On the computation of the empirical attainment function

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6576 LNCS, Issue , 2011, Pages 106-120

  Fonseca, Carlos M ^a,b,c   Guerreiro, Andreia P ^b   López Ibáñez, Manuel ^d   Paquete, Luís ^e  

^a UNIVERSITY OF COIMBRA   (Portugal)

^b INSTITUTO SUPERIOR TÉCNICO   (Portugal)

^c UNIVERSITY OF ALGARVE   (Portugal)

^d UNIVERSITÉ LIBRE DE BRUXELLES   (Belgium)

^e UNIVERSITY OF COIMBRA   (Portugal)

Author keywords

algorithms; Empirical attainment function; estimation; multiobjective optimiser performance

Indexed keywords

EFFICIENT ALGORITHM; EMPIRICAL ATTAINMENT FUNCTION; EXPERIMENTAL DATA; LOWER BOUNDS; MULTI OBJECTIVE; NON-TRIVIAL TASKS; POINT SET; TIME COMPLEXITY; TWO-DIMENSION; UPPER AND LOWER BOUNDS; NON-DOMINATED POINTS;

MULTIOBJECTIVE OPTIMIZATION; ALGORITHMS; ESTIMATION; EVOLUTIONARY ALGORITHMS;

EVOLUTIONARY ALGORITHMS; OPTIMIZATION;

EID: 79953835926     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-19893-9_8     Document Type: Conference Paper

References (10)

1. Bleuler, S., Laumanns, M., Thiele, L., Zitzler, E.: PISA - A platform and programming language independent interface for search algorithms. In: Fonseca, C.M., et al. (eds.) EMO 2003. LNCS, vol. 2632, pp. 494-508. Springer, Heidelberg (2003)
2. Fonseca, C.M., Fleming, P.J.: On the performance assessment and comparison of stochastic multiobjective optimizers. In: Voigt, H.M., et al. (eds.) PPSN 1996. LNCS, vol. 1141, pp. 584-593. Springer, Heidelberg (1996)
3. Fonseca, C.M., Grunert da Fonseca, V., Paquete, L.: Exploring the performance of stochastic multiobjective optimisers with the second-order attainment function. In: Coello, C.C., et al. (eds.) EMO 2005. LNCS, vol. 3410, pp. 250-264. Springer, Heidelberg (2005)
4. 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. pp. 103-130. Springer, Berlin (2010)
5. Grunert da Fonseca, V., Fonseca, C.M., Hall, A.O.: Inferential performance assessment of stochastic optimisers and the attainment function. In: Zitzler, E., et al. (eds.) EMO 2001. LNCS, vol. 1993, pp. 213-225. Springer, Heidelberg (2001)
6. Knowles, J.D.: A summary-attainment-surface plotting method for visualizing the performance of stochastic multiobjective optimizers. In: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications, pp. 552-557 (2005)
7. Kung, H.T., Luccio, F., Preparata, F.P.: On finding the maxima of a set of vectors. Journal of the ACM 22(4), 469-476 (1975)
8. López-Ibáñez, M., Paquete, L., Stützle, T.: Exploratory analysis of stochastic local search algorithms in biobjective optimization. In: Bartz-Beielstein, T., et al. (eds.) Experimental Methods for the Analysis of Optimization Algorithms, pp. 209-222. Springer, Berlin (2010)
9. Preparata, F.P., Shamos, M.I.: Computational Geometry. An Introduction, 2nd edn. Springer, Berlin (1988)
10. Zitzler, E., Thiele, L.: Multiobjective optimization using evolutionary algorithms - A comparative case study. In: Eiben, A.E., et al. (eds.) PPSN V 1998. LNCS, vol. 1498, pp. 292-301. Springer, Heidelberg (1998)