scholarly journals A Novel Multiperson Game Approach for Linguistic Multicriteria Decision Making Problems

2014 ◽  
Vol 2014 ◽  
pp. 1-20 ◽  
Author(s):  
Ching-San Lin ◽  
Chen-Tung Chen ◽  
Farn-Shing Chen ◽  
Wei-Zhan Hung

Game theory is considered as an efficient framework in dealing with decision making problems for two players in the competitive environment. In general, the evaluation values of payoffs matrix are expressed by crisp values in a game model. However, many uncertainties and vagueness should be considered due to the qualitative criteria and the subjective judgment of decision makers in the decision making process. The aim of this study is to develop an effective methodology for solving the payoffs matrix with linguistic variables by multiple decision makers in a game model. Based on the linguistic variables, the decision makers can easily express their opinions with respect to criteria for each alternative. By using the linear programming method, we can find the optimal solution of a game matrix in accordance with the combination of strategies of each player effectively. In addition, the expected performance value (EPV) index is defined in this paper to compare the competition ability of each player based on the optimal probability of each strategy combination. And then, numerical example will be implemented to illustrate the computation process of the proposed model. The conclusion and future research are discussed at the end of this paper.

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Reda M. S. Abdulaal ◽  
Omer A. Bafail

When decision-makers’ judgments are uncertain, they often express their opinions using grey linguistic variables. Once used, the data often retains its grey nature throughout all subsequent decision-making iterations. Multicriteria decision-making (MCDM) is a tool used when making complicated decisions and in circumstances where several criteria require evaluation to choose the most desirable option. Grey data serves as the basis for several MCDM methods. This paper compares two MCDM methods, Grey-Linear-Programming (GLP) and Grey-Best-Worst-Method (GBWM), in terms of the weights of decision criteria and their rankings. Moreover, Grey-The Technique for Order of Preference by Similarity to Ideal Solution (GTOPSIS) was used to rank the weights of the two methods. Study findings demonstrated that GBWM requires more mathematical calculations than GLP, based on linear programming's classic simplex method. On the other hand, when GTOPSIS follows GLP, the alternative rank does not change compared to when GTOPSIS followed GBWM. For the applications used in this comparison, GLP procedure is considered simpler than GBWM procedure.


Author(s):  
Jian Li ◽  
Li-li Niu ◽  
Qiongxia Chen ◽  
Zhong-xing Wang

AbstractHesitant fuzzy preference relations (HFPRs) have been widely applied in multicriteria decision-making (MCDM) for their ability to efficiently express hesitant information. To address the situation where HFPRs are necessary, this paper develops several decision-making models integrating HFPRs with the best worst method (BWM). First, consistency measures from the perspectives of additive/multiplicative consistent hesitant fuzzy best worst preference relations (HFBWPRs) are introduced. Second, several decision-making models are developed in view of the proposed additive/multiplicatively consistent HFBWPRs. The main characteristic of the constructed models is that they consider all the values included in the HFBWPRs and consider the same and different compromise limit constraints. Third, an absolute programming model is developed to obtain the decision-makers’ objective weights utilizing the information of optimal priority weight vectors and provides the calculation of decision-makers’ comprehensive weights. Finally, a framework of the MCDM procedure based on hesitant fuzzy BWM is introduced, and an illustrative example in conjunction with comparative analysis is provided to demonstrate the feasibility and efficiency of the proposed models.


2015 ◽  
Vol 67 (1) ◽  
pp. 215-220 ◽  
Author(s):  
Valentin Grecu

Abstract There is rarely an optimal solution in sustainable development but most frequently a need to build compromises between conflicting aspects such as economic, social and environmental ones and different expectations of stakeholders. Moreover, information is rarely available and precise. This paper will focus on how to use indicators to monitor sustainable development, integrating the information provided by many of them into a complex general sustainability index. Having this general indicator is essential for decision makers as it is very complicated to evaluate the performance of the organization based on multiple indicators. The objective of this paper is to find mathematical algorithms for simplifying the decision-making process by offering an instrument for the evaluation of the sustainability progress.


