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Intelligent Multi-Criteria Decision-Making Methodologies in Building and Construction Management—2nd Edition
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Intelligent Multi-Criteria Decision-Making Methodologies in Building and Construction Management—2nd Edition

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".

Deadline for manuscript submissions: 31 May 2026 | Viewed by 3267

Special Issue Editors

Dr. Seyyed Ahmad Edalatpanah

E-Mail Website
Guest Editor
Department of Applied Mathematics, Ayandegan Institute of Higher Education, Tonekabon, Iran
Interests: computational intelligence; uncertainty; decision theory and method; multicriteria decision-making; construction management, operation research; soft computing; computational modeling
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jurgita Antucheviciene

E-Mail Website
Guest Editor
Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, LT-10223 Vilnius, Lithuania
Interests: civil engineering; multiple-criteria decision-making; multiple-criteria optimization in construction technology and management; sustainability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Following the success of our first Special Issue, "Intelligent Multi-Criteria Decision-Making Methodologies in Building and Construction Management", we are thrilled to announce the second volume in this series. The previous Special Issue attracted numerous high-quality submissions, showcasing innovative applications and advancements in multi-criteria decision-making (MCDM) methodologies. Building on this foundation, the second volume aims to delve deeper into the theoretical and practical applications of intelligent decision-making approaches in building and construction management.

As the construction industry navigates increasing complexity, uncertainty, and sustainability demands, MCDM methodologies have become indispensable for optimizing decision-making processes. This Special Issue seeks cutting-edge contributions that explore mathematical innovations, computational intelligence, and practical implementations of MCDM in construction. Particular emphasis will be placed on emerging trends such as digital twins, Internet of Things (IoT)-enabled smart cities, and artificial intelligence (AI)-driven decision-making frameworks, alongside traditional areas like resource optimization, risk management, and sustainable development.

We welcome submissions on innovative MCDM models, hybrid frameworks, performance benchmarking, and real-world case studies. By inspiring novel solutions and fostering scientific progress, this Special Issue aims to advance intelligent decision-making methodologies and address critical challenges in construction management.

Topics include, but are not limited to, the following:

  • Decision analysis and strategic planning: Advanced frameworks and methodologies for decision-making in construction projects, balancing cost, efficiency, and sustainability.
  • Uncertainty in MCDM: Cutting-edge approaches to address and model uncertainty, enabling robust and adaptive decision-making under varying conditions.
  • Innovative modeling in MCDM: Development of novel mathematical and computational models to address emerging challenges and improve decision-making accuracy.
  • Digital twins and smart cities: The integration of MCDM with digital twin technology to support smart city planning, infrastructure optimization, and real-time decision-making.
  • IoT in Buildings and Construction: Leveraging IoT and intelligent systems to streamline construction processes and improve operational efficiency.
  • Computational intelligence in MCDM: Incorporating AI, machine learning, and hybrid systems to enhance the capabilities of multi-criteria decision-making.
  • Inventory and supply chain management: The application of MCDM methodologies to optimize supply chain operations, improve logistics, and enhance resilience in construction networks.
  • Performance management and benchmarking: MCDM-based evaluation tools and methods to measure and benchmark performance, ensuring alignment with strategic goals.
  • Building Information Modeling (BIM): Integration of MCDM with BIM to enhance project planning, resource allocation, and construction execution.
  • Sustainable construction: Innovative MCDM approaches for sustainable design, material selection, energy efficiency, and green building practices.
  • Risk and safety management: Advanced methods for identifying, assessing, and mitigating risks to improve safety and reliability in construction projects.
  • Construction delays and mitigation strategies: Applications of MCDM to analyze and reduce delays, optimize timelines, and improve project delivery.
  • Reliability and maintenance engineering: Ensuring long-term durability and system reliability through MCDM-based maintenance planning.
  • Urban renovation and adaptive reuse: Decision-making methodologies for urban renewal, historic preservation, and adaptive reuse of spaces to meet contemporary needs.
  • Transportation and logistics in construction: Optimization of transportation systems and logistics operations using MCDM models to improve efficiency and reduce costs.
  • Case studies and real-world applications: Empirical studies showcasing the transformative impact of MCDM in addressing real-world challenges in building and construction management.

