A comparison of dominance criteria in many-objective optimization problems

2011 IEEE Congress of Evolutionary Computation, CEC 2011

Volumn , Issue , 2011, Pages 2359-2366

  Batista, Lucas S ^a   Campelo, Felipe ^a   Guimaraes, Frederico G ^a   Ramirez, Jaime A ^a  

^a FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

DOMINANCE CRITERIA; MULTIOBJECTIVE EVOLUTIONARY OPTIMIZATION; OPTIMIZATION ALGORITHMS; OPTIMIZATION PROBLEMS;

EVOLUTIONARY ALGORITHMS;

MULTIOBJECTIVE OPTIMIZATION;

EID: 80051988722     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2011.5949909     Document Type: Conference Paper

References (38)

1. H. Ishibuchi, N. Tsukamoto, and Y. Nojima, Evolutionary Many-Objective Optimization: A Short Review, Proceedings of the 2008 IEEE Congress on Evolutionary Computation, CEC 2008, pp. 2424-2431, Hong Kong, 2008.
2. V. Khare, X. Yao, and K. Deb, Performance Scaling of Multiobjective Evolutionary Algorithms, Lecture Notes in Computer Science, vol. 2632, pp. 376-390, Springer-Verlag Berlin, Heidelberg 2003.
3. R. C. Purshouse and P. J. Fleming, Evolutionary Many-Objective Optimisation: An Exploratory Analysis, Proceedings of the 2003 IEEE Congress on Evolutionary Computation, CEC 2003, vol. 3, pp. 2066-2073, Canberra, Australia 2003.
4. E. J. Hughes, Evolutionary Many-Objective Optimisation: Many Once or One Many?, Proceedings of the 2005 IEEE Congress on Evolutionary Computation, CEC 2005, vol. 1, pp. 222-227, Edinburgh, Scotland 2005. (Pubitemid 41495859)
5. T. Wagner, N. Beume, and B. Naujoks, Pareto-, Aggregation-, and Indicator-Based Methods in Many-Objective Optimization, Lecture Notes in Computer Science, vol. 4403, pp. 742-756, Springer-Verlag Berlin, Heidelberg 2007. (Pubitemid 350270923)
6. P. J. Fleming, R. C. Purshouse, and R. J. Lygoe, Manyobjective optimization: An engineering design perspective. Lecture Notes in Computer Science, vol. 3410, pp. 14-32, Springer-Verlag Berlin, Heidelberg 2005. (Pubitemid 41251753)
7. K. Deb and J. Sundar, Preference point based multiobjective optimization using evolutionary algorithms, Proceedings of the 2006 Genetic and Evolutionary Computation Conference, GECCO 2006, pp. 635-642, Seattle 2006. (Pubitemid 44611383)
8. A. L. Jaimes, C. A. Coello Coello, and J. E. U. Barrientos, Online Objective Reduction to Deal with Many-Objective Problems, Lecture Notes in Computer Science, vol. 5467, pp. 423-437, Springer-Verlag Berlin, Heidelberg 2009.
9. K. Deb, and D. K. Saxena, Searching for Paretooptimal solutions through dimensionality reduction for certain large-dimensional multi-objective optimization problems, Proceedings of the 2006 IEEE Congress on Evolutionary Computation, CEC 2006, pp. 3353-3360, Vancouver 2006.
10. A. L. Jaimes and C. A. Coello Coello, Study of Preference Relations in Many-Objective Optimization, Proceedings of the 2009 Genetic and Evolutionary Computation Conference, GECCO 2009, pp. 611-618, Montréal Québec, Canada 2009.
11. D. Brockhoff, and E. Zitzler, Are All Objectives Necessary? On Dimensionality Reduction in Evolutionary Multiobjective Optimization, Proceedings of the Parallel Problem Solving from Nature IX, PPSN 2006, pp. 533-542, Springer-Verlag 2006. (Pubitemid 44609429)
12. M. Garza-Fabre, G. T. Pulido, and C. A. Coello Coello, Alternative Fitness Assignment Methods for Many-Objective Optimization Problems, Lecture Notes in Computer Science, vol. 5975, pp. 146-157, Springer-Verlag Berlin, Heidelberg 2010.
13. H. Ishibuchi, N. Tsukamoto, Y. Hitotsuyanagi, and Y. Nojima, Effectiveness of Scalability Improvement Attempts on the Performance of NSGA-II for Many-Objective Problems, Proceedings of the 2008 Genetic and Evolutionary Computation Conference, GECCO 2008, pp. 649-656, Atlanta 2006.
14. H. Sato, H. E. Aguirre, and K. Tanaka, Controlling Dominance Area of Solutions and Its Impact on the Performance of MOEAs, Lecture Notes in Computer Science, vol. 4403, pp. 5-20, Springer-Verlag Berlin, Heidelberg 2007. (Pubitemid 350284279)
15. H. Sato, H. Aguirre, and K. Tanaka, Controlling Dominance Area of Solutions in Multiobjective Evolutionary Algorithms and Performance Analysis on Multiobjective 0/1 Knapsack Problems, IPSJ Digital Courier, vol. 3, pp. 703-718, 2007.
16. R. C. Purshouse and P. J. Fleming, Conflict, harmony, and independence: relationships in evolutionary multicriterion optimisation, Lecture Notes in Computer Science, vol. 2632, pp. 16-30, Springer-Verlag Berlin, Heidelberg 2003.
