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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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Journal ArticleDOI

Minmax regret combinatorial optimization problems: an Algorithmic Perspective

TL;DR: The computational complexity of some classic combinatorial optimization problems using MMR approach is discussed, the design of several algorithms for these problems are analyzed, and the study of some specific research problems in this attractive area is suggested.
Book ChapterDOI

The Rooted Maximum Node-Weight Connected Subgraph Problem

TL;DR: This paper considers the Rooted Maximum Node-Weight Connected Subgraph Problem as well as its budget-constrained version, in which also non-negative costs of the nodes are given, and the solution is not allowed to exceed a given budget.
Journal ArticleDOI

A multicriteria optimization model for sustainable forest management under climate change uncertainty: An application in Portugal

TL;DR: Results show the capacity of the designed framework to provide a pool of diverse solutions with different trade-offs among the four criteria, giving to the manager the possibility of choosing a harvesting policy that meets her/his requirements.
Journal ArticleDOI

In-depth data on the network structure and hourly activity of the Central Chilean power grid.

TL;DR: This study presents the dataset of the Chilean power grid, harmonized data from three diverse sources to generate a unified dataset that focuses on preserving the physical structure of nodes’ connection incorporating the ‘tap’ structure.
Journal ArticleDOI

A simulation and optimisation methodology for choosing energy efficiency measures in non-residential buildings

TL;DR: A methodological framework for predicting (i) the energy consumed in heating and cooling an existing commercial or institutional building, and (ii) the potential impact of different energy conservation measures that could be implemented on a given building is developed.