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ETH Zürich - D-ITET - TIK - SOP - Publications
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Publications - Quality Indicators

[1 — bz2010a]
J. Bader and E. Zitzler. Robustness in Hypervolume-based Multiobjective Search. TIK Report 317, Computer Engineering and Networks Laboratory (TIK), ETH Zurich, 2010. (PDF) (bibtex)
[2 — bdz2008a]
J. Bader, K. Deb, and E. Zitzler. Faster Hypervolume-based Search using Monte Carlo Sampling. In M. Ehrgott et al., editors, Conference on Multiple Criteria Decision Making (MCDM 2008), volume 634 of LNEMS, pages 313–326, Heidelberg, Germany, 2010. (bibtex)
[3 — broc2009c]
D. Brockhoff. Theoretical Aspects of Evolutionary Multiobjective Optimization—A Review. Rapport de Recherche RR-7030, INRIA Saclay—Île-de-France, September 2009. (bibtex) (online access)
[4 — abbz2009b]
A. Auger, J. Bader, D. Brockhoff, and E. Zitzler. Articulating User Preferences in Many-Objective Problems by Sampling the Weighted Hypervolume. In G. Raidl et al., editors, Genetic and Evolutionary Computation Conference (GECCO 2009), pages 555–562, New York, NY, USA, 2009. ACM. (PDF) (bibtex)
[5 — abbz2009c]
A. Auger, J. Bader, D. Brockhoff, and E. Zitzler. Investigating and Exploiting the Bias of the Weighted Hypervolume to Articulate User Preferences. In G. Raidl et al., editors, Genetic and Evolutionary Computation Conference (GECCO 2009), pages 563–570, New York, NY, USA, 2009. ACM. (PDF) (bibtex)
[6 — bz2009d]
J. Bader and E. Zitzler. HypE: An Algorithm for Fast Hypervolume-Based Many-Objective Optimization. Evolutionary Computation, page no appear, 2009. to appear. (bibtex)
[7 — bbwz2009a]
J. Bader, D. Brockhoff, S. Welten, and E. Zitzler. On Using Populations of Sets in Multiobjective Optimization. In M. Ehrgott et al., editors, Conference on Evolutionary Multi-Criterion Optimization (EMO 2009), volume 5467 of LNCS, pages 140–154. Springer, 2009. (PDF) (bibtex)
[8 — broc2009b]
D. Brockhoff. Many-Objective Optimization and Hypervolume-Based Search. PhD thesis, ETH Zurich, 2009. (bibtex)
[9 — bz2009b]
J. Bader and E. Zitzler. A Hypervolume-Based Optimizer for High-Dimensional Objective Spaces. In Conference on Multiple Objective and Goal Programming (MOPGP 2008), Lecture Notes in Economics and Mathematical Systems. Springer, 2009. (PDF) (bibtex) (suppl. material)
[10 — abbz2009a]
A. Auger, J. Bader, D. Brockhoff, and E. Zitzler. Theory of the Hypervolume Indicator: Optimal μ-Distributions and the Choice of the Reference Point. In Foundations of Genetic Algorithms (FOGA 2009), pages 87–102, New York, NY, USA, 2009. ACM. (PDF) (bibtex) (suppl. material)
[11 — ztb2008c]
E. Zitzler, L. Thiele, and J. Bader. On Set-Based Multiobjective Optimization (Revised Version). TIK Report 300, Computer Engineering and Networks Laboratory (TIK), ETH Zurich, December 2008. (PDF) (bibtex)
[12 — zkt2008a]
E. Zitzler, J. Knowles, and L. Thiele. Quality Assessment of Pareto Set Approximations. In J. Branke, K. Deb, K. Miettinen, and R. Slowinski, editors, Multiobjective Optimization: Interactive and Evolutionary Approaches, pages 373–404. Springer, 2008. (bibtex) (online access)
[13 — bz2008a]
J. Bader and E. Zitzler. HypE: An Algorithm for Fast Hypervolume-Based Many-Objective Optimization. TIK Report 286, Computer Engineering and Networks Laboratory (TIK), ETH Zurich, November 2008. (PDF) (bibtex) (suppl. material)
[14 — ztb2008d]
E. Zitzler, L. Thiele, and J. Bader. On Set-Based Multiobjective Optimization. IEEE Transactions on Evolutionary Computation, 2009. to appear. (bibtex)
[15 — bfn2008a]
D. Brockhoff, T. Friedrich, and F. Neumann. Analyzing Hypervolume Indicator Based Algorithms. In G. Rudolph et al., editors, Conference on Parallel Problem Solving From Nature (PPSN X), volume 5199 of LNCS, pages 651–660. Springer, 2008. (PDF) (bibtex) (online access)
[16 — bz2007c]
D. Brockhoff and E. Zitzler. Improving Hypervolume-based Multiobjective Evolutionary Algorithms by Using Objective Reduction Methods. In Congress on Evolutionary Computation (CEC 2007), pages 2086–2093. IEEE Press, 2007. (PDF) (bibtex) (suppl. material)
[17 — zbt2007a]
