scholarly journals A generalized TODIM-ELECTRE II method based on linguistic Z-numbers and Dempster–Shafer evidence theory with unknown weight information

Author(s):  
Zhengmin Liu ◽  
Yawen Bi ◽  
Xinya Wang ◽  
Linbin Sha ◽  
Peide Liu

AbstractHow to effectively reflect the randomness and reliability of decision information under uncertain circumstances, and thereby improve the accuracy of decision-making in complex decision scenarios, has become a crucial topic in the field of uncertain decision-making. In this article, the loss –aversion behavior of decision-makers and the non-compensation between attributes are considered. Furthermore, a novel generalized TODIM-ELECTRE II method under the linguistic Z-numbers environment is proposed based on Dempster–Shafer evidence theory for multi-criteria group decision-making problems with unknown weight information. Firstly, the evaluation information and its reliability are provided simultaneously by employing linguistic Z-numbers, which have the ability to capture the arbitrariness and vagueness of natural verbal information. Then, the evaluation information is used to derive basic probability assignments in Dempster–Shafer evidence theory, and with the consideration of both inner and outer reliability, this article employed Dempster’s rule to fuse evaluations. Subsequently, a generalized TODIM-ELECTRE II method is conceived under the linguistic Z-numbers environment, which considers both compensatory effects between attributes and the bounded rationality of decision-makers. In addition, criteria weights are obtained by applying Deng entropy which has the ability to deal with uncertainty. Finally, an example of terminal wastewater solidification technology selection is offered to prove this framework’s availability and robustness. The predominance is also verified by a comparative analysis with several existing methods.

2021 ◽  
Vol 10 (6) ◽  
pp. 403
Author(s):  
Jiamin Liu ◽  
Yueshi Li ◽  
Bin Xiao ◽  
Jizong Jiao

The siting of Municipal Solid Waste (MSW) landfills is a complex decision process. Existing siting methods utilize expert scores to determine criteria weights, however, they ignore the uncertainty of data and criterion weights and the efficacy of results. In this study, a coupled fuzzy Multi-Criteria Decision-Making (MCDM) approach was employed to site landfills in Lanzhou, a semi-arid valley basin city in China, to enhance the spatial decision-making process. Primarily, 21 criteria were identified in five groups through the Delphi method at 30 m resolution, then criteria weights were obtained by DEMATEL and ANP, and the optimal fuzzy membership function was determined for each evaluation criterion. Combined with GIS spatial analysis and the clustering algorithm, candidate sites that satisfied the landfill conditions were identified, and the spatial distribution characteristics were analyzed. These sites were subsequently ranked utilizing the MOORA, WASPAS, COPRAS, and TOPSIS methods to verify the reliability of the results by conducting sensitivity analysis. This study is different from the previous research that applied the MCDM approach in that fuzzy MCDM for weighting criteria is more reliable compared to the other common methods.


2018 ◽  
Vol 24 (3) ◽  
pp. 1125-1148 ◽  
Author(s):  
Seyed Hossein RAZAVI HAJIAGHA ◽  
Meisam SHAHBAZI ◽  
Hannan AMOOZAD MAHDIRAJI ◽  
Hossein PANAHIAN

Decision makers usually prefer to express their preferences by linguistic variables. Classic fuzzy sets allowed expressing these preferences using a single linguistic value. Considering inevitable hesitancy of decision makers, hesitant fuzzy linguistic term sets allowed them to express individual evaluation using several linguistic values. Therefore, these sets improve the ability of humans to determine believes using their own language. Considering this feature, in this paper a method upon linear assignment method is proposed to solve group decision making problems using this kind of information, when criteria weights are known or unknown. The performance of the proposed method is illustrated in a numerical example and the results are compared with other methods to delineate the models efficiency. Following a logical and well-known mathematical logic along with simplicity of execution are the main advantages of the proposed method.


Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Virupaxi Bagodi ◽  
Biswajit Mahanty

PurposeManagerial decision-making is an area of interest to both academia and practitioners. Researchers found that managers often fail to manage complex decision-making tasks and system thinkers assert that generic structures known as systems archetypes help them to a great deal in handling such situations. In this paper, it is demonstrated that decision makers resort to lowering of goal (quick-fix) in order to resolve the gap between the goal and current reality in the “drifting the goals” systems archetype.Design/methodology/approachA real-life case study is taken up to highlight the pitfalls of “drifting the goals” systems archetype for a decision situation in the Indian two-wheeler industry. System dynamics modeling is made use of to obtain the results.FindingsThe decision makers fail to realize the pitfall of lowering the goal to resolve the gap between the goal and current reality. It is seen that, irrespective of current less-than-desirable performance, managers adopting corrective actions other than lowering of goals perform better in the long run. Further, it is demonstrated that extending the boundary and experimentation results in designing a better service system and setting benchmarks.Practical implicationsThe best possible way to avoid the pitfall is to hold the vision and not lower the long term goal. The managers must be aware of the pitfalls beforehand.Originality/valueSystems thinking is important in complex decision-making tasks. Managers need to embrace long-term perspective in decision-making. This paper demonstrates the value of systems thinking in terms of a case study on the “drifting the goals” systems archetype.


Entropy ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. 487 ◽  
Author(s):  
Miao Qin ◽  
Yongchuan Tang ◽  
Junhao Wen

Dempster–Shafer evidence theory (DS theory) has some superiorities in uncertain information processing for a large variety of applications. However, the problem of how to quantify the uncertainty of basic probability assignment (BPA) in DS theory framework remain unresolved. The goal of this paper is to define a new belief entropy for measuring uncertainty of BPA with desirable properties. The new entropy can be helpful for uncertainty management in practical applications such as decision making. The proposed uncertainty measure has two components. The first component is an improved version of Dubois–Prade entropy, which aims to capture the non-specificity portion of uncertainty with a consideration of the element number in frame of discernment (FOD). The second component is adopted from Nguyen entropy, which captures conflict in BPA. We prove that the proposed entropy satisfies some desired properties proposed in the literature. In addition, the proposed entropy can be reduced to Shannon entropy if the BPA is a probability distribution. Numerical examples are presented to show the efficiency and superiority of the proposed measure as well as an application in decision making.


Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1460
Author(s):  
Dariusz Kacprzak

This paper presents an extension of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method with objective criteria weights for Group Decision Making (GDM) with Interval Numbers (INs). The proposed method is an alternative to popular and often used methods that aggregate the decision matrices provided by the decision makers (DMs) into a single group matrix, which is the basis for determining objective criteria weights and ranking the alternatives. It does not use an aggregation operator, but a transformation of the decision matrices into criteria matrices, in the case of determining objective criteria weights, and into alternative matrices, in the case of the ranking of alternatives. This ensures that all the decision makers’ evaluations are taken into account instead of their certain average. The numerical example shows the ease of use of the proposed method, which can be implemented into common data analysis software such as Excel.


2011 ◽  
Vol 5 (9) ◽  
pp. 27 ◽  
Author(s):  
Carlos Parra López ◽  
Javier Calatrava Requena ◽  
Tomás De Haro Giménez

Even though multifunctionality concept is reflected, implicit or explicitly, in the design of actual agrarian policies, its consideration when analysing and assessing farming systems is relatively limited in the scientific literature. Analytic Hierarchy Process (AHP) is proposed with this aim. AHP is a multicriteria discrete decision support technique that is used in complex decision making. This methodology is stated jointly with a proposed procedure to measure relative agreement among decision makers and uniformity of alternatives’ performances in group decision making. Finally AHP is implemented in the assessment of organic, integrated and conventional olive groves in Andalusia considering criteria of a different nature – economic, technical, sociocultural and environmental –. The final purpose is determining the more interesting growing techniques from a holistic point of view for all the society in the medium/long-term on the basis of knowledge of experts on olive.


