CISUC

On the complexity of computing the hypervolume indicator

Authors



TechReport Number

CI 235/07, SFB 531

Cited by

Year 2009 : 7 citations

 -H. Trautman, T.Wagner, B. Naujoks, M. Press, J. Mehnen, Statistical Methods for Convergence Detection of Multi-Objective Evolutionary Algorithms, Vol. 17, No. 4, Pages 493-509.

 - N. Beume, S-Metric Calculation by Considering Dominated Hypervolume as Klees Measure Problem, Evolutionary Computation, Vol. 17, No. 4, Pages 477-492, 2009.

 - Dimo Brockhoff, Theoretical Aspects of Evolutionary Multiobjective Optimization, Technical Report 7030, INRIA, 2009.

 - N. Beume, B. Naujoks, M. Preuss, G. Rudolph, T. Wagner, Effects of 1-Greedy S-Metric-Selection on Innumerably Large Pareto Fronts, EMO 2009, LNCS 5369, Springer, pp. 21-35, 2009.

 - Karl Bringmann and Tobias Friedrich, Approximating the least hypervolume contributor: NP-hard in general, but fast in practice, EMO 2009, LNCS 5369, Springer, pp. 6-20, 2009

 - Karl Bringmann and Tobias Friedrich, Don t be greedy when calculating hypervolume contributions, ACM Foundations of Genetic Algorithms - FOGA 2009.

 - A. Auger, J. Bader, D. Brockhoff, and E. Zitzler. Theory of the Hypervolume Indicator: Optimal mu-Distributions and the Choice of the Reference Point, ACM Foundations of Genetic Algorithms - FOGA 2009.

Year 2008 : 3 citations

 - Edgar Reehuis, Multiobjective Optimization of Water Distribution Networks Using SMS-EMOA, Technical report 08-12, Universiteit Leiden, Opleiding Informatica, 2008

 - Karl Bringmann and Tobias Friedrich, Approximating the Volume of Unions and Intersections of High-Dimensional Geometric Objects, LNCS 5369, Springer, pp. 436-447, 2008

 - 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.