Group decision making systems using group recommendations based on interval fuzzy preference relations and consistency matrices

Chen, Shyi‐Ming; Cheng, Shou-Hsiung; Lin, Tsung-En

doi:10.1016/j.ins.2014.11.027

Cited by 78 publications

(38 citation statements)

References 24 publications

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“…When dealing with the results of group decision making, the consistency of the decision-makers must be taken into account. In Chen et al [19], interval fuzzy preference relations and the consistency degree of iterations are adopted to solve subjective weights. Compared to traditional methods, this approach has two advantages: (1) It considers the consistency analysis of an individual and group, so that the consistency is constantly revised and reaches a predefined threshold through an iteration.…”

Section: Fuzzy Preference Relations and Consistency Degreementioning

confidence: 99%

Research on a Decision-making Model for Service Restoration in a Smart Distribution Network

Yuan¹,

Li²

2017

Open Cyber

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Abstract:In order to restore power to out-of-service areas quickly, this paper proposes a new service restoration decision-making algorithm for a distribution network. First, using heuristic rules, a candidate service restoration scheme set is generated. Considering the target of service restoration, five evaluation indices are introduced, including the quantities of restored load and transferred load, the margin of load capacity, the rate of load balancing, and the switching times of circuit breakers. Second, because of the problem of fuzzy measure identification, interaction between attributes, and the requirements for consistency with group decision making, this study defines the Shapley value identification method based on the Mahalanobis-Taguchi system and interval fuzzy preference relations. The fuzzy measure is obtained by the Shapley value, and the decision-making model is constructed by the Choquet integral with φs transformation function. Finally, an example application proves that the method is feasible and effective for decision making. Compared with the other method, the results verify the superiority of the decision process and show that it is consistent with the real conditions of post-fault restoration in a smart distribution network.

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Section: Fuzzy Preference Relations and Consistency Degreementioning

confidence: 99%

Research on a Decision-making Model for Service Restoration in a Smart Distribution Network

Yuan¹,

Li²

2017

Open Cyber

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“…, h m ) T be the weight vector of experts, where P m k¼1 h k ¼ 1; h k P 0 and h k demonstrates the importance degree of expert e k in the decision process. A fuzzy preference relation is defined as follows [9,16,44]. The preference information on X is described by a fuzzy preference relation R & X Â X, R = (r ij ) nÂn , with membership function l R :X Â X ?…”

Section: Preliminariesmentioning

confidence: 99%

“…Group decision making (GDM) [9,13,14,18,21,24,35] is a procedure of drawing on the combined wisdom and experience of experts from different domains to rank a finite number of alternatives. Reciprocal preference relations [21,23,27,34,39] are commonly used to represent decision-makers (DMs)' preferences over a set of possible alternative solutions, and have received considerable research attention in the past decades.…”

Section: Introductionmentioning

confidence: 99%

A chi-square method for priority derivation in group decision making with incomplete reciprocal preference relations

Chen

et al. 2015

Information Sciences

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a b s t r a c tThis paper proposes a chi-square method (CSM) to obtain a priority vector for group decision making (GDM) problems where decision-makers' (DMs') assessment on alternatives is furnished as incomplete reciprocal preference relations with missing values. Relevant theorems and an iterative algorithm about CSM are proposed. Saaty's consistency ratio concept is adapted to judge whether an incomplete reciprocal preference relation provided by a DM is of acceptable consistency. If its consistency is unacceptable, an algorithm is proposed to repair it until its consistency ratio reaches a satisfactory threshold. The repairing algorithm aims to rectify an inconsistent incomplete reciprocal preference relation to one with acceptable consistency in addition to preserving the initial preference information as much as possible. Finally, four examples are examined to illustrate the applicability and validity of the proposed method, and comparative analyses are provided to show its advantages over existing approaches.

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“…that are valuable to the user [1,2]. Content-based [3,4] or collaborative filtering(CF) [5] techniques are commonly used techniques.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy prototype classifier based on items and its application in recommender system

Mei¹,

Gong²,

Li³

2017

IJCIS

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Currently, recommender systems (RS) are incorporating implicit information from social circle of the Internet. The implicit social information in human mind is not easy to reflect in appropriate decision making techniques. This paper consists of 2 contributions. First, we develop an item-based prototype classifier (IPC) in which a prototype represents a social circle's preferences as a pattern classification technique. We assume the social circle which distinguishes with others by the items their members like. The prototype structure of the classifier is defined by two2-dimensional matrices. We use information gain and OWA aggregator to construct a feature space. The item-based classifier assigns a new item to some prototypes with different prototypicalities. We reform a typical data set-Iris data set in UCI Machine Learning Repository to verify our fuzzy prototype classifier. The second proposition of this paper is to give the application of IPC in recommender system to solve new item cold-start problems. We modify the dataset of MovieLens to perform experimental demonstrations of the proposed ideas.

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Group decision making systems using group recommendations based on interval fuzzy preference relations and consistency matrices

Cited by 78 publications

References 24 publications

Research on a Decision-making Model for Service Restoration in a Smart Distribution Network

Research on a Decision-making Model for Service Restoration in a Smart Distribution Network

A chi-square method for priority derivation in group decision making with incomplete reciprocal preference relations

Fuzzy prototype classifier based on items and its application in recommender system

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