Abstract
Selecting a suitable construction project is a significant issue for contractors to decrease their costs. In real cases, the imprecise and uncertain information lead to decisions made based on vagueness. Fuzzy sets theory could help decision makers (DMs) to address incomplete information. However, this article develops a new integrated multi-criteria group decision-making model based on compromise solution and linear assignment approaches with interval-valued intuitionistic fuzzy sets (IVIFSs). IVIFSs by presenting a membership and non-membership degree for each candidate based on appraisement criteria could decrease the vagueness of selection decisions. The proposed algorithm involves a new decision process under uncertain conditions to determine the importance of criteria and DMs, separately. In this regard, no subjective or additional information is needed for this process; only the input information required is an alternative assessment matric. In this approach, weights of criteria and DMs are specified based on novel indexes to increase the reliability of obtained results. In this respect, the criteria’ weights are computed regarding entropy concepts. The basis for calculating the weight of each DM is the distance between each DM and an average of the DMs’ community. Furthermore, the linear assignment model is extended to rank the candidates. A case study about the construction project selection problem (CPSP) is illustrated to indicate the application of proposed model.
Highlights
The fuzzy sets theory was first introduced by Zadeh (1965); this theory and its developments have been widely considered for extending the decision-making techniques to solve the selection problems based on uncertain input parameters
These fuzzy sets theories are provided in some fields, such as artificial intelligence (Greco, Matarazzo, & Giove, 2011; Keramitsoglou et al, 2013), pattern recognition (Melin & Castillo, 2013, 2014), management (Doria, 2012; Paksoy, Pehlivan, & Kahraman, 2012), and decision making (Moradi, Mousavi, & Vahdani, 2017, 2018; Qin & Liu, 2013)
The interval-valued intuitionistic fuzzy sets (IVIFSs) could help decision makers (DMs) to cope with imprecise information and vague situations by presenting the linguistic terms instead of crisp values
Summary
The fuzzy sets theory was first introduced by Zadeh (1965); this theory and its developments have been widely considered for extending the decision-making techniques to solve the selection problems based on uncertain input parameters. Further- interval-valued intuitionistic MCGDM approach based on more, establishing a group of specialists for appraising the compromise solution method and linear assignment modproblem under imprecise information is lead the FMCDM el to solve the CPSP In this regard, criteria weights and approaches to fuzzy multi-criteria group decision-mak- relative importance of experts are determined based on ing (FMCGDM) approaches Based on the judgment of each DM, positive ideal rating (PIR) and negative ideal rating (NIR) are assigned to each criterion Calculations of these numbers vary according to the nature of the criteria. These indices are calculated according to Eqns (14)–. A variety of dispersion around the average matrix for two alternatives
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