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Article

Lakmayer, S. & Danielson, M. (2025). Efficient Weight Ranking in Multi-Criteria Decision Support Systems. Electronics 14 (7), p. 1237. 10.3390/electronics14071237.

Book Section

Lakmayer, S., Danielson, M. & Ekenberg, L. ORCID: https://orcid.org/0000-0002-0665-1889 (2024). Upper Performance Limits and Distribution Invariance for Surrogate Weights in MCDA. In: Human-Centric Decision and Negotiation Support for Societal Transitions. pp. 89-101 Springer. 10.1007/978-3-031-59373-4_8.

Lakmayer, S., Danielson, M. & Ekenberg, L. ORCID: https://orcid.org/0000-0002-0665-1889 (2023). Aspects of Ranking Algorithms in Multi-Criteria Decision Support Systems. In: New Trends in Intelligent Software Methodologies, Tools and Techniques. pp. 63-75 IOS Press. 10.3233/FAIA230224.

Lakmayer, S., Danielson, M. & Ekenberg, L. ORCID: https://orcid.org/0000-0002-0665-1889 (2023). Automatically Generated Weight Methods for Human and Machine Decision-Making. In: Advances and Trends in Artificial Intelligence. Theory and Applications. Eds. Fujita, H., Wang, Y., Xiao, Y. & Moonis, A., pp. 195-206 Cham, Switzerland: Springer. ISBN 978-3-031-36819-6 10.1007/978-3-031-36819-6_17.