Author(s):  
Karel Doubravský ◽  
Tomáš Meluzín ◽  
Mirko Dohnal

IPO (Initial Public Offering) is a complex decision making task which is always associated with different types of uncertainty. Poor accuracies of available probabilities of lotteries e.g. quantification of investor interest is studied in the first part of this paper (Meluzín, Doubravský, Dohnal, 2012). However, IPO is often prohibitively ill-known. This paper takes into consideration the fact that decision makers cannot specify the structure/topology of the relevant decision tree. It means that one IPO task is specified by several (partially) different decision trees which comes from different sources e.g. from different teams of decision makers/experts. A flexible integration of those trees is based on fuzzy logic using the reconciliation (Meluzín, Doubravský, Dohnal, 2012). The developed algorithm is demonstrated by a case study which is presented in details. The IPO case integrates two partially different decision trees.


2020 ◽  
Vol 39 (3) ◽  
pp. 4285-4298
Author(s):  
Ran Tao ◽  
Fuyuan Xiao

Group multi-criteria decision-making (GMCDM) is an important part of decision theory, which is aimed to assess alternatives according to multiple criteria by collecting the wisdom of experts. However, in the process of evaluating, because of the limitation of human knowledge and the complexity of problems, an efficient GMCDM approach under uncertain environment still need to be further explored. Thus, in this paper, a novel GMCDM approach with linguistic Z-numbers based on TOPSIS and Choquet integral is proposed. Firstly, since linguistic Z-numbers performs better in coping with uncertain information, it is used to express the evaluation information. Secondly, TOPSIS, one of the most useful and systematic multi-criteria decision-making (MCDM) method, is adopted as the framework of the proposed approach. Thirdly, frequently it exists interaction between criteria, so Choquet integral is introduced to capture this kind of influence. What’s more, viewing that decision makers (DMs) show different preferences for uncertainty, the risk preference is regarded as a vital parameter when calculating the score of linguistic Z-numbers. An application in supplier selection is illustrated to demonstrate the effectiveness of the proposed approach. Finally, a further comparison and discussion of the proposed GMCDM method is given.


2015 ◽  
Vol 5 (1) ◽  
pp. 2-30 ◽  
Author(s):  
Santosh Kumar Sahu ◽  
Saurav Datta ◽  
Siba Sankar Mahapatra

Purpose – Supply chain performance (SCP) extent can be attributed as a function of multiple criteria/attributes. Most of the criterions/attributes being intangible in nature; SCP appraisement relies on the subjective judgment of the decision makers. Moreover, quantitative appraisement of SCP appears to be very difficult due to involvement of ill-defined (vague) performance measures as well as metrics. The purpose of this paper is to develop an efficient decision support system (DSS) to facilitate SCP appraisement, benchmarking and related decision making. Design/methodology/approach – This study explores the concept of fuzzy logic in order to tackle incomplete and inconsistent subjective judgment of the decision makers’ whilst evaluating supply chain’s overall performance. Grey relational analysis has been adopted in the later stage to derive appropriate ranking of alternative companies/enterprises (in the same industry) in view of ongoing SCP extent. Findings – In this work, a performance appraisement index system has been postulated to gather evaluation information (weights and ratings) in relation to SCP measures and metrics. Combining the concepts of fuzzy set theory, entropy, ideal and grey relation analysis, a fuzzy grey relation method for SCP benchmarking problem has been presented. First, triangular fuzzy numbers and linguistic evaluation information characterized by triangular fuzzy numbers have been used to evaluate the importance weights of all criteria and the superiority of all alternatives vs various criteria above the alternative level. Then, the concept of entropy has been utilized to solve the adjusted integration weight of all objective criteria above the alternative level. Moreover, using the concept of the grey ration grades, various alternatives have been ranked accordingly. Originality/value – Finally, an empirical example of selecting most appropriate company has been used to demonstrate the ease of applicability of the aforesaid approach. The study results showed that this method appears to be an effective means for tackling multi-criteria decision-making problems in uncertain environments. Empirical data have been analysed and results obtained thereof, have been reported to exhibit application potential of the said fuzzy grey relation based DSS in appropriate situation.


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