Multi-criteria decision making with fuzzy linguistic preference relations

Chen, Ying-Hsiu; Wang, Tien-Chin; Wu, Ching‐Yuan

doi:10.1016/j.apm.2010.09.009

Cited by 84 publications

(52 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For getting the final decision result, current ordering based decision making methods are mainly from the information aggregation point of view, i.e., how to combine all the decision makers' opinions to obtain a final ordering or evaluation. For multi-criteria decision making, the judgments provided by decision makers for different criteria are usually assumed to preference relations in the same form [7,20] or similar forms [21,22]. While in many real cases, the provided preference relations are always in different forms which can be illustrated using the following example.…”

Section: Examplementioning

confidence: 99%

“…Wang et al [7,20,[78][79][80] proposed a hybrid method, called fuzzy linguistic preference relations, for representing preference relation under linguistic environments by expressing linguistic terms as fuzzy numbers ( , , ) L M R ij ij ij P P P , which can be seen as a special case of linguistic preference relation.…”

Section: Decision Making Based On Preference Relationsmentioning

confidence: 99%

“…Additionally, there are always many conditions or criteria in real decision making problems, not all of which can be satisfied simultaneously due to the uncertainty and complexity involved [7]. Sometimes, it may not always be feasible or realistic to acquire exact judgment on each attribute due to time restriction, lack of knowledge or data, limited expertise related to the problem domain and so on.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Ordering based decision making – A survey

et al. 2013

View full text Add to dashboard Cite

A B S T R A C TDecision making is the crucial step in many real applications such as organization management, financial planning, products evaluation and recommendation. Rational decision making is to select an alternative from a set of different ones which has the best utility (i.e., maximally satisfies given criteria, objectives, or preferences). In many cases, decision making is to order alternatives and select one or a few among the top of the ranking. Orderings provide a natural and effective way for representing indeterminate situations which are pervasive in commonsense reasoning. Ordering based decision making is then to find the suitable method for evaluating candidates or ranking alternatives based on provided ordinal information and criteria, and this in many cases is to rank alternatives based on qualitative ordering information. In this paper, we discuss the importance and research aspects of ordering based decision making, and review the existing ordering based decision making theories and methods providing future research directions.

show abstract

Section: Examplementioning

confidence: 99%

Section: Decision Making Based On Preference Relationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Ordering based decision making – A survey

et al. 2013

View full text Add to dashboard Cite

show abstract

“…While technical papers remain an important means by which innovation and technology researchers disseminate their ideas, they are also a way for scientific and technological achievements to be transformed into productivity [1]. Cost and time effectiveness are issues common to much of this work [2,18,32].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of scientific publications with hesitant fuzzy uncertain linguistic and semantic information

Xing

Huang

2015

IFS

View full text Add to dashboard Cite

Abstract. Scientific and technological papers play a fundamental role in the scientific and technological innovation of countries. The quality control of scientific and technological articles is vital to the journals and management of personnel. This paper investigates multiple attribute decision-making problems with the application of hesitant fuzzy uncertain linguistic information. Motivated by the ideal traditional I-COA operator, an induced hesitant fuzzy uncertain linguistic correlated averaging (IHFULCA) operator is developed. The IHFULCA operator was used to develop approaches to solve hesitant fuzzy uncertain linguistic multiple attribute decision-making problems. Finally, a practical example for evaluating the academic value of scientific and technological papers is provided to verify the developed approach and demonstrate its practicality and effectiveness.

show abstract

“…In addition, the human judgments made in the decision process involve inherent subjectivity and are often infeasible and inconsistent. Therefore, it is more suitable to introduce data using fuzzy numbers instead of crisp numbers 9 . Because of the above-mentioned pitfalls, alternative methods for improving classical AHP have been developed by several authors by employing fuzzy set theory.…”

Section: Introductionmentioning

confidence: 99%

Selecting appropriate ERP software using integrated fuzzy linguistic preference relations – fuzzy TOPSIS method

Çakır¹

2016

IJCIS

View full text Add to dashboard Cite

Due to the high uncertainty of business environment, the complexity and diversity of enterprise resource planning (ERP) projects and conflicting assessment criteria, appropriate ERP software selection can be viewed as a multi-criteria decisionmaking (MCDM) problem. Among the MCDM methods, extent analysis method (EAM) has been employed in many applications due to its computational simplicity. However, in EAM, inconsistency rises as the numbers of criteria or alternatives increase. In order to address this inconsistency problem, fuzzy linguistic preference relations (FLPR) has been proposed to obtain consistent solutions in the decision-making processes. This study proposes a robust ERP selection framework where the weights of the evaluation criteria are computed through FLPR and the ranking of the alternative ERP systems is obtained via Fuzzy TOPSIS. A real life application has been executed in a Turkish wholesale food company.

show abstract

Multi-criteria decision making with fuzzy linguistic preference relations

Cited by 84 publications

References 33 publications

Ordering based decision making – A survey

Ordering based decision making – A survey

Evaluation of scientific publications with hesitant fuzzy uncertain linguistic and semantic information

Selecting appropriate ERP software using integrated fuzzy linguistic preference relations – fuzzy TOPSIS method

Contact Info

Product

Resources

About