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Comparative evaluation of some interactive reference point-based methods for multi-objective optimisation

Author

Listed:
  • K Miettinen

    (University of Jyväskylä)

  • M M Mäkelä

    (University of Jyväskylä)

Abstract

Many real-world optimisation applications include several conflicting objectives of possibly nondifferentiable character. However, the lack of computationally efficient, interactive methods for nondifferentiable multi-objective optimisation problems is apparent. To satisfy this demand, a method called NIMBUS has been developed. Two versions of the basic method are presented and compared both theoretically and computationally. In order to give variety to the comparison, a related approach, called reference direction method is included. Theoretically, the methods differ in handling the information requested from the user. Numerical experiments indicate differences in computational efficiency and controllability of the solution processes.

Suggested Citation

  • K Miettinen & M M Mäkelä, 1999. "Comparative evaluation of some interactive reference point-based methods for multi-objective optimisation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(9), pages 949-959, September.
    • Handle: RePEc:pal:jorsoc:v:50:y:1999:i:9:d:10.1057_palgrave.jors.2600786
    DOI: 10.1057/palgrave.jors.2600786
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    Citations

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    Cited by:

    1. F Ruiz & M Luque & J M Cabello, 2009. "A classification of the weighting schemes in reference point procedures for multiobjective programming," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(4), pages 544-553, April.
    2. Resat, Hamdi G. & Turkay, Metin, 2015. "Design and operation of intermodal transportation network in the Marmara region of Turkey," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 83(C), pages 16-33.
    3. Kathrin Klamroth & Kaisa Miettinen, 2008. "Integrating Approximation and Interactive Decision Making in Multicriteria Optimization," Operations Research, INFORMS, vol. 56(1), pages 222-234, February.
    4. Kim, Yeong Jae & Soh, Moonwon & Cho, Seong-Hoon, 2022. "Identifying optimal financial budget distributions for the low-carbon energy transition between emerging and developed countries," Applied Energy, Elsevier, vol. 326(C).
    5. Yadav, Deepanshu & Nagar, Deepak & Ramu, Palaniappan & Deb, Kalyanmoy, 2023. "Visualization-aided multi-criteria decision-making using interpretable self-organizing maps," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1183-1200.

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