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Objective: Dynamic cerebral autoregulation (dCA) has been addressed through different approaches for discriminating between normal and impaired conditions based on spontaneous fluctuations in arterial blood pressure (ABP) and cerebral blood flow (CF). This work presents a novel multi-objective optimisation (MO) approach for finding good configurations of a cerebrovascular resistance-compliance model., Methods: Data from twenty-nine subjects under normo and hypercapnic (5% CO 2 in air) conditions was used. Cerebrovascular resistance and vessel compliance models with ABP as input and CF velocity as output were fitted using a MO approach, considering fitting Pearson's correlation and error., Results: MO approach finds better model configurations than the single-objective (SO) approach, especially for hypercapnic conditions. In addition, the Pareto-optimal front from the multi-objective approach enables new information on dCA, reflecting a higher contribution of myogenic mechanism for explaining dCA impairment., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Felipe Andres Bello Robles reports financial support was provided by FONDECYT 3200598. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)