Special Issue "Fuzzy Hybrid Systems for Construction Engineering and Management"

A special issue of Algorithms (ISSN 1999-4893). This special issue belongs to the section "Evolutionary Algorithms and Machine Learning".

Deadline for manuscript submissions: 15 August 2020.

Special Issue Editors

Prof. Dr. Aminah Robinson Fayek
Website
Guest Editor
Department of Civil and Environmental Engineering, University of Alberta, Edmonton, AB T6G 2R3, Canada
Interests: fuzzy logic; fuzzy hybrid systems; machine learning; decision support systems; simulation; optimization; system dynamics; agent-based modeling; subjective knowledge; construction
Special Issues and Collections in MDPI journals
Dr. Mohammad Raoufi
Website
Guest Editor
Department of Civil and Environmental Engineering, University of Alberta, Edmonton, AB T6G 2R3, Canada
Interests: construction engineering and management; civil engineering
Dr. Sumati Vuppuluri
Website
Guest Editor
Department of Civil and Environmental Engineering, University of Alberta, Edmonton, AB T6G 2R3, Canada
Interests: function approximation; fuzzy neural nets; fuzzy reasoning; fuzzy set theory; fuzzy systems; inference mechanisms

Special Issue Information

Dear Colleagues,

The construction industry is a vital part of many national economies. Construction industry performance is largely dependent on the effective planning, execution, and control of construction projects, which involve both complexity and uncertainty. Fuzzy logic methodologies are able to model subjective information, handle uncertainty and complexity, and address the lack of comprehensive datasets available for modeling in construction engineering and management. In recent years, researchers have combined fuzzy logic with other soft computing and simulation techniques to create advanced fuzzy hybrid systems that are well-suited to construction modeling. This Special Issue focuses on recent advances and applications of fuzzy hybrid computing techniques in the construction domain. The Special Issue also focuses on the practical application of these techniques to solve real-world problems across a wide range of construction engineering and management issues.

Papers are invited that cover, but are not limited to, the following topics:

  • Fuzzy hybrid techniques in construction
  • Fuzzy arithmetic applications in construction
  • Fuzzy simulation techniques in construction
  • Fuzzy machine learning and optimization techniques in construction
  • Fuzzy multi-criteria decision-making applications in construction
  • Neuro-fuzzy systems in construction
  • Construction applications of fuzzy hybrid techniques, including risk analysis, project performance, productivity, procurement, contracting strategies, construction methods, competency assessment, quality management, safety management, and project planning and control.

Prof. Aminah Robinson Fayek
Dr. Mohammad Raoufi
Dr. Sumati Vuppuluri
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • soft computing
  • fuzzy logic
  • neuro-fuzzy systems
  • fuzzy hybrid techniques
  • artificial intelligence
  • machine learning
  • optimization
  • simulation
  • construction modeling
  • decision-making
  • uncertainty modeling
  • construction engineering and management

Published Papers (1 paper)

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Research

Open AccessArticle
A Fuzzy-Based Decision Support Model for Risk Maturity Evaluation of Construction Organizations
Algorithms 2020, 13(5), 115; https://doi.org/10.3390/a13050115 - 02 May 2020
Abstract
Risk maturity evaluation is an efficient tool which can assist construction organizations in the identification of their strengths and weaknesses in risk management processes and in taking necessary actions for the improvement of these processes. The accuracy of its results relies heavily on [...] Read more.
Risk maturity evaluation is an efficient tool which can assist construction organizations in the identification of their strengths and weaknesses in risk management processes and in taking necessary actions for the improvement of these processes. The accuracy of its results relies heavily on the quality of responses provided by participants specialized in these processes across the organization. Risk maturity models reported in the literature gave equal importance to participants’ responses during the model development, neglecting their level of authority in the organization as well as their level of expertise in risk management processes. Unlike the existing models, this paper presents a new risk maturity model that considers the relative importance of the responses provided by the participants in the model development. It considered their authority in the organization and their level of involvement in the risk management processes for calculating the relative weights associated with the risk maturity attributes. It employed an analytic network process (ANP) to model the interdependencies among the risk maturity attributes and utilizes the fuzzy set theory to incorporate the uncertainty associated with the ambiguity of the responses used in the model development. The developed model allows the construction organizations to have a more accurate and realistic view of their current performance in risk management processes. The application of the developed model was investigated by measuring the risk maturity level of an industrial partner working on civil infrastructure projects in Canada. Full article
(This article belongs to the Special Issue Fuzzy Hybrid Systems for Construction Engineering and Management)
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