E. Zitzler, D. Brockhoff, and L. Thiele. The Hypervolume Indicator Revisited: On the Design of Pareto-compliant Indicators Via Weighted Integration. In S. Obayashi et al., editors, Conference on Evolutionary Multi-Criterion Optimization (EMO 2007), volume 4403 of LNCS, pages 862–876, Berlin, 2007. Springer. (PDF) (bibtex) (online access) (suppl. material)
[18 — bz2006f]
M. Basseur and E. Zitzler. A Preliminary Study On Handling Uncertainty in Multiobjective Optimization. In F. Rothlauf, J. Branke, S. Cagnoni, et al., editors, European Workshop on Evolutionary Algorithms in Stochastic and Noisy Environments (EvoSTOC 2006), volume 3907 of LNCS, pages 727–739. Springer, 2006. (PDF) (bibtex)
[19 — ktz2006a]
J. Knowles, L. Thiele, and E. Zitzler. A Tutorial on the Performance Assessment of Stochastic Multiobjective Optimizers. TIK Report 214, Computer Engineering and Networks Laboratory (TIK), ETH Zurich, February 2006. (PDF) (bibtex)
[20 — bz2006e]
M. Basseur and E. Zitzler. Handling Uncertainty in Indicator-Based Multiobjective Optimization. International Journal of Computational Intelligence Research, 2(3):255–272, 2006. (PDF) (bibtex)
[21 — zk2004a]
E. Zitzler and S. Künzli. Indicator-Based Selection in Multiobjective Search. In X. Yao et al., editors, Conference on Parallel Problem Solving from Nature (PPSN VIII), volume 3242 of LNCS, pages 832–842. Springer, 2004. (PDF) (bibtex)
[22 — ztlf2003a]
E. Zitzler, L. Thiele, M. Laumanns, C. M. Fonseca, and V. Grunert da Fonseca. Performance Assessment of Multiobjective Optimizers: An Analysis and Review. IEEE Transactions on Evolutionary Computation, 7(2):117–132, 2003. (PDF) (bibtex)
[23 — ltdz2002a]
M. Laumanns, L. Thiele, K. Deb, and E. Zitzler. Combining Convergence and Diversity in Evolutionary Multiobjective Optimization. Evolutionary Computation, 10(3):263–282, 2002. (PDF) (bibtex)
[24 — ltdz2002b]
M. Laumanns, L. Thiele, K. Deb, and E. Zitzler. Archiving with Guaranteed Convergence And Diversity in Multi-objective Optimization. In Genetic and Evolutionary Computation Conference (GECCO 2002), pages 439–447, New York, NY, USA, July 2002. Morgan Kaufmann Publishers. (PDF) (bibtex)
[25 — zltf2002a]
E. Zitzler, M. Laumanns, L. Thiele, C. M. Fonseca, and V. Grunert da Fonseca. Why Quality Assessment Of Multiobjective Optimizers Is Difficult. In Genetic and Evolutionary Computation Conference (GECCO 2002), pages 666–674, New York, NY, USA, July 2002. Morgan Kaufmann Publishers. (PDF) (bibtex)
[26 — ztlf2002a]
E. Zitzler, L. Thiele, M. Laumanns, C. M. Fonseca, and V. Grunert da Fonseca. Performance Assessment of Multiobjective Optimizers: An Analysis and Review. TIK Report 139, Computer Engineering and Networks Laboratory (TIK), ETH Zurich, June 2002. (PDF) (bibtex)
[27 — ltdz2001a]
M. Laumanns, L. Thiele, K. Deb, and E. Zitzler. On the Convergence and Diversity-Preservation Properties of Multi-Objective Evolutionary Algorithms. TIK Report 108, Computer Engineering and Networks Laboratory (TIK), ETH Zurich, 2001. (PDF) (bibtex)
[28 — zdt2000a]
E. Zitzler, K. Deb, and L. Thiele. Comparison of Multiobjective Evolutionary Algorithms: Empirical Results. Evolutionary Computation, 8(2):173–195, 2000. (PDF) (bibtex)
[29 — zitz1999a]
E. Zitzler. Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications. PhD thesis, ETH Zurich, Switzerland, 1999. (PDF) (bibtex)
[30 — zdt1999b]
E. Zitzler, K. Deb, and L. Thiele. Comparison of Multiobjective Evolutionary Algorithms: Empirical Results (Revised Version). TIK Report 70, Computer Engineering and Networks Laboratory (TIK), ETH Zurich, December 1999. (PDF) (bibtex)
[31 — zt1999a]
E. Zitzler and L. Thiele. Multiobjective Evolutionary Algorithms: A Comparative Case Study and the Strength Pareto Approach. IEEE Transactions on Evolutionary Computation, 3(4):257–271, 1999. (PDF) (bibtex)
[32 — zt1998b]
E. Zitzler and L. Thiele. Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study. In Conference on Parallel Problem Solving from Nature (PPSN V), pages 292–301, Amsterdam, 1998. (PDF) (bibtex)
[33 — zt1998a]
E. Zitzler and L. Thiele. An Evolutionary Approach for Multiobjective Optimization: The Strength Pareto Approach. TIK Report 43, Computer Engineering and Networks Laboratory (TIK), ETH Zurich, May 1998. (PDF) (bibtex)
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