Abstract
Determining consensus for a set of ordered partitions (or a collective) is used for making decisions. Ordered partitions are a helpful structure for representing the opinions of experts or agents. Algorithms to determine 1-Optimality consensus were introduced in the literature. However, no algorithm has yet to be proposed for determining the 2-Optimality consensus. Determining 2-Optimality consensus for a collective of ordered partitions is an NP-hard problem. In this study, first, we present a mathematical formula for determining such a collective. Then, three hybrid genetic algorithms are proposed to solve this problem. The simulation results show that the HG3 algorithm finds the best quality consensus in an acceptable time.
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This research is funded by Vietnam National University Ho Chi Minh City (VNU-HCM) under grant number DS2021-26-03.
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Dang, D.T., Truong, H.B., Nguyen, N.T. (2023). Hybrid Genetic Algorithms to Determine 2-Optimality Consensus for a Collective of Ordered Partitions. In: Nguyen, N.T., et al. Computational Collective Intelligence. ICCCI 2023. Lecture Notes in Computer Science(), vol 14162. Springer, Cham. https://doi.org/10.1007/978-3-031-41456-5_1
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