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| Vol. 1 (2010) , No. 1 pp.65-78 |
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| A Hybrid Selection Strategy Using Scalarization and Adaptive epsilon-Ranking for Many-objective Optimization |
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| Aguirre Hernan, Tanaka Kiyoshi |
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[Aguirre 07] Aguirre, H., and Tanaka, K.: Working Principles, Behavior, and Performance of MOEAs on MNK-Landscapes, European Journal of Operational Research, Elsevier, vol. 181(3), pp. 1670-1690 (2007)
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[Aguirre 09] Aguirre, H., and Tanaka, K.: Adaptive epsilon-Ranking on MNK-Landscapes, Proc.2009 IEEE Symposium on Computational Intelligence in Multicriteria Decision Making, IEEE Service Center, pp.104-111 (2009)
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[Aguirre 10a] Aguirre, H., and Tanaka, K.: Space Partitioning Evolutionary Many-Objective Optimization: Performance Analysis on MNK-Landscapes, Transactions of the Japanese Society for Artificial Intelligence, vol. 25, no. 2, pp.366-373 (2010)
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[Aguirre 10b] Aguirre, H., and Tanaka, K.: A Hybrid Scalarization and Adaptive epsilon-Ranking Strategy for Many-objective Optimization, Parallel Problem Solving from Nature XI, Part II, Springer, LNCS, vol. 6239, pp. 11-20 (2010)
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[Aguirre 10c] Aguirre, H., and Tanaka, K.: Performance Study of a Two-stage Hybrid Method for Many-objective Optimization on Non-convex Continuous Problems, Proc. International Symposium on Intelligent Systems iFAN 2010, 4-pages(2010)
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[Brockhoff 07] Brockhoff, D., and Zitzler, E.: Are All Objectives Necessary? On Dimensionality Reduction in Evolutionary Multiobjective Optimization, Parallel Problem Solving from Nature IX, Springer, LNCS, vol. 4193, pp. 533-542 (2006)
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[Coello 02] Coello, C., Van Veldhuizen, D., and Lamont, G.: Evolutionary Algorithms for Solving Multi-Objective Problems, Kluwer Academic Publishers, Boston (2002)
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[Corne 07] Corne, D., and Knowles, J.: Techniques for Highly Multiobjective Optimization: Some Non-dominated Points are Better than Others, Proc. 2007 Genetic and Evolutionary Computation Conference, pp.773-780 (2007)
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[Deb 00] Deb, K., Agrawal, S., Pratap, A., and Meyarivan, T.: A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II, KanGAL report 200001 (2000)
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[Deb 01] Deb, K.: Multi-Objective Optimization using Evolutionary Algorithms}, John Wiley & Sons, Chichester, West Sussex, England (2001)
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[Deb 02] Deb, K., Thiele, L., Laumanns, M., and Zitzler, E.: Scalable Multi-Objective Optimization Test Problems, Proc. 2002 Congress on Evolutionary Computation, IEEE Service Center, pp.825--830 (2002)
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[Deb 06a] Deb, K., and Sundar,J.: Preference Point Based Multi-objective Optimization Using Evolutionary Algorithms, Proc. 2006 Genetic and Evolutionary Computation Conference, pp. 635-642 (2006)
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[Deb 06b] Deb, K., and Saxena, K.: Searching for Pareto-optimal Solutions Through Dimensionality Reduction for Certain Large-dimensional Multi-objective Optimization Problems, Proc. 2006 IEEE Congress on Evolutionary Computation, pp. 3353-3360 (2006)
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[Emmerich 05] Emmerich, M., Beume, N., and Naujoks, B.: An EMO Algorithm Using the Hypervolume Measure as Selection Criterion, Proc. 3rd Intl. Conf. on Evolutionary Multi-Criterion Optimization, Springer, LNCS, vol. 3410, pp. 62-76 (2005)
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[Fonseca 06] Fonseca, C., Paquete, L., and Lopez-Ibanez, M.: An Improved Dimension-sweep Algorithm for the Hypervolume Indicator, Proc. 2006 IEEE Congress on Evolutionary Computation, IEEE Service Center, pp.1157-1163 (2006)
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[Hughes 05] Hughes, E. J.: Evolutionary Many-Objective Optimization: Many Once or One Many?, Proc. 2005 IEEE Congress on Evolutionary Computation, IEEE Service Center, Vol.1, pp.222-227 (2005)
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[Ishibuchi 98] Ishibuchi, H., Murata,T.: A Multi-Objective Genetic Local Search Algorithm and Its Applications to Flowshop Scheduling, IEEE Trans. on Systems, Man, and Cybernetics - Part C: Applications and Reviews, vol. 28, pp. 392-403 (1998)
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[Ishibuchi 07a] Ishibuchi, H., Tsukamoto, N., and Nojima, Y.: Iterative Approach to Indicator-based Multiobjective Optimization, Proc. 2007 IEEE Congress on Evolutionary Computation, pp. 3697-3704 (2007)
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[Ishibuchi 07b] Ishibuchi, H., and Nojima, Y.: Optimization of Scalarizing Functions Through Evolutionary Multiobjective Optimization, Proc. Fourth Intl. Conf. on Evolutionary Multi-Criterion Optimization, Springer, LNCS, vol. 4403, pp. 51-65 (2007)
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[Ishibuchi 08] Ishibuchi, H., Tsukamoto, N., and Nojima, Y.: Evolutionary Many-Objective Optimization: A Short Review, Proc. IEEE Congress on Evolutionary Computation, IEEE Service Center, pp.2424-2431 (2008)
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[Jaskiewics 02] Jaskiewics, A.: Genetic Local Search for Multi-Objective Combinatorial Optimization, European Journal of Operational Research, vol. 137, pp.50-71 (2002)
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[Kauffman 93] Kauffman, S. A.: The Origins of Order: Self-Organization and Selection in Evolution, Oxford University Press (1993)
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[Koppen 07] Koppen, M., and Yoshida, K.: Substitute Distance Assignments in NSGA-II for Handling Many-Objective Optimization Problems, Proc. 4th Intl. Conf. on Evolutionary Multi-Criterion Optimization, Springer, LNCS, vol.4403, pp,727-741 (2007)
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[Kukkonen 07] Kukkonen, S., and Lampinen, J.: Ranking-dominance and Many Objective Optimization, Proc. 2007 IEEE Congress on Evolutionary Computation, pp. 3983-3990 (2007)
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[Lopez Jaimes 08] Lopez Jaimes, A., Coello, C., and Chakraborty, D.: Objective Reduction Using a Feature Selection Technique, Proc. 2008 Genetic and Evolutionary Computation Conference, ACM Press, pp.674-680 (2008)
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[Sato 07] Sato, H., Aguirre H., and Tanaka K.: Controlling Dominance Area of Solutions in Multiobjective Evolutionary Algorithms and Performance Analysis on Multiobjective 0/1 Knapsack Problems, IPSJ Trans. Mathematical Modeling and its Applications, vol. 48, no. SIG15 (TOM 18), pp.137-152 (2007)
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[Zitzler 99] Zitzler, E.: Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications, PhD thesis, Swiss Federal Institute of Technology, Zurich (1999)
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[Zitzler 04] Zitzler, E., and Kunzli, S.: Indicator-based Selection in Multiobjective Search, Proc. 8th Intl. Conf. on Parallel Problem Solving from Nature, Springer, LNCS, vol.3242, pp. 832-842 (2004)
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