Evaluating the sustainable mining contractor selection problems: An imprecise last aggregation preference selection index method

Borujeni, Mohammad Panahi; Gitinavard, Hossein

doi:10.1016/j.jsm.2017.12.006

Cited by 44 publications

(14 citation statements)

References 46 publications

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“…Hence, in SPS, it will be more advantageous to collect the data sets for the importance degree of each criterion and performance of each alternative using a fuzzy or linguistic-based technique in order to analyze the projects and select the best one. In essence, developing a framework which can deal with ambiguity, vagueness and imprecision is beneficial (Borujeni & Gitinavard, 2017). Fuzzy set theory, developed by Zadeh (1978) as a method to cope with the problem of exact data collection in real world, has been widely used in decision making (Ebrahimnejad et al, 2017;Erdogan et al, 2017;Gitinavard et al, 2017;Govindan et al, 2019;Nguyen et al, 2018;N.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Decision Support System for Sustainable Construction Project Selection: An Integrated FPP-Fis Model

Fallahpour

Wong

Rajoo

et al. 2020

Journal of Civil Engineering and Management

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Sustainability has become a key concern for project selection in construction industries. Determining the best sustainable project based on various sustainability attributes is a very complicated decision. Accordingly, developing a suitable decision support framework can be very helpful for decision makers to attain planned business goals and complete projects at the right time with good quality. This research develops a decision support model which helps managers to understand the concept of sustainability in construction project selection and choose the best project using a new integrated Multi-Criteria Decision Making (MCDM) approach under uncertainty by integrating Fuzzy Preference Programming (FPP) as a modification of Fuzzy Analytical Hierarchy Process (FAHP), with Fuzzy Inference System (FIS) as a fuzzy rulebased expert system. In the first phase of the research, fifteen sustainability attributes were selected. In the second phase, the final weight of each attribute was computed by using FPP. In the last phase, the most appropriate project was selected by running the weighted FIS. The results showed that Project 3 (P3) is the best project. Finally, two different evaluative tests were also applied to verify the validity and robustness of the developed model.

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Section: Introductionmentioning

confidence: 99%

A Fuzzy Decision Support System for Sustainable Construction Project Selection: An Integrated FPP-Fis Model

Fallahpour

Wong

Rajoo

et al. 2020

Journal of Civil Engineering and Management

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“…Therefore, different sets of evaluative attributes for contractor selection with different scenarios are needed. During last two decades, many efforts have been paid to identify selection attributes and construct comprehensive contractor selection methods with different applications [8,10,18,19,23,24,26,28,67,68].…”

Section: Evaluative Attributes For Green Contractor Selectionmentioning

confidence: 99%

“…Alhumaidi [20] utilized linguistic variables to construct a fuzzy-logic based multiple attributes group decision-making method. Most recently, in viewing of common phenomena of decision hesitancy in complex decision-making processes [21,22], Borujeni and Gitinavard [23] studied a group decision-making approach based on hesitant fuzzy preference relations.…”

Section: Introductionmentioning

confidence: 99%

Tackling Complexity in Green Contractor Selection for Mega Infrastructure Projects: A Hesitant Fuzzy Linguistic MADM Approach with considering Group Attitudinal Character and Attributes’ Interdependency

Zhang

Liang

2018

Complexity

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Continuous environmental concerns regarding construction industry have been driving general constructors of mega infrastructure projects to incorporate green contractors. Although conventional multiple attributes decision-making (MADM) methodologies have provided feasible ways to select contractor, high complexity in scenarios of megaprojects still challenges existing MADM methods in concurrently accommodating three key issues of decision hesitancy, attributes interdependency, and group attitudinal character. To elicit decision-makers’ hesitant fuzzy assessments more objectively and comprehensively, we define an expression tool called interval-valued dual hesitant fuzzy uncertain unbalanced linguistic set (IVDHF_UUBLS) and develop aggregation operators through its operations. To exploit attributes interdependency, we establish a synthesized attributes’ weighting model to fuse an attributes interdependency-based weighting vector and an argument-dependent weighting vector, which are, respectively, derived through Decision-Making and Trial Evaluation Laboratory (DEMATEL) technique and maximizing deviation method. To effectively utilize decision-makers’ group attitudinal characters, we also develop a TOPSIS-based method to rationally transform group ideal attitudes into order-inducing vectors. On the strength of the above methods, an integrated MADM approach is then constructed. Finally, illustrative case study and experiments are conducted to validate our approach.

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“…M CDM has been paid close attention in information systems in recent years [1]- [3]. The applications of MCDM have been widely discussed in many fields, such as supplier selection [4], [5], fault diagnosis [6], [7], and heartcare management [8], [9]. To make the decision outcome reliable, some techniques are applied to its optimization processes, including analytical hierarchy process (AHP) [10]- [12], decision making trial and evaluation laboratory (DEMATEL) method [13], [14], and technique for order preference by similarity to an ideal solution (TOPSIS) method [15]- [17].…”

Section: Introductionmentioning

confidence: 99%

A Generalized Golden Rule Representative Value for Multiple-Criteria Decision Analysis

Liu

Xiao

Lin

et al. 2021

IEEE Trans. Syst. Man Cybern, Syst.

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Multicriteria decision analysis evaluates multiple conflicting criteria in decision making, but conflicting criteria are typical in evaluating options. As the existing ordering operations involved in multicriteria decision making cannot easily be implemented with intervals, we assume that scalar representative values with intervals can effectively avoid this issue. To deal with interval-valued criteria, we propose a generalized golden rule representative value approach, which involves the sigmoid function of backpropagation neural networks to tune parameters. Our approach considers the uncertainties and side effects of the interval variables to improve individual scalar representative values. Based on numerical examples, we address the effectiveness of the proposed approach, and we provide a specific application concerning multicriteria decision making with interval criteria satisfaction.

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Evaluating the sustainable mining contractor selection problems: An imprecise last aggregation preference selection index method

Cited by 44 publications

References 46 publications

A Fuzzy Decision Support System for Sustainable Construction Project Selection: An Integrated FPP-Fis Model

A Fuzzy Decision Support System for Sustainable Construction Project Selection: An Integrated FPP-Fis Model

Tackling Complexity in Green Contractor Selection for Mega Infrastructure Projects: A Hesitant Fuzzy Linguistic MADM Approach with considering Group Attitudinal Character and Attributes’ Interdependency

A Generalized Golden Rule Representative Value for Multiple-Criteria Decision Analysis

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