Behavior of evolutionary many-objective optimization

Proceedings - UKSim 10th International Conference on Computer Modelling and Simulation, EUROSIM/UKSim2008

Volumn , Issue , 2008, Pages 266-271

  Ishibuchi, Hisao ^a   Tsukamoto, Noritaka ^a   Nojima, Yusuke ^a  

^a Osaka Prefecture University

Author keywords

[No Author keywords available]

Indexed keywords

0/1 KNAPSACK PROBLEMS; COMPUTER MODELLING; CONVERGENCE OF SOLUTIONS; EMO ALGORITHMS; EVOLUTIONARY COMPUTATION; EVOLUTIONARY MULTI-OBJECTIVE OPTIMIZATION; FUTURE RESEARCH DIRECTIONS; INTERNATIONAL CONFERENCES; OBJECTIVE OPTIMIZATION; PARETO FRONTS; RESEARCH AREAS; SEARCH ABILITY; TO MANY;

COMPUTER SYSTEMS; EVOLUTIONARY ALGORITHMS; INTEGER PROGRAMMING; OPTIMIZATION;

MULTIOBJECTIVE OPTIMIZATION;

EID: 50149086001     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/UKSIM.2008.13     Document Type: Conference Paper

References (22)

1. K. Deb, Multi-Objective Optimization Using Evolutionary Algorithms, John Wiley & Sons, Chichester, 2001.
2. C.A.C. Coello, D.A. van Veldhuizen, and G.B. Lamont, Evolutionary Algorithms for Solving Multi-Objective Problems, Kluwer Academic Publishers, Boston, 2002.
3. C.A.C. Coello and G.B. Lamont, Applications of Multi-Objective Evolutionary Algorithms, World Scientific, Singapore, 2004.
4. A. Abraham, L.C. Jain, and R. Goldberg (eds.), Evolutionary Multiobjective Optimization: Theoretical Advances and Applications, Springer, Berlin, 2005.
5. 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), pp. 182-197, April 2002.
6. E. Zitzler and L. Thiele, "Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach," IEEE Trans. on Evolutionary Computation 3 (4), pp. 257-271, November 1999.
7. A. Jaszkiewicz, "On the computational efficiency of multiple objective metaheuristics: The knapsack problem case study," European Journal of Operational Research 158 (2), pp. 418-433, October 2004.
8. E. J. Hughes, "Evolutionary many-objective optimization: Many once or one many?," Proc. of 2005 IEEE Congress on Evolutionary Computation, pp. 222-227, Edinburgh, UK, September 2-5, 2005.
9. H. Ishibuchi, Y. Nojima, and T. Doi, "Comparison between single-objective and multi-objective genetic algorithms: Performance comparison and performance measures," Proc. of 2006 Congress on Evolutionary Computation, pp. 3959-3966, Vancouver, July 16-21, 2006.
10. H. Sato, H. E. Aguirre, and K. Tanaka, "Controlling dominance area of solutions and its impact on the performance of MOEAs," Lecture Notes in Computer Science 4403: Evolutionary Multi-Criterion Optimization - EMO 2007, pp. 5-20, Springer, Berlin, March 2007.
11. A. Jaszkiewicz, "On the performance of multiple-objective genetic local search on the 0/1 knapsack problem - A comparative experiment," IEEE Trans. on Evolutionary Computation 6 (4), pp. 402-412, August 2002.
12. A. Sülflow, N. Drechsler, and R. Drechsler, "Robust multi-objective optimization in high dimensional spaces," Lecture Notes in Computer Science 4403: Evolutionary Multi-Criterion Optimization - EMO 2007, pp. 715-726, Springer, Berlin, March 2007.
13. D. Corne and J. Knowles, "Techniques for highly multiobjective optimization: Some non-dominated points are better than others," Proc. of 2007 Genetic and Evolutionary Computation Conference, pp. 773-780, London, July 7-11, 2007.
14. S. Kukkonen and J. Lampinen, "Ranking-Dominance and Many-Objective Optimization," Proc. of 2007 IEEE Congress on Evolutionary Computation, pp. 3983-3990, Singapore, September 25-28, 2007.
15. H. Ishibuchi and Y. Nojima, "Optimization of scalarizing functions through evolutionary multiobjective optimization," Lecture Notes in Computer Science 4403: Evolutionary Multi-Criterion Optimization - EMO 2007, pp. 51-65, Springer, Berlin, March 2007.
16. E. J. Hughes, "Multiple single objective Pareto sampling," Proc. of 2003 Congress on Evolutionary Computation, pp. 2678-2684, Canberra, Australia, December 8-12, 2003.
17. H. Ishibuchi, T. Doi, and Y. Nojima, "Incorporation of scalarizing fitness functions into evolutionary multiobjective optimization algorithms," Lecture Notes in Computer Science 4193: Parallel Problem Solving from Nature - PPSN IX, pp. 493-502, Springer, Berlin, September 2006.
18. E. J. Hughes, "MSOPS-II: A general-purpose many-objective optimiser," Proc. of 2007 Congress on Evolutionary Computation, pp. 3944-3951, Singapore, September 25-28, 2007.
19. E. Zitzler and S. Künzli, "Indicator-based selection in multiobjective search," Lecture Notes in Computer Science 3242: Parallel Problem Solving from Nature - PPSN VIII, pp. 832-842, Springer, Berlin, September 2004.
20. N. Beume, B. Naujoks, and M. Emmerich, "SMS-EMOA: multiobjective selection based on dominated hypervolume," European Journal of Operational Research 181 (3), pp. 1653-1669, September 2007.
21. T. Wagner, N. Beume, and B. Naujoks, "Pareto-, aggregation-, and indicator-based methods in many-objective optimization," Lecture Notes in Computer Science 4403: Evolutionary Multi-Criterion Optimization - EMO 2007, pp. 742-756, Springer, Berlin, March 2007.
22. H. Ishibuchi, N. Tsukamoto, and Y. Nojima, "Iterative approach to indicator-based multiobjective optimization," Proc. of 2007 IEEE Congress on Evolutionary Computation, pp. 3697-3704, Singapore, September 25-28, 2007.