The multi-objective distinct candidates optimization approach

Bioinspired Optimization Methods and their Applications - Proceedings of the 4th International Conference on Bioinspired Optimization Methods and their Applications, BIOMA 2010

Volumn , Issue , 2010, Pages 55-66

  Ursem, Rasmus K ^a   Justesen, Peter Dueholm ^b  

^a Grundfos DK AS   (Denmark)

^b AARHUS UNIVERSITY   (Denmark)

Author keywords

Distinct candidates; Diversity management; Multi objective optimization

Indexed keywords

CANDIDATE SOLUTION; DESIGN DIFFERENCES; DISTINCT CANDIDATES; DOMAIN SPECIFIC; MULTI OBJECTIVE; MULTI OBJECTIVE OPTIMIZATIONS (MOO); OPTIMIZATION APPROACH; POST PROCESSING; REAL-WORLD PROBLEM; SIMILAR SOLUTION;

ALGORITHMS;

MULTIOBJECTIVE OPTIMIZATION;

EID: 84866674704     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (19)

1. J. Branke, K. Deb, H. Dierolf, and M. Osswald. Finding knees in multi-objective optimization. In Proc. 8th International Conference on Parallel Problem Solving from Nature (PPSN), pages 720-729, 2004.
2. J. Branke, H. Schmeck, K. Deb, and R. Maheshwar. Parallelizing multi-objective evolutionary algorithms: Cone separation. In Proc. IEEE Congress on Evolutionary Computation (CEC), pages 1952-1957, 2004.
3. E. D. Brill Jr. The use of optimization models in public-sector planning. Manage. Sci., 25(5):413-422, 1979.
4. E. D. Brill Jr., S.-Y. Chang, and L. D. Hopkins. Modeling to generate alternatives: The hsj approach and an illustration using a problem in land use planning. Manage. Sci., 28(3):221-235, 1982.
5. E. D. Brill Jr., J. M. Flach, L. D. Hopkins, and S. Ranjithan. Mga: A decision support system for complex, incompletely defined problems. IEEE T. Syst. Man Cyb., 20(4):745-757, 1990.
6. C. A. Coello Coello. A comprehensive survey of evolutionary-based multiobjective optimization techniques. Knowl. Inf. Syst., 1(3):269-308, 1999.
7. C. A. Coello Coello. An updated survey of GA-based multiobjective optimization techniques. ACM Comput. Surv., 32(2):109-143, 2000.
8. C. A. Coello Coello. Handling preferences in evolutionary multiobjective optimization: A survey. In Proc. IEEE Congress on Evolutionary Computation (CEC), vol. 1, pages 30-37, 2000.
9. K. Deb. Multi-Objective Optimization using Evolutionary Algorithms. John Wiley & Sons, Chichester, 2001.
10. P. D. Justesen and R. K. Ursem. Multiobjective distinct candidates optimization (modco): A cluster-forming differential evolution algorithm. In Proc. Fifth International Conference on Evolutionary Multi-Criterion Optimization (EMO), vol. 1, pages 525-539, 2009.
11. P. D. Justesen and R. K. Ursem. Preference-based multi-objective distinct candidates optimization. In Proc. Fourth International Conference on Bioinspired Optimization Methods and their Applications (BIOMA), pages 117-129, 2010.
12. T. E. Koch and A. Zell. MOCS: Multi-objective clustering selection evolutionary algorithm. In Proc. Genetic and Evolutionary Computation Conference (GECCO), pages 423-430, 2002.
13. D. H. Loughlin, S. R. Ranjithan, E. D. Brill Jr., and J. W. Baugh Jr. Genetic algorithm approaches for addressing unmodeled objectives in optimization problems. Eng. Optimiz., 33(5):549-569, 2001.
14. M. Li. Robust optimization and sensitivity analysis with multi-objective genetic algorithms: Single-and multi-disciplinary applications. Ph.D. dissertation, University of Maryland, 2007.
15. A. Molyneaux, G. Leyland, and D. Favrat. A new, clustering evolutionary multiobjective optimisation technique. In Proc. Third International Symposium on Adaptive Systems, Evolutionary Computation and Probabilistic Graphical Models, pages 41-47, 2001.
16. L. Rachmawati and D. Srinivasan. A multi-objective evolutionary algorithm with weighted-sum niching for convergence on knee regions. In Proc. Conference on Genetic and Evolutionary Computation (GECCO), pages 749-750, 2006.
17. M. Reyes-Sierra and C. A. Coello Coello. Multi-objective particle swarm optimizers: A survey of the state-of-the-art. Int. J. Comput. Intel. Res., 2(3):287-308, 2006.
18. D. A. V. Veldhuizen and G. B. Lamont. Multiobjective evolutionary algorithms: Analyzing the state-of-the-art. Evol. Comput., 8(2):125-147, 2000.
19. E. Zechman and S. R. Ranjithan. An evolutionary algorithm to generate alternatives (eaga) for engineering optimization problems. Eng. Optimiz., 36(5):539-553, 2004.