Author(s):  
Ankur V. Bansod ◽  
Awanikumar P. Patil ◽  
Kanak Kalita ◽  
B. D. Deshmukh ◽  
Nilay Khobragade

Abstract Suitable material selection with emphasis on a specific property or application is an indispensable part of engineering sciences. It is a complex process that involves multiple criteria and often multiple decision makers. The tendency of decision makers to specify their preference in terms of imprecise qualitative statements like ‘good’, ‘bad’ etc. poses a further challenge. Thus, in this research, a comprehensive multicriteria decision-making study was conducted to select the optimal Zn-Al alloy based on performance in a corrosive environment. Four variants of technique for order of preference by similarity to the ideal solution were used to perform the multicriteria decision-making analysis. Group decision and imprecise decision making is handled by incorporating the fuzzy theory concept in a technique for order of preference by similarity to the ideal solution. The effect of addition of aluminium to zinc was studied by examination of microstructure, hardness, and corrosion behaviour. The result indicates that an increase in Al content increases the formation of dendrites. The dendrites were rich in the α phase, which results in an increase in hardness. An increase in Al content in Zn (Zn-22Al and Zn-55Al) results in the uniform distribution of the a phase in the microstructure and reduction of non-equilibrium phases. The potentiodynamic polarisation test revealed that an increase in Al in the alloy decreases the corrosion current density. The weight loss test carried out to validate the potentiodynamic test findings exhibited higher weight loss in pure Zn and lowest in Zn-55Al. Similar results were observed in the salt spray test. The multicriteria decision-making analysis revealed that Zn-55Al is the most suitable alloy in a corrosive environment among the tested alloys.


2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Bowen Wang ◽  
Haitao Xiong ◽  
Chengrui Jiang

As a hot topic in supply chain management, fuzzy method has been widely used in logistics center location selection to improve the reliability and suitability of the logistics center location selection with respect to the impacts of both qualitative and quantitative factors. However, it does not consider the consistency and the historical assessments accuracy of experts in predecisions. So this paper proposes a multicriteria decision making model based on credibility of decision makers by introducing priority of consistency and historical assessments accuracy mechanism into fuzzy multicriteria decision making approach. In this way, only decision makers who pass the credibility check are qualified to perform the further assessment. Finally, a practical example is analyzed to illustrate how to use the model. The result shows that the fuzzy multicriteria decision making model based on credibility mechanism can improve the reliability and suitability of site selection for the logistics center.


Author(s):  
Ibrahim Suleiman Yahaya ◽  
Maryam M.B Yusuf

This paper The search paper aimed at introducing new development in decision-making and problem-solving models which will enable the decision-makers to have more options on the way of handling any give scenarios that might occur in the process of daily life or organizational activities, this will improve fast decision by individual or organization. Decision making is an acceptable part of human daily life. People have to make different important decisions nearly every day, hence the reason that often-making decisions can be a difficult action to take. However, a significant number of observational studies have shown that most individuals are much worse in decision-making in organizations. Thus, people started paying more attention to learning how to make an acceptable decision through the related hypotheses and models that fit their scenarios. Along with the line hundred (100) sample of the design developed model with a Likert-Scale from 1-5 was attached and sent to some prominent leaders who virtually make a decision and solved problems almost every day, for their assessment’s/analysis in order to collect data to determine both input and output of the developed model which some accepted as it was designed while some make changes and other make a recommendation for future research work. The decision-making tools are needed at the critical time of Covid.


