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Analysis of institutional authors

Latorre, AntonioAuthorPena, Jose-MariaAuthor

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June 9, 2019
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Distributed Estimation of Distribution Algorithms for continuous optimization: How does the exchanged information influence their behavior?

Publicated to: INFORMATION SCIENCES. 268 231-254 - 2014-06-01 268(), DOI: 10.1016/j.ins.2013.10.026

Authors:

Muelas, S; Mendiburu, A; LaTorre, A; Peña, JM
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Affiliations

CSIC, Inst Cajal - Author
Univ Basque Country, Dept Comp Architecture & Technol, Intelligent Syst Grp - Author
Univ Politecn Madrid, Dept Comp Syst Architecture & Technol - Author
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Abstract

One of the most promising areas in which probabilistic graphical models have shown an incipient activity is the field of heuristic optimization and, in particular, in Estimation of Distribution Algorithms. Due to their inherent parallelism, different research lines have been studied trying to improve Estimation of Distribution Algorithms from the point of view of execution time and/or accuracy. Among these proposals, we focus on the so-called distributed or island-based models. This approach defines several islands (algorithms instances) running independently and exchanging information with a given frequency. The information sent by the islands can be either a set of individuals or a probabilistic model. This paper presents a comparative study for a distributed univariate Estimation of Distribution Algorithm and a multivariate version, paying special attention to the comparison of two alternative methods for exchanging information, over a wide set of parameters and problems - the standard benchmark developed for the IEEE Workshop on Evolutionary Algorithms and other Metaheuristics for Continuous Optimization Problems of the ISDA 2009 Conference. Several analyses from different points of view have been conducted to analyze both the influence of the parameters and the relationships between them including a characterization of the configurations according to their behavior on the proposed benchmark. (c) 2014 Published by Elsevier Inc.
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Keywords

Continuous domainsContinuous optimizationEdasEstimation of distribution algorithmEvolutionary computationGenetic algorithmsGraphical modelIsland modelMigrationParallel bmdaProbability-models

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal INFORMATION SCIENCES due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2014, it was in position 6/139, thus managing to position itself as a Q1 (Primer Cuartil), in the category Computer Science, Information Systems.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-25:

  • WoS: 13
  • Scopus: 18
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-25:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 19 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/36090/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 482
  • Downloads: 479
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Muelas, Santiago) and Last Author (PEÑA SANCHEZ, JOSE MARIA).

the author responsible for correspondence tasks has been Muelas, Santiago.

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Awards linked to the item

This work was financed by the Spanish Ministry of Science TIN2010-21289-C02-02 and supported by the Cajal Blue Brain Project. The authors thankfully acknowledge the computer resources, technical expertise and assistance provided by the Centro de Supercomputacion y Visualizacion de Madrid (CeSViMa) and the Spanish Supercomputing Network. The authors would also like to thank Nelis Franken for his help with his Fluxviz tool.
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