary Computation, vol. 14, pp.801-818, 2010.
7. J. Yen and R. Langari, Fuzzy Logic: Intelligence, Control, and Information, Prentice-Hall: Upper Saddle River, NJ, 1998.
8. K. Deb, A. Pratab, S. Agrawal, and T. Meyarivan, "A fast and elitist multiobjective genetic algorithm: NSGA-II," IEEE Transactions on Evolutionary Computation, vol. 6, pp. 182-197, 2002.
9. M. Garza-Fabre, G. Toscano Pulido, and C. Coello Coello, "Ranking methods for many-objective optimization," in Proceedings of the 8th Mexican International Conference on Artificial Intelligence, Guanajuato, México, pp. 633-645, 2009.
10. M. Garza-Fabre, G.T. Pulido, and C.A. Coello Coello, "Alternative fitness assignment methods for many-objective optimization problems," in Proceedings of Artificial Evolution Conference, Strasbourg, France, pp. 146-157, 2009.
11. E. Hughes, "Fitness assignment methods for many-objective problems," in J. Knowles, D. Corne, and K. Deb, editors, Multi-Objective Problem Solving from Nature: From Concepts to Applications, Springer: Germany, pp. 307-329, Berlin, 2008.
12. L. Batista, F. Campelo, F. Guimaraes, and J. Ramirez, "A comparison of dominance criteria in many-objective optimization problems," in Proceedings of IEEE Congress on Evolutionary Computation, Barcelona, Spain, pp. 2359-2366, 2011.
13. E. Zitzler and S. Kunzli, "Indicator-based selection in multiobjective search," in Proceedings of International Conference on Parallel Problem Solving from Nature, Birmingham, UK, pp. 832-842, 2004.
14. M. Farina and P. Amato. "A fuzzy definition of 'optimality' for many-criteria optimization problems," IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, vol. 34, pp. 315-326, 2004.
15. M. Nasir, A. Mondal, S. Sengupta, S. Das, and A. Abraham, "An improved multiobjective evolutionary algorithm based on decomposition with fuzzy dominance," in Proceedings of IEEE Congress on Evolutionary Computation, New Orleans, LA, pp.765-772, 2011.
16. M. Köppen, R. Garcia, and B. Nickolay, "Fuzzy-Pareto-dominance and its application in evolutionary multi-objective optimization," in Proceedings of the International Conference on Evolutionary Multi-Criterion Optimization, Guanajuato, Mexico, pp. 399-412, 2005.
17. J. Mendel, "Fuzzy logic systems for engineering: a tutorial," Proceedings of the IEEE, vol. 83, pp.345-377, 1995.
18. E. Zitzler, M. Laumanns, and L. Thiele, "SPEA2: improving the strength Pareto evolutionary algorithm," Technical Report TIK-Report 103, Swiss Federal Institute of Technology, Zurich, Germany, 2001.
19. S. Huband, P. Hingston, L. Barone, and L. While, "A review of multiobjective test problems and a scalable test problem toolkit," IEEE Transactions on Evolutionary Computation, vol.10, pp.477-506, 2006.
20. D. Van Veldhuizen, "Multiobjective evolutionary algorithms: classifications, analyses, and new innovations," Ph.D. dissertation, Air Force Institute of Technology, Wright-Patterson AFB, OH, 1999.
21. Q. Zhang, A. Zhou, and Y. Jin, "RM-MEDA: a regularity model based multiobjective estimation of distribution algorithm," IEEE Transactions on Evolutionary Computation, vol. 12, pp. 41-63, 2008.
22. J. Schott, "Fault tolerant design using single and multicriteria genetic algorithm optimization," M.S. thesis, Massachusetts Institute of Technology, Cambridge, MA, 1995.
23. K. Deb, Multi-Objective Optimization Using Evolutionary Algorithms, John Wiley: New York, NY, 2001.