Author(s):  
Rami Benbenishty ◽  
John D. Fluke

This chapter presents the basic concepts, theoretical perspectives, and areas of scholarship that bear on decisions in child welfare—making choices in decision environments characterized by high levels of uncertainty. The authors distinguish between normative models that predict what decision-makers ought to choose when faced with alternatives and descriptive models that describe how they tend to make these choices in real life. The chapter reviews those challenges that may be especially relevant in the complex context of child welfare and protection. One way in which decision-makers overcome task complexities and limitations in human information processing (bounded rationality) is by using heuristics to navigate complex tasks. The chapter reviews strategies to correct some limitations in judgment. The authors examine the relationships between workers’ predictions of what would be the outcomes of the case and the actual outcomes and describe two types of error (false positive and false negative) and the related concepts of specificity and sensitivity. These issues are followed by a description of the Lens Model and some of its implications for child welfare decision-making, including predictive risk modeling and studies on information processing models. The final section presents current theoretical models in child welfare decision-making and describes Decision-Making Ecology (DME) and Judgments and Decision Processes in Context (JUDPiC). The chapter concludes with suggestions for future research on child welfare decision-making that could contribute to our conceptual understanding and have practical utility as well.


Author(s):  
Charles A. Miller

The “sunk costs fallacy” is a popular import into political science from organizational psychology and behavioral economics. The fallacy is classically defined as a situation in which decision-makers escalate commitment to an apparently failing project in order to “recoup” the costs they have already sunk into it. The phenomenon is often framed as a good example of how real decision-making departs from the assumption of forward-looking rationality which underpins traditional approaches to understanding politics. Researchers have proposed a number of different psychological drivers for the fallacy, such as cognitive dissonance reduction, and there is experimental and observational evidence that it accurately characterizes decision-making in certain contexts. However, there is significant skepticism about the fallacy in many social sciences, with critics arguing that there are better forward-looking rational explanations for decisions apparently driven by a desire to recoup sunk costs – among them reputational concerns, option values and agency problems. Critics have also noted that in practical situations sunk costs are informative both about decision makers’ intrinsic valuation for the issue and the prospects for success, making it hard to discern a separate role for sunk costs empirically. To address these concerns, empirical researchers have employed a number of strategies, especially leveraging natural experiments in certain non-political decision making contexts such as sports or business, in order to isolate the effects of sunk costs per se from other considerations. In doing so, they have found mixed support for the fallacy. Research has also shown that the prevalence of the sunk costs fallacy may be moderated by a number of factors, including the locus of decision-making, framing, and national context. These provide the basis for suggestions for future research.


Author(s):  
Marius Guenzel ◽  
Ulrike Malmendier

One of the fastest-growing areas of finance research is the study of managerial biases and their implications for firm outcomes. Since the mid-2000s, this strand of behavioral corporate finance has provided theoretical and empirical evidence on the influence of biases in the corporate realm, such as overconfidence, experience effects, and the sunk-cost fallacy. The field has been a leading force in dismantling the argument that traditional economic mechanisms—selection, learning, and market discipline—would suffice to uphold the rational-manager paradigm. Instead, the evidence reveals that behavioral forces exert a significant influence at every stage of a chief executive officer’s (CEO’s) career. First, at the appointment stage, selection does not impede the promotion of behavioral managers. Instead, competitive environments oftentimes promote their advancement, even under value-maximizing selection mechanisms. Second, while at the helm of the company, learning opportunities are limited, since many managerial decisions occur at low frequency, and their causal effects are clouded by self-attribution bias and difficult to disentangle from those of concurrent events. Third, at the dismissal stage, market discipline does not ensure the firing of biased decision-makers as board members themselves are subject to biases in their evaluation of CEOs. By documenting how biases affect even the most educated and influential decision-makers, such as CEOs, the field has generated important insights into the hard-wiring of biases. Biases do not simply stem from a lack of education, nor are they restricted to low-ability agents. Instead, biases are significant elements of human decision-making at the highest levels of organizations. An important question for future research is how to limit, in each CEO career phase, the adverse effects of managerial biases. Potential approaches include refining selection mechanisms, designing and implementing corporate repairs, and reshaping corporate governance to account not only for incentive misalignments, but also for biased decision-making.


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