17. K. Ikeda, H. Kita, and S. Kobayash, Failure of Pareto-Based MOEAs: Does Non-Dominated Really Mean Near to Optimal?, Proceedings of the 2001 Congress on Evolutionary Computation, CEC 2001, vol. 2, pp. 957-962, Seoul, South Korea 2001. (Pubitemid 32806244)
18. M. Laumanns, L. Thiele, K. Deb, and E. Zitzler, Combining Convergence and Diversity in Evolutionary Multi-objective Optimization, Evolutionary Computation, vol. 10, no. 3, pp. 263-282, 2002.
19. L. S. Batista, F. Campelo, F. G. Guimarães, and J. A. Ramírez, Pareto Cone ε-Dominance: Improving Convergence and Diversity in Multiobjective Evolutionary Algorithms, (to appear) Proceedings of the 6th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2011, 2011.
20. J. Knowles and D. Corne, Quantifying the Effects of Objective Space Dimension in Evolutionary Multiobjective Optimization, Lecture Notes in Computer Science, vol. 4403, pp. 757-771, Springer-Verlag Berlin, Heidelberg 2007. (Pubitemid 350270924)
21. D. Corne and J. Knowles, Techniques for Highly Multiobjective Optimisation: Some Nondominated Points are Better than Others, Proceedings of the 2007 Genetic and Evolutionary Computation Conference, GECCO 2007, pp. 773-780, London, England, United Kingdom 2007. (Pubitemid 47296800)
22. M. Köppen and K. Yoshida, Substitute Distance Assignments in NSGA-II for Handling Many-Objective Optimization Problems, Lecture Notes in Computer Science, vol. 4403, pp. 727-741, Springer-Verlag Berlin, Heidelberg 2007. (Pubitemid 350270922)
23. E. J. Hughes, Fitness Assignment Methods for Many-Objective Problems, in Multi-Objective Problem Solving from Nature, Natural Computing Series, Part IV, pp. 307-329, 2008.
24. M. Garza-Fabre, G. T. Pulido, and C. A. Coello Coello, Ranking Methods for Many-Objective Optimization, Lecture Notes in Artificial Intelligence, vol. 5845, pp. 633-645, Springer-Verlag Berlin, Heidelberg 2009.
25. 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, no. 3, pp. 315-326, 2004.
26. A. G. Hernández-Díaz, L. V. Santana-Quintero, C. A. Coello Coello, and J. Molina, Pareto-Adaptive ε-Dominance, Evolutionary Computation, vol. 15, no. 4, pp. 493-517, 2007.
27. K. Le and D. Landa-Silva, Obtaining Better Non-Dominated Sets Using Volume Dominance, Proceedings of the 2007 IEEE Congress on Evolutionary Computation, CEC 2007, pp. 3119-3126, Singapore 2007.
28. X. Zou, Y. Chen, M. Liu, and L. Kang, A New Evolutionary Algorithm for Solving Many-Objective Optimization Problems, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 38, no. 5, pp. 1402-1412, 2008.
29. K. Deb, Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley & Sons, Chichester, 2001.
30. E. Zitzler and L. Thiele, Multiobjective Evolutionary Algorithms: A Comparative Case Study and the Strength Pareto Approach, IEEE Transactions on Evolutionary Computation, vol. 3, no. 4, pp. 257-271, 1999. (Pubitemid 30544879)
31. K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, vol. 6, no. 2, pp. 182-197, 2002. (Pubitemid 34555372)
32. K. M. Miettinen, Nonlinear Multiobjective Optimization, International Series in Operations Research & Management Science. Springer, 1st edition, 1998.
33. D. J. White, Epsilon efficiency, Journal Of Optimization Theory And Applications, vol. 49, no. 2, pp. 319-337, 1986.
34. H. K. Singh, A. Isaacs, T. Ray, and W. Smith, A Study on the Performance of Substitute Distance Based Approaches for Evolutionary Many Objective Optimization, Lecture Notes in Computer Science, vol. 5361, pp. 401-410, Springer-Verlag Berlin, Heidelberg 2008.
35. D. K. Saxena, T. Ray, K. Deb, and A. Tiwari, Constrained Many-Objective Optimization: A Way Forward, Proceedings of the 2009 IEEE Congress on Evolutionary Computation, CEC 2009, pp. 545-552, Trondheim 2009.
36. H. Aguirre and K. Tanaka, Adaptive ε-Ranking on Many-Objective Problems, Evolutionary Intelligence, vol. 2, no. 4, pp. 183-206, Springer-Verlag 2009.
37. H. Aguirre and K. Tanaka, A Study on the Effects of Rankings Sensitive to Density on Many-Objective MNK Landscapes, Proceedings of the 2010 IEEE World Congress on Computational Intelligence, WCCI 2010, pp. 1089-1096, Barcelona, Spain 2010.
38. Deb, K., Thiele, L., Laumanns, M., Zitzler, E.: Scalable Test Problems for Evolutionary Multiobjective Optimization. In: Abraham, A., Jain, L., Goldberg, R. (eds.) Evolutionary Multiobjective Optimization. Theoretical Advances and Applications, pp. 105-145. Springer (2005)