The stochastıc vikor method and its use in reverse logistic option selection problem

Aydoğan, Emel Kızılkaya; Özmen, Mihrimah

doi:10.1051/ro/2016027

Cited by 13 publications

(5 citation statements)

References 64 publications

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“…In real managements, especially for MADM, the attributes are often uncertain information, which is typically characterized by fuzzy information or stochastic information [32][33][34][35]. Of course, the most complex situation is with fuzzy information and stochastic information, simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Multiple Attribute Decision-Making Methods Based on Normal Intuitionistic Fuzzy Interaction Aggregation Operators

Лю¹

2017

Symmetry

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Normal intuitionistic fuzzy numbers (NIFNs), which combine the normal fuzzy number (NFN) with intuitionistic number, can easily express the stochastic fuzzy information existing in real decision making, and power-average (PA) operator can consider the relationships of different attributes by assigned weighting vectors which depend upon the input arguments. In this paper, we extended PA operator to process the NIFNs. Firstly, we defined some basic operational rules of NIFNs by considering the interaction operations of intuitionistic fuzzy sets (IFSs), established the distance between two NIFNs, and introduced the comparison method of NIFNs. Then, we proposed some new aggregation operators, including normal intuitionistic fuzzy weighted interaction averaging (NIFWIA) operator, normal intuitionistic fuzzy power interaction averaging (NIFPIA) operator, normal intuitionistic fuzzy weighted power interaction averaging (NIFWPIA) operator, normal intuitionistic fuzzy generalized power interaction averaging (NIFGPIA) operator, and normal intuitionistic fuzzy generalized weighted power interaction averaging (NIFGWPIA) operator, and studied some properties and some special cases of them. Based on these operators, we developed a decision approach for multiple attribute decision-making (MADM) problems with NIFNs. The significant characteristics of the proposed method are that: (1) it is easier to describe the uncertain information than the existing fuzzy sets and stochastic variables; (2) it used the interaction operations in part of IFSs which could overcome the existing weaknesses in operational rules of NIFNs; (3) it adopted PA operator which could relieve the influence of unreasonable data given by biased decision makers; and (4) it made the decision-making results more flexible and reliable because it was with generalized parameter which could be regard as the risk attitude value of decision makers. Finally, an illustrative example is given to verify its feasibility, and to compare with the existing methods.Keywords: power average (PA); normal intuitionistic fuzzy number (NIFN); normal intuitionistic fuzzy power interaction averaging (NIFPIA) operator; interaction operations; multiple attribute decision-making (MADM)

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Section: Introductionmentioning

confidence: 99%

Multiple Attribute Decision-Making Methods Based on Normal Intuitionistic Fuzzy Interaction Aggregation Operators

Лю¹

2017

Symmetry

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“…The improved approach can be implemented with many other logistics decision problems such as: determination of logistics center location, supplier selection, logistics service provider evaluation, route selection of multimodal transportation network, etc. In addition, the application of improved TODIM in the stochastic [49,50] and fuzzy environment, integration and comparison with other methods can be considered as a topic for future research.…”

Section: Resultsmentioning

confidence: 99%

Logistics competitiveness of OECD countries using an improved TODIM method

Özmen

2019

Sādhanā

Self Cite

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The Organization for Economic Cooperation and Development (OECD) provides a forum where governments can work together to increase the global welfare and to seek solutions to common problems through economic growth, where logistics plays an important role and contributes to financial stability. Evaluation of the logistics competitiveness of countries is a technical decision-making issue involving a variety of criteria. Most importantly, these criteria usually conflict with each other and they often act and react upon one another. As in logistics competitiveness as well as in many decision-making problems, the relationships among criteria are interdependent. Moreover, different dimensions and criteria weights also affect the evaluation results. By considering these situations, in order to handle these criteria interactions, Mahalanobis distance (MD) based TODIM (an acronym in Portuguese for Interactive and Multicriteria Decision Making) method has been developed and it has been applied to evaluate the logistics competitiveness of the OECD countries. Evaluation of the correlation between criteria develops the consideration outcomes (regarding sorting) to a certain degree with the traditional TODIM method.

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“…SMAA‐3 (Lahdelma and Salminen, ) is an ELECTRE III extension. SMAA‐TRI and SMAA‐PROMETHEE are extensions for the methods ELECTRE TRI and PROMETHEE (Tervonen et al., ; Corrente et al., ), and SMAA‐TOPSIS and SMAA‐VIKOR are extensions of the compromise methods TOPSIS and VIKOR (Okul et al., ; Aydogan and Ozmen, ). Recently, Zhang et al.…”

Section: Resultsmentioning

confidence: 99%

Techniques to model uncertain input data of multi‐criteria decision‐making problems: a literature review

Pelissari

Oliveira

Abackerli³

et al. 2018

Int Trans Operational Res

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There are a few studies in the literature regarding possible types of uncertainty in input data of multi-criteria decision making (MCDM) or multi-criteria decision analysis (MCDA) problems and the techniques employed to deal with each of them. Therefore, the aim of this study is to identify the different types of uncertainty that occur in input data of MCDM/MCDA problems and the most appropriate techniques to deal with each one of these uncertainty types. In this paper, a comprehensive literature review is presented in order to meet this objective. We selected and summarized 134 international journal articles. They were analyzed based on the type of data with uncertainty, the type of uncertainty, and the technique used to model it. We identified three distinct types of uncertainty in input data of MCDM/MCDA problems, namely (i) uncertainty due to ambiguity, (ii) uncertainty due to randomness, and (iii) uncertainty due to partial information. We identified a new generation of fuzzy approaches including Type-2, intuitionistic, and hesitant fuzzy sets (FSs), which are used to model these types of uncertainty alongside other approaches such as traditional FSs theory, probability theory, evidential reasoning theory, rough set theory, and grey numbers. Finally, a framework that indicates techniques used in different decision-making contexts under uncertainty is proposed.

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The stochastıc vikor method and its use in reverse logistic option selection problem

Cited by 13 publications

References 64 publications

Multiple Attribute Decision-Making Methods Based on Normal Intuitionistic Fuzzy Interaction Aggregation Operators

Multiple Attribute Decision-Making Methods Based on Normal Intuitionistic Fuzzy Interaction Aggregation Operators

Logistics competitiveness of OECD countries using an improved TODIM method

Techniques to model uncertain input data of multi‐criteria decision‐making problems: a literature review

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