Finding preferred subsets of Pareto optimal solutions

1. Coello, C.A., Van Veldhuizen, D.A., Lamont, G.B.: Evolutionary Algorithms for Solving Multi-objective Problems. Kluwer Academic, New York (2002)

   MATH  Google Scholar 

2. Das, I.: A preference ordering among various Pareto optimal alternatives. Struct. Optim. 18(1), 30–35 (1999)

   Article  Google Scholar 

3. Ehrgott, M.: Multicriteria Optimization. Springer, Berlin (2005)

   MATH  Google Scholar 

4. Ehrgott, M., Gandibleux, X. (eds.): Multiple Criteria Optimization: State of the Art Annotated Bibliographic Surveys. Kluwer Academic, Boston (2002)

   MATH  Google Scholar 

5. Kao, G.K., Jacobson, S.H.: Post-optimality algorithms and heuristic for multi-objective optimization. Technical report, Department of Computer Science, University of Illinois, Urbana, IL (2006)

6. Kasprzak, E.M., Lewis, K.E.: An approach to facilitate decision tradeoffs in Pareto sets. J. Eng. Valuat. Cost Anal. 3(1), 173–187 (2000)

   Google Scholar 

7. Kasprzak, E.M., Lewis, K.E.: Pareto analysis in multiobjective optimization using the collinearity theorem and scaling method. Struct. Multidiscip. Optim. 22(3), 208–218 (2001)

   Article  Google Scholar 

8. Korhonen, P., Halme, M.: Supporting the decision maker to find the most preferred solutions for a MOLP-problem. In: Proceedings of the 9th International Conference on Multiple Criteria Decision Making, Fairfax, VA, pp. 173–183

9. Mattson, C.A., Mulur, A.A., Messac, A.: Smart Pareto filter: obtaining a minimal representation of multiobjective design space. Eng. Optim. 36(6), 721–740 (2004)

   Article  MathSciNet  Google Scholar 

10. Messac, A., Ismail-Yahaya, A., Mattson, C.A.: The normalized normal constraint method for generating the Pareto frontier. Struct. Multidiscip. Optim. 25(2), 86–98 (2003)

    Article  MathSciNet  Google Scholar 

11. Messac, A., Mattson, C.A.: Normal constraint method with guarantee of even representation of complete Pareto frontier. AIAA J. 42(10), 2101–2111 (2004)

    Article  Google Scholar 

12. Miettinen, K.M.: Nonlinear Multiobjective Optimization. Kluwer Academic, Boston (1999)

    MATH  Google Scholar 

13. Miettinen, K.M., Mäkelä, M.M.: Interactive multiobjective optimization system WWW-NIMBUS on the Internet. Comput. Oper. Res. 27, 709–723 (2000)

    Article  MATH  Google Scholar 

14. Narula, S.C., Kirilov, L., Vassilev, V.: An interactive algorithm for solving multiple objective nonlinear programming problems. In: Proceedings of the 10th International Joint Conference on Multiple Criteria Decision Making, Taipei, Taiwan, pp. 119–127

15. Peeters, R.: The maximum edge biclique problem is NP-complete. Discrete Appl. Math. 131, 651–654 (2003)

    Article  MATH  MathSciNet  Google Scholar 

16. Van Veldhuizen, D.A.: Multiobjective evolutionary algorithms: classifications, analyses, and new innovations. Ph.D. thesis, Department of Electrical and Computer Engineering, Graduate School of Engineering, Air Force Institute of Technology, Wright-Patterson AFB, OH (1999)

17. Venkat, V., Jacobson, S.H., Stori, J.A.: A post-optimality analysis algorithm for multi-objective optimization. Comput. Optim. Appl. 28, 357–372 (2004)

    Article  MATH  MathSciNet  Google Scholar 

Download references