Publications - Search Algorithms

[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 — wbhb2010a]

M. Woehrle, D. Brockhoff, T. Hohm, and S. Bleuler. Investigating Coverage and Connectivity Trade-offs in Wireless Sensor Networks: The Benefits of MOEAs. In M. Ehrgott et al., editors, Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems (MCDM 2008), volume 634 of LNEMS, pages 211–221, Heidelberg, Germany, 2010. Springer. (bibtex)

[3 — 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)

[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 — 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)

[11 — 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)

[12 — ztb2008d]

E. Zitzler, L. Thiele, and J. Bader. On Set-Based Multiobjective Optimization. IEEE Transactions on Evolutionary Computation, 2009. to appear. (bibtex)

[13 — wbhb2008b]

M. Woehrle, D. Brockhoff, T. Hohm, and S. Bleuler. Investigating Coverage and Connectivity Trade-offs in Wireless Sensor Networks: The Benefits of MOEAs. TIK Report 294, Computer Engineering and Networks Laboratory (TIK), ETH Zurich, October 2008. (PDF) (bibtex)

[14 — ztb2008b]

E. Zitzler, L. Thiele, and J. Bader. SPAM: Set Preference Algorithm for Multiobjective Optimization. In G. Rudolph et al., editors, Conference on Parallel Problem Solving From Nature (PPSN X), volume 5199 of LNCS, pages 847–858. Springer, 2008. (PDF) (bibtex) (online access)

[15 — 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)

[16 — 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)

[17 — ltz2006a]

M. Laumanns, L. Thiele, and E. Zitzler. An Efficient, Adaptive Parameter Variation Scheme for Metaheuristics Based on the Epsilon-Constraint Method. European Journal of Operational Research, 169(3):932–942, March 2006. (PDF) (bibtex)

[18 — 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)

[19 — 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)

[20 — 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)

[21 — 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)

[22 — zlt2002a]

E. Zitzler, M. Laumanns, and L. Thiele. SPEA2: Improving the Strength Pareto Evolutionary Algorithm for Multiobjective Optimization. In K.C. Giannakoglou et al., editors, Evolutionary Methods for Design, Optimisation and Control with Application to Industrial Problems (EUROGEN 2001), pages 95–100. International Center for Numerical Methods in Engineering (CIMNE), 2002. (PDF) (bibtex)

[23 — 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)

[24 — zlt2001a]

E. Zitzler, M. Laumanns, and L. Thiele. SPEA2: Improving the Strength Pareto Evolutionary Algorithm. TIK Report 103, Computer Engineering and Networks Laboratory (TIK), ETH Zurich, Zurich, Switzerland, 2001. (PDF) (bibtex)

[25 — zitz1999a]

E. Zitzler. Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications. PhD thesis, ETH Zurich, Switzerland, 1999. (PDF) (bibtex)

[26 — 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)

[27 — 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)

[28 — 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)