A Fuzzy TOPSIS+Worst-Case Model for Personnel Evaluation Using Information Culture Criteria

2016 ◽  
Vol 7 (4) ◽  
pp. 38-66 ◽  
Author(s):  
Rasim M. Alguliyev ◽  
Ramiz M. Aliguliyev ◽  
Rasmiyya S. Mahmudova
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Personnel Evaluation ◽  
Information Culture ◽  
Worst Case ◽  
Entropy Methods ◽  
Fuzzy Mcdm

Personnel evaluation process is aimed at choosing the best alternative to fill the defined vacancy in an organization. It determines the input quality of personnel and thus plays an important role in human resource management. The multi criteria nature and the presence of qualitative factors make it considerably more complex. This paper proposes a hybrid fuzzy MCDM model for personnel evaluation. It combines the fuzzy TOPSIS method with fuzzy worst-case (or entropy) method for linguistic reasoning under group decision making. Fuzzy worst-case and entropy methods are used to get weights of criteria, while fuzzy TOPSIS is utilized to rank the alternatives. The weights obtained from fuzzy worst-case and entropy methods are included in fuzzy TOPSIS computations and the alternatives are evaluated. The fuzzy MCDM for group decision making enables to aggregate subjective assessments of the decision-makers and thus offer an opportunity to perform more robust personnel evaluation procedures. To evaluate the alternatives the authors have formed an executive group consisting of five decision-makers. For evaluation the group has decided to consider five information culture criteria expressed in linguistic variables. A numerical example demonstrated the possibilities of application of the proposed method.

A Fuzzy TOPSIS+Worst-Case Model for Personnel Evaluation Using Information Culture Criteria

2018 ◽  
pp. 1068-1099
Author(s):  
Rasim M. Alguliyev ◽  
Ramiz M. Aliguliyev ◽  
Rasmiyya S. Mahmudova
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Personnel Evaluation ◽  
Information Culture ◽  
Worst Case ◽  
Entropy Methods ◽  
Fuzzy Mcdm

Personnel evaluation process is aimed at choosing the best alternative to fill the defined vacancy in an organization. It determines the input quality of personnel and thus plays an important role in human resource management. The multi criteria nature and the presence of qualitative factors make it considerably more complex. This paper proposes a hybrid fuzzy MCDM model for personnel evaluation. It combines the fuzzy TOPSIS method with fuzzy worst-case (or entropy) method for linguistic reasoning under group decision making. Fuzzy worst-case and entropy methods are used to get weights of criteria, while fuzzy TOPSIS is utilized to rank the alternatives. The weights obtained from fuzzy worst-case and entropy methods are included in fuzzy TOPSIS computations and the alternatives are evaluated. The fuzzy MCDM for group decision making enables to aggregate subjective assessments of the decision-makers and thus offer an opportunity to perform more robust personnel evaluation procedures. To evaluate the alternatives the authors have formed an executive group consisting of five decision-makers. For evaluation the group has decided to consider five information culture criteria expressed in linguistic variables. A numerical example demonstrated the possibilities of application of the proposed method.

scholarly journals Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method

2015 ◽  
Vol 15 (4) ◽  
pp. 863-874 ◽  
Author(s):  
G. Lee ◽  
K. S. Jun ◽  
E.-S. Chung
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Consensus Building ◽  
Vikor Method ◽  
Flood Vulnerability ◽  
Fuzzy Vikor ◽  
Risk Vulnerability

Abstract. This study proposes an improved group decision making (GDM) framework that combines the VIKOR method with data fuzzification to quantify the spatial flood vulnerability including multiple criteria. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. This approach effectively can propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the southern Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the spatial flood vulnerability using general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods (i.e., Borda, Condorcet, and Copeland). As a result, the proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.

scholarly journals An Assessment of Objectivity Convergence of Fuzzy TOPSIS Method Extended With Rank Order Weights in Group Decision Making

2018 ◽  
Vol 7 (3) ◽  
pp. 26-33
Author(s):  
Ayan Chattopadhyay ◽  
Upasana Bose
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Rank Order ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Topsis Method ◽  
Chain Management ◽  
Criteria Weights ◽  
Topsis Approach

Group decision making in a multi criteria environment is a familiar business situation where the decision makers identify an ideal choice, among many. The situation gets complex when decision makers do not have crisp data to deal with. The fuzzy TOPSIS method, and its likes, provides solution to such problems and the criteria weight plays a determinant role in the overall priority estimation. This paper presents an extended fuzzy TOPSIS approach by incorporating criteria weights derived from rank order. It considers three criteria weights; the rank order centroid, rank sum and rank reciprocal weights. The criteria weights are calculated separately and integrated with fuzzy TOPSIS method to rank choices. Finally, objectivity convergence of the alternative rankings is tested. The proposed method yields a fairly uniform and consistent result in the case of supply chain management and anticipates wide application in multi criteria environment, concomitant with uncertainty and vagueness.

