Abstract
This paper investigates the relationship between the covered fraction, completeness, and (weighted) hypervolume indicators for assessing the quality of the Pareto-front approximations produced by multiobjective optimizers. It is shown that these unary quality indicators are all, by definition, weighted Hausdorff measures of the intersection of the region attained by such an optimizer outcome in objective space with some reference set. Moreover, when the optimizer is stochastic, the indicators considered lead to real-valued random variables following particular probability distributions. Expressions for the expected value of these distributions are derived, and shown to be directly related to the first-order attainment function.
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References
Alberti, G.: Geometric measure theory. In: Françoise, J.P., et al. (eds.) Encyclopedia of Mathematical Physics, vol. 2, pp. 520–527. Elsevier, Oxford (2006)
Bader, J.M.: Hypervolume-Based Search for Multiobjective Optimization: Theory and Methods. Ph.D. thesis, Swiss Federal Institute of Technology, Zurich (2009)
Barenblatt, G.I.: Scaling, Self-similarity, and Intermediate Asymptotics. Cambridge University Press, Cambridge (1996)
DiBenedetto, E.: Real Analysis. Birkhäuser, Boston (2002)
Fonseca, C.M., Grunert da Fonseca, V., Paquete, L.: Exploring the Performance of Stochastic Multiobjective Optimisers with the Second-Order Attainment Function. In: Coello Coello, C.A., Hernández Aguirre, A., Zitzler, E. (eds.) EMO 2005. LNCS, vol. 3410, pp. 250–264. Springer, Heidelberg (2005)
Fonseca, C.M., Guerreiro, A.P., López-Ibáñez, M., Paquete, L.: On the Computation of the Empirical Attainment Function. In: Takahashi, R.H.C., Deb, K., Wanner, E.F., Greco, S. (eds.) EMO 2011. LNCS, vol. 6576, pp. 106–120. Springer, Heidelberg (2011)
Grunert da Fonseca, V., Fonseca, C.M.: The attainment-function approach to stochastic multiobjective optimizer assessment and comparison. In: Bartz-Beielstein, T., et al. (eds.) Experimental Methods for the Analysis of Optimization Algorithms, ch. 5, pp. 103–130. Springer, Berlin (2010)
Grunert da Fonseca, V., Fonseca, C.M., Hall, A.O.: Inferential Performance Assessment of Stochastic Optimisers and the Attainment Function. In: Zitzler, E., Deb, K., Thiele, L., Coello Coello, C.A., Corne, D. (eds.) EMO 2001. LNCS, vol. 1993, pp. 213–225. Springer, Heidelberg (2001)
Ito, K. (ed.): Encyclopedic Dictionary of Mathematics 2. The Mathematical Society of Japan. The MIT Press (1987)
Lotov, A.V., Bushenkov, V.A., Kamenev, G.K.: Interactive Decision Maps: Approximation and Visualization of Pareto Frontier. Kluwer Academic Publishers, Dordrecht (2004)
Molchanov, I.: Theory of Random Sets. Springer, London (2005)
Ott, E.: Chaos in Dynamical Systems. Cambridge University Press, Cambridge (2002)
Ulungu, E.L., Teghem, J., Fortemps, P.H., Tuyttens, D.: MOSA method: A tool for solving multiobjective combinatorial optimization problems. Journal of Multi-Criteria Decision Analysis 8(4), 221–236 (1999)
Zitzler, E., Brockhoff, D., Thiele, L.: The Hypervolume Indicator Revisited: On the Design of Pareto-compliant Indicators Via Weighted Integration. In: Obayashi, S., Deb, K., Poloni, C., Hiroyasu, T., Murata, T. (eds.) EMO 2007. LNCS, vol. 4403, pp. 862–876. Springer, Heidelberg (2007)
Zitzler, E., Knowles, J., Thiele, L.: Quality Assessment of Pareto Set Approximations. In: Branke, J., Deb, K., Miettinen, K., Słowiński, R. (eds.) Multiobjective Optimization. LNCS, vol. 5252, pp. 373–404. Springer, Heidelberg (2008)
Zitzler, E., Thiele, L.: Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, H.-P. (eds.) PPSN 1998. LNCS, vol. 1498, pp. 292–301. Springer, Heidelberg (1998)
Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C.M., Grunert da Fonseca, V.: Performance assessment of multiobjective optimizers: An analysis and review. IEEE Transactions on Evolutionary Computation 7(2), 117–132 (2003)
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Grunert da Fonseca, V., Fonseca, C.M. (2012). The Relationship between the Covered Fraction, Completeness and Hypervolume Indicators. In: Hao, JK., Legrand, P., Collet, P., Monmarché, N., Lutton, E., Schoenauer, M. (eds) Artificial Evolution. EA 2011. Lecture Notes in Computer Science, vol 7401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35533-2_3
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DOI: https://doi.org/10.1007/978-3-642-35533-2_3
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