Dr. Seyyed Ahmad Edalatpanah
Prof. Dr. Jurgita Antucheviciene
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 submissions that pass pre-check are 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. Buildings is an international peer-reviewed open access semimonthly 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 2600 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

  • multi-criteria decision-making
  • measurement of performance in construction
  • computational intelligence
  • optimization in construction management
  • multi-attribute decision-making
  • digital twins and smart cities
  • sustainable construction
  • risk and safety management
  • building information modeling
  • building management

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Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (5 papers)

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Research

18 pages, 1460 KB  
Article
Sustainable Optimization Design of Architectural Space Based on Visual Perception and Multi-Objective Decision Making
by Qunjing Ji, Yu Cai and Osama Sohaib
Buildings 2025, 15(16), 2940; https://doi.org/10.3390/buildings15162940 - 19 Aug 2025
Viewed by 260
Abstract
This study proposes an integrated computational framework that combines deep learning-based visual perception analysis with multi-criteria decision making to optimize indoor architectural layouts in terms of both visual coherence and sustainability. The framework initially employs a deep learning method leveraging edge pixel feature [...] Read more.
This study proposes an integrated computational framework that combines deep learning-based visual perception analysis with multi-criteria decision making to optimize indoor architectural layouts in terms of both visual coherence and sustainability. The framework initially employs a deep learning method leveraging edge pixel feature recombination to extract critical spatial layout features and determine key visual focal points. A fusion model is then constructed to preprocess visual representations of interior layouts. Subsequently, an evolutionary deep learning algorithm is adopted to optimize parameter convergence and enhance feature extraction accuracy. To support comprehensive evaluation and decision making, an improved Analytic Hierarchy Process (AHP) is integrated with the entropy weight method, enabling the fusion of objective, data-driven weights with subjective expert judgments. This dual-focus framework addresses two pressing challenges in architectural optimization: sensitivity to building-specific spatial features and the traditional disconnect between perceptual analysis and sustainability metrics. Experimental results on a dataset of 25,400 building images demonstrate that the proposed method achieves a feature detection accuracy of 92.3%, surpassing CNN (73.6%), RNN (68.2%), and LSTM (75.1%) baselines, while reducing the processing time to under 0.95 s and lowering the carbon footprint to 17.8% of conventional methods. These findings underscore the effectiveness and practicality of the proposed model in facilitating intelligent, sustainable architectural design. Full article
(This article belongs to the Special Issue Intelligent Multi-Criteria Decision-Making Methodologies in Building and Construction Management—2nd Edition)
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22 pages, 916 KB  
Article
A Model Based on Variable Weight Theory and Interval Grey Clustering to Evaluate the Competency of BIM Construction Engineers
by Shaonan Sun, Yiming Zuo, Chunlu Liu, Xiaoxiao Yao, Ailing Wang and Zhihui Wang
Buildings 2025, 15(14), 2574; https://doi.org/10.3390/buildings15142574 - 21 Jul 2025
Viewed by 226
Abstract
Building information modeling (BIM) has emerged as a fundamental component of Industry 4.0 recently. BIM construction engineers (BCEs) play a pivotal role in implementing BIM, and their personal competency is crucial to the successful application and promotion of BIM technology. Existing research on [...] Read more.
Building information modeling (BIM) has emerged as a fundamental component of Industry 4.0 recently. BIM construction engineers (BCEs) play a pivotal role in implementing BIM, and their personal competency is crucial to the successful application and promotion of BIM technology. Existing research on evaluating BIM capabilities has mainly focused on the enterprise or project level, neglecting individual-level analysis. Therefore, this study aims to establish an individual-level competency evaluation model for BCEs. Firstly, the competency of BCEs was divided into five levels by referring to relevant standards and domestic and foreign research. Secondly, through the analysis of literature data and website data, the competency evaluation indicator system for BCEs was constructed, which includes four primary indicators and 27 secondary indicators. Thirdly, variable weight theory was used to optimize the weights determined by general methods and calculate the comprehensive weights of each indicator. Then the competency levels of BCEs were determined by the interval grey clustering method. To demonstrate the application of the proposed method, a case study from a Chinese enterprise was conducted. The main results derived from this case study are as follows: domain competencies have the greatest weight among the primary indicators; the C9-BIM model is the secondary indicator with the highest weight (ωj = 0.0804); and the competency level of the BCE is “Level 3”. These results are consistent with the actual situation of the enterprise. The proposed model in this study provides a comprehensive tool for evaluating BCEs’ competencies from an individual perspective, and offers guideline for BCEs to enhance their competencies in pursuing sustainable professional development. Full article
(This article belongs to the Special Issue Intelligent Multi-Criteria Decision-Making Methodologies in Building and Construction Management—2nd Edition)
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28 pages, 395 KB  
Article
Resident Satisfaction in Eco-Friendly Housing: Informing Sustainable Decision-Making in Urban Development
by Dan Wang, Yunbo Zhang, Radzi Ismail, Mohd Wira Mohd Shafiei and Terh Jing Khoo
Buildings 2025, 15(12), 1966; https://doi.org/10.3390/buildings15121966 - 6 Jun 2025
Viewed by 699
Abstract