Doubly Extended Fuzzy TOPSIS Method for Group Decision Making

2019 ◽  
Vol 66 (1) ◽  
pp. 27-50
Author(s):  
Dariusz Kacprzak
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Group Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Final Decision ◽  
Topsis Method ◽  
Decision Matrix

Multiple Criteria Decision Making methods, such as TOPSIS, have become very popular in recent years and are frequently applied to solve many real-life situations. However, the increasing complexity of the decision problems analysed makes it less feasible to consider all the relevant aspects of the problems by a single decision maker. As a result, many real-life problems are discussed by a group of decision makers. In such a group each decision maker can specialize in a different field and has his/her own unique characteristics, such as knowledge, skills, experience, personality, etc. This implies that each decision maker should have a different degree of influence on the final decision, i.e., the weights of decision makers should be different. The aim of this paper is to extend the fuzzy TOPSIS method to group decision making. The proposed approach uses TOPSIS twice. The first time it is used to determine the weights of decision makers which are then used to calculate the aggregated decision matrix for all the group decision matrices provided by the decision makers. Based on this aggregated matrix, the extended TOPSIS is used again, to rank the alternatives and to select the best one. A numerical example illustrates the proposed approach.

scholarly journals Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method

2014 ◽  
Vol 2 (9) ◽  
pp. 6141-6171 ◽  
Author(s):  
G. Lee ◽  
K. S. Jun ◽  
E. S. Cung
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Consensus Building ◽  
Vikor Method ◽  
Flood Vulnerability ◽  
Fuzzy Vikor ◽  
Multi Criteria Evaluation

Abstract. This study proposes an improved group decision making (GDM) framework that combines VIKOR method with fuzzified data to quantify the spatial flood vulnerability including multi-criteria evaluation indicators. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. Triangular fuzzy numbers are used to consider the uncertainty of weights and the crisp data of proxy variables. This approach can effectively propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the south Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the results from general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods, such as those developed by Borda, Condorcet, and Copeland. The evaluated priorities were significantly dependent on the employed decision-making method. The proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.

CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection

2021 ◽  
pp. 1-11
Author(s):  
Huiyuan Zhang ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Supplier Selection ◽  
Group Decision ◽  
Comparison Method ◽  
Entropy Method ◽  
Decision Makers ◽  
Green Supplier Selection ◽  
Multiple Attribute ◽  
Psychological Perceptions

The green supplier selection is one of the popular multiple attribute group decision making (MAGDM) problems. The spherical fuzzy sets (SFSs) can fully express the complexity and fuzziness of evaluation information for green supplier selection. Furthermore, the classic MABAC (multi-attributive border approximation area comparison) method based on the cumulative prospect theory (CPT-MABAC) is designed, which is an optional method in reflecting the psychological perceptions of decision makers (DMs). Therefore, in this article, we propose a spherical fuzzy CPT-MABAC (SF-CPT-MABAC) method for MAGDM issues. Meanwhile, considering the different preferences of DMs to attribute sets, we obtain the objective weights of attributes through entropy method. Focusing on the current popular problems, this paper applies the proposed method for green supplier selection and proves for green supplier selection based on SF-CPT-MABAC method. Finally, by comparing existing methods, the effectiveness of the proposed method is certified.

Method for Selecting Storage Enterprises Based on IFHA

2015 ◽  
Vol 713-715 ◽  
pp. 1769-1772
Author(s):  
Jie Wu ◽  
Lei Na Zheng ◽  
Tie Jun Pan
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Decision Problems ◽  
Decision Making Process ◽  
Final Decision ◽  
Multiple Decision Makers ◽  
Intuitionistic Fuzzy ◽  
Averaging Operator

In order to reflect the decision-making more scientific and democratic, modern decision problems often require the participation of multiple decision makers. In group decision making process,require the use of intuitionistic fuzzy hybrid averaging operator (IFHA) to get the final decision result.

scholarly journals Some q-Rung Dual Hesitant Fuzzy Heronian Mean Operators with Their Application to Multiple Attribute Group Decision-Making

