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Eduardo Álvarez-Miranda

Researcher at University of Talca

Publications -  61
Citations -  651

Eduardo Álvarez-Miranda is an academic researcher from University of Talca. The author has contributed to research in topics: Heuristics & Optimization problem. The author has an hindex of 14, co-authored 58 publications receiving 477 citations. Previous affiliations of Eduardo Álvarez-Miranda include University of Bologna.

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The Generalized Reserve Set Covering Problem with Connectivity and Buffer Requirements

TL;DR: The results show the flexibility of the proposed models to provide solutions according to the decision-makers’ requirements, and the effectiveness of the devised algorithm for providing good solutions in reasonable computing times.
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A bi-objective network design approach for discovering functional modules linking Golgi apparatus fragmentation and neuronal death

TL;DR: The obtained results show that it is possible to obtain additional evidence supporting the hypothesis that alterations of the Golgi apparatus structure and neuronal death interact through the biological mechanisms underlying the outbreak and progression of neurodegenerative diseases.
Posted Content

On a Class of Interval Data Minmax Regret CO Problems

TL;DR: In this paper, the Kasperski and Zielinski approximation algorithm for a class of interval data minmax regret combinatorial optimization problems (Algorithm K&Z) is presented.
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Group decision-making method based on advanced aggregation operators with entropy and divergence measures under 2-tuple linguistic Pythagorean fuzzy environment

TL;DR: In this paper , a new score value function for 2-tuple linguistic Pythagorean fuzzy values (2TLPFVs) is introduced, and two aggregation operators (AOs) are presented, namely, the advanced 2-to-triple linguistic linguistics Pythagoregorean fuzzy weighted average (Adv-2TL PFWA) operator, which aggregates 2-TTLPFV information based on novel operational laws of 2TLIFVs, and a new multiple attribute group decision-making (MAGDM) method is constructed.
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Multicriteria saliency detection: a (exact) robust network design approach

TL;DR: A network design-based framework for multicriteria robust saliency detection is proposed and a new method, which incorporates a novel tool for image contour detection, is designed, which exhibits high accuracy in the detection of salience objects.