A multi-criteria decision-support framework for optimising intelligence in high-performance buildings

Meryem Laraba; Mohamed Derradji

doi:10.35784/bud-arch.8606

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Published: 2026-07-31

DOI: https://doi.org/10.35784/bud-arch.8606

Issue Vol. 25 No. 3 (2026)

Articles

A multi-criteria decision-support framework for optimising intelligence in high-performance buildings
Meryem Laraba, Mohamed Derradji

26036
Residential satisfaction, social capital and place attachment. Case study: Sahar Residential Tower, Tehran
S.Narges Mousavi, Islam Karami

26037
BIM–AI integration in architecture: a workflow-based review
Semih Bayer, Sema Alaçam, Orkan Zeynel Güzelci

26038
Computerized systems in the early-stage real estate development: a systematic literature review in the context of Construction 4.0
José Matheus Moraes Costa da Silva, Alberto Casado Lordsleem Júnior, Everton Gabriel Medeiros da Silva, Fagner José Coutinho de Melo

26039
Limited space and disaster awareness: a comparative analysis of curriculum transformation in interior architecture education
Betül Irem Tarakçı, Melih Kurnalı

26040
Peculiarities of preservation, protection and restoration of the urban heritage (on the example of small towns in Western Ukraine)
Zoriana Lukomska, Viktoriia Berbets, Diana Akparsheva

26041
Structural response of circular RC elements under nonlinear hereditary creep
Mukhlis Hajiyev, Ulviya Hajiyeva, Seymur Bashirzade, Baxrom Xasanov

26042

Authors

Meryem Laraba

meryem.laraba@univ-constantine3.dz

Department of Architecture; Faculty of Architecture and Urbanism; University of Constantine 3; Constantine

https://orcid.org/0000-0003-3148-7846

Mohamed Derradji

mohamed.derradji@univ-constantine3.dz

Department of Architecture; Faculty of Architecture and Urbanism; University of Constantine 3; Constantine

https://orcid.org/0009-0006-4443-2405

Abstract

This study proposes an exploratory decision-support approach aimed at optimising the performance, spatial quality, and intelligence of high-performance architectural spaces. The methodology combines a structured literature review with numerical modelling based on the Analytic Hierarchy Process (AHP). The analytical framework addresses diverse uses of architectural space and their conceptual foundations, enabling the development of a multidimensional model of building intelligence integrating technological, environmental, and human-centred criteria. Four groups of themes and associated indices were identified and validated through a questionnaire survey conducted with a panel of experts. The results reveal strong interdependencies between the evaluated criteria and confirm the coherence and robustness of the proposed framework. This is further supported by a satisfactory consistency ratio within the AHP model (CR = 7.2%), indicating the reliability of the decision-making structure. The findings highlight the importance of moving beyond automation toward adaptive, data-driven, and user-centred intelligent systems. The proposed approach addresses the lack of reliable decision-support tools in the early stages of high-performance building design and provides practical implications for cost estimation, spatial quality management, environmental strategies, communication systems, and the integration of smart and passive technologies.

Keywords:

high-performance buildings, smart architecture, exploratory approach, Analytic Hierarchy Process (AHP), decision-support framework

Sustainable Development Goal (SDG)

Good health and well-being
Clean water and sanitation
Affordable and clean energy
Industry, Innovation, Technology and Infrastructure
Sustainable cities and communities
Responsible consumption and production
Climate action
Life on land

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“A multi-criteria decision-support framework for optimising intelligence in high-performance buildings” (2026) Budownictwo i Architektura / Civil and Architectural Engineering, 25(3), p. 26036. doi:10.35784/bud-arch.8606.

A multi-criteria decision-support framework for optimising intelligence in high-performance buildings

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