The study examines how design quality, indoor air quality, and energy efficiency affect customer satisfaction in eco-friendly houses in Shanghai, China. Further, it examines how environmental awareness mediates community participation and resident satisfaction. A stratified sampling technique is used to collect the data [...] Read more.
The study examines how design quality, indoor air quality, and energy efficiency affect customer satisfaction in eco-friendly houses in Shanghai, China. Further, it examines how environmental awareness mediates community participation and resident satisfaction. A stratified sampling technique is used to collect the data from 742 eligible respondents in public and private eco-residential complexes. The results show that design, air quality, and energy efficiency improve customer satisfaction. At the same time, community engagement partially mediates these correlations, stressing the importance of social cohesion in enhancing residential area quality. Environmental awareness moderated the effects and boosted the happiness benefits of energy efficiency and indoor air quality. This research uses a comprehensive framework that includes psychological, environmental, and social components to make it stand out. Instead of studying green housing benefits in general, it accomplishes this inside China’s urban sustainability program. The results help policymakers, urban planners, and housing authorities make megacity green housing more desirable and livable. Full article
(This article belongs to the Special Issue Intelligent Multi-Criteria Decision-Making Methodologies in Building and Construction Management—2nd Edition)
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31 pages, 3565 KB  
Article
Sustainable Construction Material Selection Based on Novel Integrated CRIterion Free-Fall Time–SPHERicity of Alternative Decision-Making Model
by Miloš Gligorić, Zoran Gligorić, Suzana Lutovac and Svetlana Štrbac-Savić
Buildings 2025, 15(9), 1440; https://doi.org/10.3390/buildings15091440 - 24 Apr 2025
Viewed by 488
Abstract
As the civil industry, and especially the concrete industry, constantly advance and modernize, the usage of sustainable construction materials is becoming increasingly important. These materials represent one of the most significant components in the concept of the sustainable development of every company and [...] Read more.
As the civil industry, and especially the concrete industry, constantly advance and modernize, the usage of sustainable construction materials is becoming increasingly important. These materials represent one of the most significant components in the concept of the sustainable development of every company and industry. Underground mining, as a part of mining industry, largely applies sustainable materials to perform some of its technological operations. The optimal selection of sustainable construction materials is one of the key tasks for underground mining engineers. This paper proposes a novel integrated CRIFFT-SPHERA decision-making model for choosing the most suitable concrete mixture for supporting and backfilling activities in an underground mine. A total of ten concrete mixtures forms a set of alternatives which are evaluated with respect to four criteria. To validate the proposed MCDM model, an extensive numerical calculation procedure as well as comparative analysis are conducted through a hypothetical example. The obtained results confirm the extremely high degree of stability and reliability of the developed model. Also, the results are checked using sensitivity analysis based on changes in the values of the weight coefficients. In addition, the effectiveness of the developed model is verified through real-world problems where its application for solving these problems in various industries is accepted. This paper provides valuable insights for engineers dealing with problem of the construction of different concrete forms and structures, especially in underground areas, with fly ash as an element belonging to a group of sustainable construction materials. Full article
(This article belongs to the Special Issue Intelligent Multi-Criteria Decision-Making Methodologies in Building and Construction Management—2nd Edition)
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29 pages, 17900 KB  
Article
Multi-Criteria Analysis of Steel–Concrete–Steel Slab Performance: Dynamic Response Assessment Under Post-Fire Explosion
by Shijie Zhang, Zhenfu Chen, Yizhi Liu, Qiuwang Tao, Dan Wu and Pinyu Zou
Buildings 2025, 15(8), 1340; https://doi.org/10.3390/buildings15081340 - 17 Apr 2025
Viewed by 548
Abstract
Steel–concrete–steel (SCS) composite slabs are widely used in critical infrastructures such as nuclear power plants, where systematic performance evaluation through multiple criteria is crucial due to their safety functions. During their use, fires may occur due to fuel or gas leaks, leading to [...] Read more.
Steel–concrete–steel (SCS) composite slabs are widely used in critical infrastructures such as nuclear power plants, where systematic performance evaluation through multiple criteria is crucial due to their safety functions. During their use, fires may occur due to fuel or gas leaks, leading to explosions. This article uses ABAQUS 2020 finite element software and combines the different advantages of the implicit heat transfer algorithm and explosion display algorithm to establish a numerical simulation method for dynamic analysis of SCS slab under explosion after fire. Based on different fire conditions and the propagation laws of explosion shock waves, some key dynamic indicators and failure modes of the slab were studied. The results reveal progressive damage mechanisms with increasing fire duration, characterized by expanding damage areas, significant stress fluctuations, and increasing displacement rates. Additionally, the fire surface shows greater vulnerability than the back fire surface. The results provide multiple evaluation criteria for assessing structural performance, including temperature distribution, stress evolution, and damage patterns, which can support engineering decision-making in structural safety management. Full article
(This article belongs to the Special Issue Intelligent Multi-Criteria Decision-Making Methodologies in Building and Construction Management—2nd Edition)
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