A new approach of multi-criteria analysis for the evaluation and selection of sustainable transport investment projects under uncertainty: A case study

Mohagheghi, Vahid; Mousavi, Seyed Meysam; Aghamohagheghi, M.; Vahdani, Behnam

doi:10.2991/ijcis.2017.10.1.41

Cited by 32 publications

(15 citation statements)

References 45 publications

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“…It can be observed that the best and the worst alternatives remain the same. However, the presented method has several advantages in comparison with the method of Ashtiani et al [38]: (1) the developed method applies Interval-Valued Pythagorean Fuzzy Set (IVPFS), one of the most powerful tools in dealing with uncertainty, to increase the 16 flexibility and ability of expressing and calculating the uncertainty in the decision problem; (2) the DMs are given a weight objectively based on the compromise solution method; and (3) the method uses an optimization model that simultaneously considers the deviation between attribute assessments and knowledge measure to address the weights of unknown criteria. This model utilizes all the available information in decision preferences and creates a comprehensive weighting approach.…”

Section:  mentioning

confidence: 99%

“…Despite all the efforts to model the uncertainty of a sustainable transportation evaluation problem in MCDM methods, most of them were based on classical fuzzy sets. In fact, there are few studies in the literature concerning sustainable transportation evaluation by using an extension of classical fuzzy sets (FSs) [12][13][14][15][16]. There is no any research carried out to discuss the problem by utilizing the Interval-Valued Pythagorean Fuzzy Set (IVPFS).…”

Section: Introductionmentioning

confidence: 99%

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A new decision approach for the sustainable transport investment selection based on the generalized entropy and knowledge measure under an interval-valued Pythagorean fuzzy environment

2019

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Finding the most suitable transport project is one of the most important tasks of transport planning. This task gets more complicated as the sustainable criteria get involved. In this paper, a new method of multi-criteria group decision-making with unknown attribute and expert weights is proposed to address the sustainable transport investment selection problem. To make the method more powerful in dealing with uncertain elements, an Interval-Valued Pythagorean Fuzzy (IVPF) set is used as a useful tool to handle uncertainty. First, a generalized entropy measure under an IVPF environment is introduced, which enables the method to determine the fuzziness of the attribute values, which are expressed by Interval-Valued Pythagorean Fuzzy Numbers (IVPFNs). To determine the fuzziness of IVPFNs with identical membership and nonmembership degrees, a generalized knowledge measure of the IVPFNs is also introduced. Based on this measure and considering the deviation among attribute assessments, a new optimization model is presented to obtain unknown attribute weights. In addition, based on the extension of the VIKOR method, a novel algorithm is introduced to determine the unknown expert weights. Finally, to show the efficiency of the proposed methods a real case study is considered. Technology where he taught several graduate and under graduate courses, supervised 8 PhD and more than 65 master students. Prof. Hashemi's area of research includes Graph Theory and Applications, Algorithm and Complexity, Network and Combinatorial Optimization, Operation Research, and Transportation Systems, in which he has published more than 150 peer reviewed journal and conference papers presented nationally and internationally. Hashemi was involved in several industrial projects including design and managing the enterprise application safety systems, designing integrated public transportation network for Tehran, introducing the BRT system in collaboration with ITDP (Institute for Transportation and Development) and Iranian national ITS Architecture. Prof. Hashemi has held various academic positions including Dean of He has obtained the outstanding rank as the top 1% scientist and researcher in the world elite 32 group since 2014. He has published 4 books, 23 book chapters, and more than 1000 journal and conference papers.

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Section:  mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A new decision approach for the sustainable transport investment selection based on the generalized entropy and knowledge measure under an interval-valued Pythagorean fuzzy environment

2019

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“…In this section to demonstrate the application steps of the introduced approach in real-world problems, an existing sustainable infrastructure project evaluation and selection problem in the literature (Mohagheghi, Mousavi, Aghamohagheghi, & Vahdani, 2017b) is adopted and solved by using the presented method. Additionally, the case deals with selecting infrastructure projects in a multi-criteria process.…”

Section: Case Studymentioning

confidence: 99%

Sustainable Infrastructure Project Selection by a New Group Decision-Making Framework Introducing Moras Method in an Interval Type 2 Fuzzy Environment

Mohagheghi

Mousavi

Antuchevičienė

et al. 2019

International Journal of Strategic Property Management

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Project management is a process that is involved with making important decisions under uncertainty. In project management often the existing data is limited and vague. Sustainable project selection has a multi-criteria evaluation nature which calls for attending to various often conflicting factors under vagueness. To deal with sustainable project selection several important factors should be properly considered. In this paper, in order to provide a new multi-criteria project selection method, a novel last aggregation method is presented. This method has several main novelties. First, to address uncertainty interval type 2 fuzzy sets (IT2FSs) are used. Second, the importance of criteria is investigated by using IT2F entropy. Third, a novel index for decision making is presented that has the merits of ratio system in MOORA and COPRAS, named MORAS. Fourth, the weights of decision makers are computed according to the obtained judgments and the weights are employed to aggregate the results. Fifth, the defuzzification is carried out in the last step of the process by means of a new IT2F ranking method. To present the applicability of the method, it is used in an existing case study in the literature and the outcomes are presented.

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“…Therefore, the fuzzy MCDM (FMCDM) approaches are obtained to assess the candidates in an uncertain environment (Giti-navard, Makui, & Jabbarzadeh, 2016;Gitinavard, Mousavi, & Vahdani, 2016;Gitinavard, & Zarandi, 2016). Furthermore, establishing a group of specialists for appraising the problem under imprecise information is lead the FMCDM approaches to fuzzy multi-criteria group decision-making (FMCGDM) approaches (e.g., Mohagheghi, Mousavi, Aghamohagheghi, & Vahdani, 2017;Mohagheghi, Mousavi, Vahdani, & Siadat, 2017;Mohagheghi, Mousavi, & Vahdani, 2017a, 2017bZolfaghari & Mousavi, 2018).…”

Section: Introductionmentioning

confidence: 99%

Solving Construction Project Selection Problem by a New Uncertain Weighting and Ranking Based on Compromise Solution With Linear Assignment Approach

Davoudabadi

Mousavi

Šaparauskas

et al. 2019

Journal of Civil Engineering and Management

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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.

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A new approach of multi-criteria analysis for the evaluation and selection of sustainable transport investment projects under uncertainty: A case study

Cited by 32 publications

References 45 publications

A new decision approach for the sustainable transport investment selection based on the generalized entropy and knowledge measure under an interval-valued Pythagorean fuzzy environment

A new decision approach for the sustainable transport investment selection based on the generalized entropy and knowledge measure under an interval-valued Pythagorean fuzzy environment

Sustainable Infrastructure Project Selection by a New Group Decision-Making Framework Introducing Moras Method in an Interval Type 2 Fuzzy Environment

Solving Construction Project Selection Problem by a New Uncertain Weighting and Ranking Based on Compromise Solution With Linear Assignment Approach

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