STATIC STRATEGIC GAME APPROACH FOR MULTIPLE ATTRIBUTE DECISION MAKING PROBLEMS WITHOUT WEIGHT INFORMATION

2011 ◽  
Vol 20 (03) ◽  
pp. 577-588 ◽  
Author(s):  
LIHUA ZHOU ◽  
WEIYI LIU ◽  
LIZHEN WANG
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Strategic Game ◽  
Arithmetic Average ◽  
Attribute Weights ◽  
A Value ◽  
Multiple Attribute ◽  
Ranking Of Alternatives ◽  
The One

In multiple attribute decision making (MADM) problems, it is usual that no single alternative works best for all performance attributes, so it is difficult to select the best from among multiple available alternatives, especially in the situation that the attribute weights are completely unknown. This research propose a game theory-based approach (GMADM) which incorporates static strategic game theory into MADM problems to derive the attribute weights, and then utilize the weight arithmetic average (WAA) operator to aggregate the attribute values corresponding to each alternative and rank alternatives by means of aggregated information. In GMADM, each attribute is regarded as a player taking part in the game, and the player's strategy is to select a value from interval [0,1] to assign corresponding attribute weight, and the player's utility is defined as the agreement between the ranking of alternatives determined by the aggregated information and the one determined by the attribute values. When the game is in equilibrium status, the strategy profile is the best attribute weights which make each player have good utilities. Moreover, the equilibrium solution of game and the resolution method for the MADM problem without weight information have also been developed. Finally, the result of proposed approach for a practical MADM problem and its comparisons with one of other methods are given.

scholarly journals Fuzzy Attribute Expansion Method for Multiple Attribute Decision-Making with Partial Attribute Values and Weights Unknown and Its Applications

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 717
Author(s):  
Jinbao Zhuo ◽  
Weifeng Shi ◽  
Ying Lan
Keyword(s):  
Decision Making ◽  
Spline Interpolation ◽  
Expansion Method ◽  
Fuzzy Comprehensive Evaluation ◽  
Multiple Attribute Decision Making ◽  
Clustering Methods ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
Interpolation Technique ◽  
Spline Interpolation Technique

In the real world, there commonly exists types of multiple attribute decision-making (MADM) problems with partial attribute values and weights totally unknown. Symmetry among some attribute information that is already known and unknown, and symmetry between the pure attribute set and fuzzy attribute membership set can be a considerable way to solve this type of MADM problem. In this paper, a fuzzy attribute expansion method is proposed to solve this type of problem based on two key techniques: the spline interpolation technique and the attribute weight reconfiguration technique, which are respectively used for the determination of attribute values and the reconfiguration of attribute weights. The spline interpolation technique to expand attribute values can enhance the performance of some regression methods and clustering methods by the comparisons between the results of these methods dealing with practical cases with and without the application of the technique, which further illustrates the effectiveness of this technique. For MADM problems with partial attribute values and weights totally unknown, compared with traditional fuzzy comprehensive evaluation (FCE), FCE with the application of fuzzy attribute expansion method can obtain results more similar with the ones when all attribute values and weights are known, which is proved by the practical power quality evaluation example.

scholarly journals Dombi Aggregation Operators of Linguistic Cubic Variables for Multiple Attribute Decision Making

Information ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 188 ◽  
Author(s):  
Xueping Lu ◽  
Jun Ye
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Optimal Choice ◽  
Decision Makers ◽  
Linguistic Variable ◽  
Operational Parameter ◽  
Arithmetic Average ◽  
Weighted Arithmetic ◽  
Multiple Attribute ◽  
Dombi Operations

A linguistic cubic variable (LCV) is comprised of interval linguistic variable and single-valued linguistic variable. An LCV contains decision-makers’ uncertain and certain linguistic judgments simultaneously. The advantage of the Dombi operators contains flexibility due to its changeable operational parameter. Although the Dombi operations have been extended to many studies to solve decision-making problems; the Dombi operations are not used for linguistic cubic variables (LCVs) so far. Hence, the Dombi operations of LCVs are firstly presented in this paper. A linguistic cubic variable Dombi weighted arithmetic average (LCVDWAA) operator and a linguistic cubic variable Dombi weighted geometric average (LCVDWGA) operator are proposed to aggregate LCVs. Then a multiple attribute decision making (MADM) method is developed in LCV setting on the basis of LCVDWAA and LCVDWGA operators. Finally, two illustrative examples about the optimal choice problems demonstrate the validity and the application of this method.

