Abstract
Concrete, one of the sources of energy consumption and carbon emissions, is widely used in the construction industry. The selection of concrete materials raises the question of energy sustainability and turns it into a complex multicriteria decision-making (MCDM) issue. To address this, we present an MCDM framework based on the intuitionistic linguistic hybrid weighted logarithmic averaging distance (ILHWLAD). To begin with, the intuitionistic linguistic numbers are used to deal with the uncertainty and fuzziness of the decision-making process. In addition, in view of the significance and the ordered position of the input arguments, an intuitionistic linguistic hybrid weighted logarithmic averaging distance (ILHWLAD) operator is defined. We, then, initiate the criteria system and present the MCDM framework based on the ILHWLAD to select the finest concrete. A case study involving four alternative materials, namely, autoclaved aerated concrete (AAC), hollow concrete blocks (HCB), expanded polystyrene (EPS), and lime hemp concrete (LHC), is presented to verify the scientificity of the framework.
Highlights
It is difficult to use specific data in the analysis of the performance and functionality of specific concrete materials
The energy of concrete material varies Journal of Mathematics according to levels of technology, production conditions, and so on [9]. e intuitionistic linguistic number (ILN) is an effective way to resolve these issues, and it has been frequently used in different fields [10], e.g., energy performance contracting [11], strategy decisions [12], the selection of offshore wind farms [13], and assessment of green building insulation materials [14]
We proposed an HWLAD-multicriteria decisionmaking (MCDM) framework for the selection of the finest concrete materials under an intuitionistic linguistic fuzzy environment. e four alternative concrete materials lime hemp concrete (LHC), aerated concrete (AAC), hollow concrete blocks (HCB), and expanded polystyrene (EPS) were evaluated using six criteria, which encompass energy sustainability, economic performance, comfort, and safety
Summary
It is difficult to use specific data in the analysis of the performance and functionality of specific concrete materials. E intuitionistic linguistic number (ILN) is an effective way to resolve these issues, and it has been frequently used in different fields [10], e.g., energy performance contracting [11], strategy decisions [12], the selection of offshore wind farms [13], and assessment of green building insulation materials [14]. We can utilize ILN to characterize the grades of each criterion for concrete materials because the information is hard to measure with specific values. To address the defects of ILWLAD and ILOWLAD, we introduce a new intuitionistic linguistic hybrid weighted logarithmic average distance (ILHWLAD) operator for better handling of the data
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