A New Criterion for Soft Set Based Decision Making Problems under Incomplete Information

Alcantud, José Carlos R.; Santos‐García, Gustavo

doi:10.2991/ijcis.2017.10.1.27

Cited by 65 publications

(37 citation statements)

References 31 publications

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“…The idea of partial valuations should not be mistaken with the well-known notion of incomplete (fuzzy) soft sets [36,[43][44][45][46]. In the latter case, the parameterization has missing values.…”

Section: Remarkmentioning

confidence: 99%

Valuation Fuzzy Soft Sets: A Flexible Fuzzy Soft Set Based Decision Making Procedure for the Valuation of Assets

2017

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Zadeh's fuzzy set theory for imprecise or vague data has been followed by other successful models, inclusive of Molodtsov's soft set theory and hybrid models like fuzzy soft sets. Their success has been backed up by applications to many branches like engineering, medicine, or finance. In continuation of this effort, the purpose of this paper is to put forward a versatile methodology for the valuation of goods, particularly the assessment of real state properties. In order to reach this target, we develop the concept of (partial) valuation fuzzy soft set and introduce the novel problem of data filling in partial valuation fuzzy soft sets. The use of fuzzy soft sets allows us to quantify the qualitative attributes involved in an assessment context. As a result, we illustrate the effectiveness and validity of our valuation methodology with a real case study that uses data from the Spanish real estate market. The main contribution of this paper is the implementation of a novel methodology, which allows us to assess a large variety of assets where data are heterogeneous. Our technique permits to avoid the appraiser's subjectivity (exhibited by practitioners in housing valuation) and the well-known disadvantages of some alternative methods (such as linear multiple regression).

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Section: Remarkmentioning

confidence: 99%

Valuation Fuzzy Soft Sets: A Flexible Fuzzy Soft Set Based Decision Making Procedure for the Valuation of Assets

2017

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“…The exploitation of soft sets and hybrid soft sets models in decision-making shows a great development in the recent years [18][19][20][21][22]. The utilization of soft rough sets models in decision-making shows a promising prospect.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Some Soft Rough Sets

2017

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Through the combination of different types of sets such as fuzzy sets, soft sets and rough sets, abundant hybrid models have been presented in order to take advantage of each other and handle uncertainties. A comparative study of relationships and interconnections of some existing hybrid models has been carried out. Some foundational properties of modified soft rough sets (MSR sets) are analyzed. It is pointed out that MSR approximation operators are some kinds of Pawlak approximation operators, whereas approximation operators of Z-soft rough fuzzy sets are equivalent to approximation operators of rough fuzzy sets. The relationships among F-soft rough fuzzy sets, M-soft rough fuzzy sets and Z-soft rough fuzzy sets are surveyed. A new model called soft rough soft sets has been provided as the generalization of F-soft rough sets, and its application in group decision-making has been studied. Various soft rough sets models show great potential as a tool to solve decision-making problems, and a depth study of the connections among these models contributes to the flexible application of soft rough sets based decision-making approaches.

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“…Alcantud [17][18][19] gave a novel approach to the problems of fuzzy soft sets based decision-making. Alcantud and Santos-Garcia [20,21] produced a completely new approach to soft set based decision-making problems when information is incomplete. They also proposed and compared an algorithmic solution with previous approaches in the literature in [20].…”

Section: Introductionmentioning

confidence: 99%

“…Alcantud and Santos-Garcia [20,21] produced a completely new approach to soft set based decision-making problems when information is incomplete. They also proposed and compared an algorithmic solution with previous approaches in the literature in [20]. Feng et al [22] gave the novel idea of rough soft sets by combining the Pawlak rough sets and soft sets.…”

Section: Introductionmentioning

confidence: 99%

A New Multi-Attribute Decision-Making Method Based on m-Polar Fuzzy Soft Rough Sets

2017

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Abstract:We introduce notions of soft rough m-polar fuzzy sets and m-polar fuzzy soft rough sets as novel hybrid models for soft computing, and investigate some of their fundamental properties. We discuss the relationship between m-polar fuzzy soft rough approximation operators and crisp soft rough approximation operators. We also present applications of m-polar fuzzy soft rough sets to decision-making.

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A New Criterion for Soft Set Based Decision Making Problems under Incomplete Information

Cited by 65 publications

References 31 publications

Valuation Fuzzy Soft Sets: A Flexible Fuzzy Soft Set Based Decision Making Procedure for the Valuation of Assets

Valuation Fuzzy Soft Sets: A Flexible Fuzzy Soft Set Based Decision Making Procedure for the Valuation of Assets

A Comparative Study of Some Soft Rough Sets

A New Multi-Attribute Decision-Making Method Based on m-Polar Fuzzy Soft Rough Sets

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