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A Multi-criteria Group Decision Making Model for Selection of Green Building Project

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1188))

Abstract

The green building concept is recognized as a sustainable building strategy due to its benefits. Careful selection of sustainable building project has been identified as the easiest way to impose the sustainable building principles. The frame of building information modeling concerns all aspects of building design, construction and operations. In this respect, the current paper deals with design problems related to the selection of the most suitable project for building by group decision making. The proposed combinatorial optimization model for selection is based on the formulation of utility function considering some evaluation criteria corresponding to the green building concept. The experts’ opinion is taken into account by weighted coefficients. These coefficients express the importance of experts’ opinions corresponding to their experience and knowledge. The practical applicability of the proposed modeling approach is demonstrated in the case of selection of the most appropriate building project among a predefined set of projects. A project evaluation is done by using the given criteria and a group of experts. The final decision for the selection of the building project is a result of the aggregated evaluation of all experts. Each expert takes part in a group decision both through evaluations and the contribution expressed by weighted coefficients for the level of expertise and knowledge. The results showed that using weights for experts influence the final aggregate group decision for the selection of the project for green building.

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Correspondence to Daniela Borissova .

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Borissova, D. (2020). A Multi-criteria Group Decision Making Model for Selection of Green Building Project. In: Ofluoglu, S., Ozener, O., Isikdag, U. (eds) Advances in Building Information Modeling. EBF 2019. Communications in Computer and Information Science, vol 1188. Springer, Cham. https://doi.org/10.1007/978-3-030-42852-5_11

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  • DOI: https://doi.org/10.1007/978-3-030-42852-5_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-42851-8

  • Online ISBN: 978-3-030-42852-5

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