An evolution strategy with probabilistic mutation for multi-objective optimisation

2003 Congress on Evolutionary Computation, CEC 2003 - Proceedings

Volumn 4, Issue , 2003, Pages 2284-2291

  Huband, S ^a   Hingston, P ^a   While, L ^b   Barone, L ^b  

^a EDITH COWAN UNIVERSITY   (Australia)

^b UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

MULTIOBJECTIVE OPTIMIZATION;

EVOLUTION STRATEGIES; MULTI-OBJECTIVE TESTS; PARAMETER-LESS; STATE-OF-THE-ART ALGORITHMS;

EVOLUTIONARY ALGORITHMS;

EID: 24344467352     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2003.1299373     Document Type: Conference Paper

References (23)

1. H. A, Abbass. The Self-adaptive Pareto Differential Evolution algorithm. In D. B. Fogel et al., editor, CEC'02, volume 1, pages 831-836. IEEE, 2002.
2. K. H. Ang, G. Chong. and Y. Li. Preliminary statement on the current progress of multi-objective evolutionary algorithm performance measurement. In D. B. Fogel et al., editor, CEC'02, volume 2, pages 1139-1144. IEEE, 2002.
3. T. Back, U. Hammel. and H-P. Schwefel. Evolutionary computation: Comments on the history and current state. IEEE Trans, on Evolutionary-Computation, 1(1):3-16. 1997.
4. L. Barone, L. While, and P. Hingston. Designing crushers with a multi-objective evolutionary algorithm. In W. B. Langdon et al., editor. CECCO-2002. pages 995-1002. Morgan Kaufmann Publishers. 2002.
5. D. Büche, P. Stoll. R. Dornberger. and P. Koumoutsakos. Multiobjective evolutionary algorithm for the optimization of noisy combustion processes. IEEE Trans, on Systems, Man, and Cybernetics - Part C: Applications and Reviews, 32(4):460-473, 2002.
6. L. Costa and P. Oliveira. An evolution strategy for multiobjective optimization. In D. B. Fogel et al., editor, CEC'02, volume 1, pages 97-102. IEEE, 2002.
7. K. Deb. A. Pratap. S. Agarwal, and T. Meyarivan. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans, on Evolutionary Computation, 6(2):182-197. 2002.
8. C, M. Fonseca and P. J. Fleming. Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization. In S. Forrest, editor, Proceedings of the Fifth International Conference on Genetic Algorithms, pages 416-423. Morgan Kaufmann Publishers, 1993.
9. C, M. Fonseca and P. J. Fleming. On the performance assessment and comparison of stochastic multiobjective optimizers. In H-M. Voigt et al., editor, PPSN IV. volume 1141 of LNCS, pages 584-593. Springer-Verlag, 1996.
10. D. E. Goldberg. Genetic Algorithms in Search, Optimization & Machine Learning. Addison-Wesley, 1989.
11. J. Knowles and D. Corne. Approximating the nondominated front using the Pareto archived evolution strategy. Evolutionary Computation. 8(2):149-172, 2000.
12. J. Knowles and D. Corne. M-PAES: A memetic algorithm for multiobjective optimization. In CEC'00, volume 1, pages 325-332. IEEE, 2000.
13. J. Knowles and D. Corne. On metrics for comparing nondominated sets. In D. B. Fogel et al., editor, CEC'02, volume 1, pages 711-716. IEEE, 2002.
14. B. F. J. Manly. Randomization. Bootstrap and Monte Carlo Methods in Biology. Chapman & Hall, 1991
15. R. C. Purshouse and P. J. Fleming. The Multiobjective Genetic Algorithm applied to benchmark problems - an analysis. Research Report 796, University of Sheffield, Dept of Automatic Control and Systems Engineering, UK, 2001.
16. R. C. Purshouse and P. J. Fleming. Elitism, sharing. and ranking choices in evolutionary multi-criterion optimisation. Research Report 815, University of Sheffield. Dept of Automatic Control and Systems Engineering, UK, 2002.
17. R. C. Purshouse and P. J. Fleming. Why use elitism and sharing in a multi-objective genetic algorithm? In W. B. Langdon et al., editor. GECCO-2002. pages 520-527. Morgan Kaufmann Publishers, 2002.
18. R. C, Purshouse and P. J. Fleming. An adaptive divide-and-conquer methodology for evolutionary multi-criterion optimisation. In C. M. Fonseca et al., editor, EMO 2003, volume 2632 of LNCS. pages 133-147. Springer-Verlag, 2003.
19. D. A. Van Veldhuizen. Multiobjective Evolutionary Algorithms: Classifications, Analyses, and New Innovations. PhD thesis. Air Force Inst of Technology, Wright-Patterson AFB, Ohio, 1999.
20. E. Zitzler. Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications. PhD thesis. Swiss Federal Inst of Technology (ETH) Zurich. 1999.
21. E. Zitzler, K. Deb, and L. Thiele. Comparison of multiobjective evolutionary algorithms: Empirical results. Evolutionary Computation, 8(2):173-195, 2000.
22. E. Zitzler. M. Laumanns, and L. Thiele. SPEA2: Improving the strength Pareto evolutionary algorithm for multiobjective optimization. In K. C. Giannakoglou et al., editor. EUROGEN 2001, pages 95-100. International Center for Numerical Methods in Engineering (CIMNE), Barcelona. Spain, 2001.
23. E. Zitzler and L. Thiele. Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach. IEEE Trans, on Evolutionary Computation, 3(4):257-271, 1999.