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Experiments with classification-based scalarizing functions in interactive multiobjective optimization

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  • Miettinen, Kaisa
  • Makela, Marko M.
  • Kaario, Katja

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  • Miettinen, Kaisa & Makela, Marko M. & Kaario, Katja, 2006. "Experiments with classification-based scalarizing functions in interactive multiobjective optimization," European Journal of Operational Research, Elsevier, vol. 175(2), pages 931-947, December.
    • Handle: RePEc:eee:ejores:v:175:y:2006:i:2:p:931-947
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    References listed on IDEAS

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    1. Buchanan, John & Gardiner, Lorraine, 2003. "A comparison of two reference point methods in multiple objective mathematical programming," European Journal of Operational Research, Elsevier, vol. 149(1), pages 17-34, August.
    2. Sakawa, Masatoshi & Yauchi, Katsuhiro, 1999. "An interactive fuzzy satisficing method for multiobjective nonconvex programming problems through floating point genetic algorithms," European Journal of Operational Research, Elsevier, vol. 117(1), pages 113-124, August.
    3. Caballero, Rafael & Rey, Lourdes & Ruiz, Francisco, 1998. "Lexicographic improvement of the target values in convex goal programming," European Journal of Operational Research, Elsevier, vol. 107(3), pages 644-655, June.
    4. Sakawa, Masatoshi, 1982. "Interactive multiobjective decision making by the sequential proxy optimization technique: SPOT," European Journal of Operational Research, Elsevier, vol. 9(4), pages 386-396, April.
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    Cited by:

    1. Lizhen Shao & Matthias Ehrgott, 2014. "An objective space cut and bound algorithm for convex multiplicative programmes," Journal of Global Optimization, Springer, vol. 58(4), pages 711-728, April.
    2. Zeiträg, Yannik & Figueira, José Rui & Pereira, Miguel Alves, 2024. "A web-based interactive decision support system for a multi-objective lot-sizing and production scheduling model," International Journal of Production Economics, Elsevier, vol. 271(C).
    3. Ismail I. Almaraj & Theodore B. Trafalis, 2022. "A robust optimization approach in a multi-objective closed-loop supply chain model under imperfect quality production," Annals of Operations Research, Springer, vol. 319(2), pages 1479-1505, December.
    4. Francisco Ruiz & Mariano Luque & Kaisa Miettinen, 2012. "Improving the computational efficiency in a global formulation (GLIDE) for interactive multiobjective optimization," Annals of Operations Research, Springer, vol. 197(1), pages 47-70, August.
    5. Lu Chen & Kaisa Miettinen & Bin Xin & Vesa Ojalehto, 2023. "Comparing reference point based interactive multiobjective optimization methods without a human decision maker," Journal of Global Optimization, Springer, vol. 85(3), pages 757-788, March.
    6. Ana Ruiz & Rubén Saborido & Mariano Luque, 2015. "A preference-based evolutionary algorithm for multiobjective optimization: the weighting achievement scalarizing function genetic algorithm," Journal of Global Optimization, Springer, vol. 62(1), pages 101-129, May.
    7. Çağın Ararat & Firdevs Ulus & Muhammad Umer, 2022. "A Norm Minimization-Based Convex Vector Optimization Algorithm," Journal of Optimization Theory and Applications, Springer, vol. 194(2), pages 681-712, August.
    8. Ruiz, Francisco & Luque, Mariano & Miguel, Francisca & del Mar Munoz, Maria, 2008. "An additive achievement scalarizing function for multiobjective programming problems," European Journal of Operational Research, Elsevier, vol. 188(3), pages 683-694, August.
    9. Matthias Ehrgott & Lizhen Shao & Anita Schöbel, 2011. "An approximation algorithm for convex multi-objective programming problems," Journal of Global Optimization, Springer, vol. 50(3), pages 397-416, July.
    10. Luque, Mariano & Miettinen, Kaisa & Eskelinen, Petri & Ruiz, Francisco, 2009. "Incorporating preference information in interactive reference point methods for multiobjective optimization," Omega, Elsevier, vol. 37(2), pages 450-462, April.

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