Symmetry ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 472 ◽  
Author(s):  
Yuan Xu ◽  
Xiaopu Shang ◽  
Jun Wang ◽  
Wen Wu ◽  
Huiqun Huang
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Hesitant Fuzzy Sets ◽  
Multiple Attribute ◽  
A New Technique ◽  
Supplier Selection Problem ◽  
Heronian Mean

The q-rung orthopair fuzzy sets (q-ROFSs), originated by Yager, are good tools to describe fuzziness in human cognitive processes. The basic elements of q-ROFSs are q-rung orthopair fuzzy numbers (q-ROFNs), which are constructed by membership and nonmembership degrees. As realistic decision-making is very complicated, decision makers (DMs) may be hesitant among several values when determining membership and nonmembership degrees. By incorporating dual hesitant fuzzy sets (DHFSs) into q-ROFSs, we propose a new technique to deal with uncertainty, called q-rung dual hesitant fuzzy sets (q-RDHFSs). Subsequently, we propose a family of q-rung dual hesitant fuzzy Heronian mean operators for q-RDHFSs. Further, the newly developed aggregation operators are utilized in multiple attribute group decision-making (MAGDM). We used the proposed method to solve a most suitable supplier selection problem to demonstrate its effectiveness and usefulness. The merits and advantages of the proposed method are highlighted via comparison with existing MAGDM methods. The main contribution of this paper is that a new method for MAGDM is proposed.

Fuzzy multi-attribute group decision making to identify the order of establishing temporary logistics hubs during disaster response

2019 ◽  
Vol 9 (1) ◽  
pp. 2-21 ◽  
Author(s):  
Rajali Maharjan ◽  
Shinya Hanaoka
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Disaster Response ◽  
Group Decision ◽  
Decision Makers ◽  
Numerical Illustration ◽  
Content Type ◽  
Using Data ◽  
The Impact ◽  
Post Disaster

Purpose The purpose of this paper is to reveal the importance of the order of establishment of temporary logistics hubs (TLHs) when resources (mobile storage units used as TLHs) are limited and to present the development and implementation of a methodology that determines the order of establishment of TLHs to support post-disaster decision making. Design/methodology/approach It employed a decision support system that considers multiple decision makers and subjective attributes, while also addressing the impreciseness inherent in post-disaster decision making for ordering the establishment of TLHs. To do so, an optimization model was combined with a fuzzy multi-attribute group decision making approach. A numerical illustration was performed using data from the April 2015 Nepal Earthquake. Findings The results showed the location and order of establishment of TLHs, and demonstrated the impact of decision makers’ opinions on the overall ordering. Research limitations/implications The study does not discuss the uncertain nature of the location problem and the potential need for relocation of TLHs. Practical implications This methodology offers managerial insights for post-disaster decision making when resources are limited and their effective utilization is vital. The results highlight the importance of considering the opinions of multiple actors/decision makers to enable coordination and avoid complication between the growing numbers of humanitarian responders during disaster response. Originality/value This study introduces the concept of the order of establishment of TLHs and demonstrates its importance when resources are limited. It develops and implements a methodology determining the order of establishment of TLHs to support post-disaster decision making.

scholarly journals Hybrid Multiattribute Group Decision Making Based on Intuitionistic Fuzzy Information and GRA Method

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Jian Guo
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Ideal Solution ◽  
Decision Matrix ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Intuitionistic Fuzzy Entropy ◽  
Fuzzy Group Decision Making

Hybrid multiple attribute group decision making involves ranking and selecting competing courses of action available using attributes to evaluate the alternatives. The decision makers assessment information can be expressed in the form of real number, interval-valued number, linguistic variable, and the intuitionistic fuzzy number. All these evaluation information can be transformed to the form of intuitionistic fuzzy numbers. A combined GRA with intuitionistic fuzzy group decision-making approach is proposed. Firstly, the hybrid decision matrix is standardized and then transformed into an intuitionistic fuzzy decision matrix. Then, intuitionistic fuzzy averaging operator is utilized to aggregate opinions of decision makers. Intuitionistic fuzzy entropy is utilized to obtain the entropy weights of the criteria, respectively. After intuitionistic fuzzy positive ideal solution and intuitionistic fuzzy negative ideal solution are calculated, the grey relative relational degree of alternatives is obtained and alternatives are ranked. In the end, a numerical example illustrates the validity and applicability of the proposed method.

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