A fast many-objective hypervolume algorithm using iterated incremental calculations

2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

Volumn , Issue , 2010, Pages

  Bradstreet, Lucas ^a   While, Lyndon ^a   Barone, Luigi ^a  

^a UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

AVERAGE CASE; COMPREHENSIVE ANALYSIS; FAST ALGORITHMS; HYPERVOLUME; HYPERVOLUME BY SLICING OBJECTIVES; KLEE'S MEASURE PROBLEM; PERFORMANCE COMPARISON; STATE-OF-THE-ART ALGORITHMS;

ARTIFICIAL INTELLIGENCE;

EVOLUTIONARY ALGORITHMS;

EID: 79959471916     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2010.5586344     Document Type: Conference Paper

References (30)

1. R. Purshouse, "On the evolutionary optimisation of many objectives," Ph.D. dissertation, The University of Sheffield, United Kingdom, 2003.
2. E. Zitzler, "Evolutionary algorithms for multiobjective optimization: Methods and applications," Ph.D. dissertation, Swiss Federal Institute of Technology (ETH) Zurich, Switzerland, 1999.
3. M. Laumanns, E. Zitzler, and L. Thiele, "A unified model for multiobjective evolutionary algorithms with elitism," in Congress on Evolutionary Computation, R. Eberhart, Ed. IEEE, 2000, pp. 46-53.
4. M. Fleischer, "The measure of Pareto optima: Applications to multiobjective metaheuristics," in Evolutionary Multi-objective Optimisation, ser. Lecture Notes on Computer Science, C. M. Fonseca, P. J. Fleming, E. Zitzler, K. Deb, and L. Thiele, Eds., vol. 2632. Springer-Verlag, 2003, pp. 519-533.
5. E. Zitzler, L. Thiele, M. Laumanns, C. M. Fonseca, and V. G. da Fonseca, "Performance assessment of multiobjective optimizers: An analysis and review," IEEE Transactions on Evolutionary Computation, vol. 7, no. 2, pp. 117-132, April 2003.
6. M. Fleischer, "The measure of Pareto optima: Applications to multiobjective metaheuristics," Institute for Systems Research, University of Maryland, Technical Report ISR TR 2002-32, 2002.
7. T. Wagner, N. Beume, and B. Naujoks, "Pareto-, aggregation-, and indicator-based methods in many-objective optimization," Lecture Notes in Computer Science, vol . 4403, p. 742, 2007.
8. R. Everson, J. Fieldsend, and S. Singh, "Full elite sets for multiobjective optimisation," in Proceedings of the 5th International Conference on Adaptive Computing in Design and Manufacture, 2002, pp. 87-100.
9. J. Bader, K. Deb, and E. Zitzler, "Faster Hypervolume-based Search using Monte Carlo Sampling," in Conference on Multiple Criteria Decision Making (MCDM 2008). Springer, 2008, pp. 313-326.
10. E. Zitzler, "Hypervolume metric calculation," 2001. [Online] . Available: ftp://ftp.tik.ee.ethz.ch/pub/people/zitzler/hypervol.c
11. J. Knowles, "Local-search and hybrid evolutionary algorithms for Pareto optimisation," Ph.D. dissertation, The University of Reading, United Kingdom, 2002.
12. L. While, P. Hingston, L. Barone, and S. Huband, "A faster algorithm for calculating hypervolume," IEEE Transactions on Evolutionary Computation, vol. 10, no. 1, pp. 29-38, February 2006.
13. L. While, L. Bradstreet, L. Barone, and P. Hingston, "Heuristics for optimising the calculation of hypervolume for multi-objective optimisation problems," in Congress on Evolutionary Computation, B. McKay, Ed. IEEE, 2005, pp. 2225-2232.
14. M. H. Overmars and C.-K. Yap, "New upper bounds in Klee's measure problem," SIAM Journal on Computing, vol. 20, no. 6, pp. 1034-1045, December 1991.
15. N. Beume and G. Rudolph, "Faster S-metric calculation by considering dominated hypervolume as klee's measure problem," University of Dortmund, Technical Report CI 216/06, 2006.
16. L. Paquete, C. M. Fonseca, and M. López-Ibáñez, "An optimal algorithm for a special case of Klee's measure problem in three dimensions," CSI, Universidade do Algarve, Tech. Rep. CSI-RT-I-01/2006, 2006.
17. N. Beume, C. Fonseca, M. López-Ibáñez, L. Paquete, and J. Vahrenhold, "On the complexity of computing the hypervolume indicator," 2007.
18. C. M. Fonseca, L. Paquete, and M. López-Ibáñez, "An improved dimension-sweep algorithm for the hypervolume indicator," in Congress on Evolutionary Computation, C. L. P. Chen, Ed. IEEE, 2006, pp. 3973-3979.
19. L. Bradstreet, L. While, and L. Barone, "A fast incremental hypervolume algorithm," Evolutionary Computation, IEEE Transactions on, vol. 12, no. 6, pp. 714-723, Dec. 2008.
20. S. Huband, P. Hingston, L. While, and L. Barone, "An evolution strategy with probabilistic mutation for multi-objective optimization," in Congress on Evolutionary Computation, H. Abbass and B. Verma, Eds. IEEE, 2003, pp. 2284-2291.
21. J. Knowles, D. Come, and M. Fleischer, "Bounded archiving using the Lebesgue measure," in Congress on Evolutionary Computation, H. Abbass and B. Verma, Eds. IEEE, 2003, pp. 2490-2497.
22. E. Zitzler and S. Künzli, "Indicator-based selection in multi objective search," in Parallel Problem Solving from Nature VIII, ser. Lecture Notes on Computer Science, X. Yao, E. Burke, J. A. Lozano, J. Smith, J. J. Merelo-Guervos, J. A. Bullinaria, J. Rowe, P. Tino, A. Kaban, and H.-P. Schwefel, Eds., vol. 3242. Springer-Verlag, 2004, pp. 832-842.
23. M. Emmerich, N. Beume, and B. Naujoks, "An EMO algorithm using the hypervolume measure as selection criterion," in Evolutionary Multi-objective Optimisation, ser. Lecture Notes on Computer Science, C. A. Coello Coello, A. H. Aguirre, and E. Zitzler, Eds., vol. 3410. Springer-Verlag, 2005, pp. 62-76.
24. T. Bäck, D. Fogel, and Z. Michalewicz, Eds., Handbook of Evolutionary Computation. Institute of Physics Publishing and Oxford University Press, 1997.
25. N. Beume, "HOY source code," 2006. [Online] . Available: http://ls11-www.cs.uni-dortmund.de/people/beume/publications/hoy.cpp
26. C. M. Fonseca, M. López-Ibáñez, and L. Paquete, "Computation of the hypervolume indicator," 2007. [Online]. Available: http://sbe.napier.ac.uk/manuel/hypervolume
27. Walking Fish Group, "IIHSO code," 2009. [Online]. Available: wfg.csse.uwa.edu.au/Hypervolume
28. K. Deb, L. Thiele, M. Laumanns, and E. Zitzler, "Scalable multiobjective optimization test problems," in Congress on Evolutionary Computation, R. Eberhart, Ed. IEEE, 2002, pp. 825-830.
29. S. Huband, P. Hingston, L. Barone, and L. While, "A review of multi-objective test problems and a scalable test problem toolkit," Transactions on Evolutionary Computation, vol. 10, no. 5, pp. 477-506, 2006.
30. Walking Fish Group, "Hypervolume test data," 2009. [Online]. Available: wfg.csse.uwa.edu.au/Hypervolume