scholarly journals Multiple Attribute Decision Making Based on Cross-Evaluation with Uncertain Decision Parameters

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Tao Ding ◽  
Liang Liang ◽  
Min Yang ◽  
Huaqing Wu
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Service Companies ◽  
Attribute Weights ◽  
Research Fields ◽  
Multiple Attribute ◽  
Single Attribute ◽  
The Stability ◽  
The City

Multiple attribute decision making (MADM) problem is one of the most common and popular research fields in the theory of decision science. A variety of methods have been proposed to deal with such problems. Nevertheless, many of them assumed that attribute weights are determined by different types of additional preference information which will result in subjective decision making. In order to solve such problems, in this paper, we propose a novel MADM approach based on cross-evaluation with uncertain parameters. Specifically, the proposed approach assumes that all attribute weights are uncertain. It can overcome the drawback in prior research that the alternatives’ ranking may be determined by a single attribute with an overestimated weight. In addition, the proposed method can also balance the mean and deviation of each alternative’s cross-evaluation score to guarantee the stability of evaluation. Then, this method is extended to a more generalized situation where the attribute values are also uncertain. Finally, we illustrate the applicability of the proposed method by revisiting two reported studies and by a case study on the selection of community service companies in the city of Hefei in China.

scholarly journals Sistem Informasi untuk Menentukan Potensi Mahasiswa Menggunakan Metode Fuzzy Multiple Attribute Decision Making dengan Simple Additive Weighting Studi Kasus : STIKES DUTA GAMA KLATEN

Respati ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. 97
Author(s):  
Sofyan Suryawan Priyono, Wing Wahyu Winarno, Ferry Wahyu Wibowo
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Academic Community ◽  
Teaching Activities ◽  
Learning And Teaching ◽  
A Value ◽  
Multiple Attribute ◽  
Simple Additive Weighting ◽  
Academic Potential

Dalam kegiatan belajar dan mengajar lingkungan akademisi tentunya menghasilkan peserta didik yang memiliki keunggulan diatas rata – rata. Keunggulan mahasiswa dalam sebuah lingkungan belajar dapat di indikasikan menjadi sebuah potensi. Dalam studi kasus penelitian ini STIKES Duta Gama Klaten memiliki beberapa data mahasiswa yang dapat dijadikan tolak ukur untuk menentukan mahasiswa yang memiliki potensi.Dengan implementasi metode Fuzzy Multiple Attribute Decision Making dengan Simple Additive Weighting, yaitu melakukan pembobotan pada setiap alternatif pada semua atribut. Data yang ada akan diberikan nilai sesuai dengan rating kecocokan setiap alternatif. Potensi mahasiswa yang selama ini hanya di indikasikan dalam bidang akademik saja, dalam penelitian ini dibagi menjadi 3 alternatif yaitu potensi akademik, potensi non akademik, dan potensi umum.Hasil dari tahap perankingan akan dijadikan sebagai informasi yang diberikan kepada bagian akademik untuk dijadikan pertimbangan. Diharapkan dengan adanya penerapan metode metode Fuzzy Multiple Attribute Decision Making dengan Simple Additive Weighting dapat membantu dalam menentukan potensi apa saja yang ada dalam lingkungan civitas akademika STIKES Duta Gama Klaten.Kata kunci: Potensi, Akademisi, Civitas, Fuzzy Multiple Attribute Decision Making, Simple Additive Weighting                                               ABSTRACTIn the learning and teaching activities of the academic environment of course produce learners who have above average superiority. Student excellence in a learning environment can be indicated to be a potential. In this case study study STIKES Duta Gama Klaten has some student data that can be used as a benchmark to determine students who have potential.With the implementation of Fuzzy Multiple Attribute Decision Making method with Simple Additive Weighting, which is to weighting every alternative on all attributes. Existing data will be assigned a value in accordance with each alternative's match rating. Potential students who have been only indicated in the field of academics alone, in this study is divided into 3 alternatives of academic potential, non-academic potential, and general potential.The results of the ranking stage will be used as information given to the academic to be considered. It is expected that the application of the method of Fuzzy Multiple Attribute Decision Making method with Simple Additive Weighting can help in determining the potential of what is in the academic community of STIKES Duta Gama Klaten.Keywords: Potential, Academic, Civitas, Fuzzy Multiple Attribute Decision Making, Simple Additive Weighting

Extending ARAS with Integration of Objective Attribute Weighting under Spherical Fuzzy Environment

2021 ◽  
pp. 1-26
Author(s):  
Sait Gül
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Decision Makers ◽  
Owa Operator ◽  
Attribute Weighting ◽  
Preference Domain ◽  
Attribute Weights ◽  
Fuzzy Environment ◽  
Multiple Attribute ◽  
Collection Time

Various fuzzy sets have been developed in the recent years to model the uncertainty in judgments. Spherical fuzzy set (SFS) concept is one of these developments. It can provide an extensive preference domain for decision-makers by allowing them to state their hesitancy more explicitly. The peculiarity of SFS is that the squared sum of membership, nonmembership, and hesitancy degrees should be between 0 and 1 while each is independently defined in [0, 1]. In this study, ARAS as one of the most applied multiple attribute decision-making approaches is extended into a spherical fuzzy environment. Entropy-based and OWA operator-based objective attribute weights are also integrated with the newly proposed spherical fuzzy ARAS for coping with the drawbacks of subjective weighting such as longer data collection time and manipulation risk. The applicability of the proposition is shown in a hypothetical example of a product design problem and its robustness is shown by a comparative analysis.

PROJECTION METHOD FOR UNCERTAIN MULTI-ATTRIBUTE DECISION MAKING WITH PREFERENCE INFORMATION ON ALTERNATIVES

2004 ◽  
Vol 03 (03) ◽  
pp. 429-434 ◽  
Author(s):  
ZESHUI XU ◽  
QINGLI DA
Keyword(s):  
Decision Making ◽  
Projection Method ◽  
Multiple Attribute Decision Making ◽  
Projection Model ◽  
Preference Information ◽  
Objective Information ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
Multi Attribute Decision Making

In this paper, we study the uncertain multiple attribute decision making problems with preference information on alternatives (UMADM-PIA, for short), in which the information on attribute weights is not precisely known, but value ranges can be obtained. A projection method is proposed for the UMADM-PIA. To reflect the decision maker's preference information, a projection model is established to determine the weights of attributes, and then to select the most desirable alternative(s). The method can reflect both the objective information and the decision maker's subjective preferences, and can also be performed on computer easily. Finally, an illustrative example is given to verify the proposed method and to demonstrate its feasibility and practicality.

Multiple Criteria Decision Making Research of Flight Control System Design

2013 ◽  
Vol 648 ◽  
pp. 334-343
Author(s):  
Rui Nie ◽  
Bai Nan Zhang ◽  
Bao Ning Liu ◽  
Wei Guo Zhang ◽  
Jing Yuan
Keyword(s):  
Neural Network ◽  
Decision Making ◽  
Flight Control ◽  
Multiple Criteria Decision Making ◽  
Multiple Attribute Decision Making ◽  
Multiple Objective ◽  
Flight Control System ◽  
Attribute Weights ◽  
Multiple Attribute ◽  
Multiple Objective Decision Making

Flight control system; multiple criteria decision making; multiple objective decision making; multiple attribute decision making; neural network; mean impact value index. Abstract. It is complex and difficult to tune the parameters of the flight controller. To solve such problem, a multiple objective decision making (MODM) method by using the reference model which is built based on the criteria, is proposed. In order to resolve defects of the multiple attribute decision making (MADM) that the arbitrary of the subjective attribute weights and ignoring the objective message of the objective attribute weights, a subjective attribute weights based on the BP neural network by using the MIV (mean impact value) index is proposed. Finally, a combining method based on the TOPSIS is used to give the final attribute weights. The simulation results show that the method could obtain a set of trade-off solutions which satisfy the requirements of the MODM and could tune the controller effectively.

Sign in / Sign up

Export Citation Format

Share Document