Cooperative fuzzy games with interval characteristic functions

Meng, Fanyong; Chen, Xiaohong; Tan, Chunqiao

doi:10.1007/s12351-015-0183-z

Cited by 32 publications

(16 citation statements)

References 43 publications

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“…However, these conclusions do not hold in the setting of IFPRs: (i) from formula (2), formula (9) does not necessarily hold. [42]). Thus, it is unsuitable to directly extend formula (9) in the setting of intervals to define multiplicative consistent IFPRs; (ii) formula (2) is not robust to the object labels; thus, with different compared orders, formula (2) will not hold.…”

Section: New Multiplicative Consistency Concept For Ifprsmentioning

confidence: 99%

Multiplicative consistency analysis for interval fuzzy preference relations: A comparative study

Meng

Tan

Chen

2017

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Section: New Multiplicative Consistency Concept For Ifprsmentioning

confidence: 99%

Multiplicative consistency analysis for interval fuzzy preference relations: A comparative study

Meng

Tan

Chen

2017

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“…Moreover, it is not appropriate to imprecise and blurred information of coalition outcomes, which is found in the real-world case (Borkotokey, 2008;Abed-Elmdoust and Kerachian, 2012). Coalition in classical Shapley value has been defined by many scholars before in a set of real numbers (Borkotokey, 2008;Meng et al, 2016). This definition did not reflect the real supply chain situation, though with imprecise and uncertain information.…”

Section: Cooperative Game Theory: the Shapley Value And Its Limitationsmentioning

confidence: 99%

Supply Chain Fair Profit Allocation Based on Risk and Value Added for Sugarcane Agro-industry

Asrol

Marimin

Machfud

et al. 2020

OSCM: An Int. Journal

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Profit allocation is the main critical problem in the supply chain. In agro-industry supply chain, establishing a fair and reasonable profit allocation has been more challenging due to the influence of uncertain factors. Cooperative game theory with the Shapley value has an opportunity to solve this problem given its appropriateness for the key goals of the supply chain. Fuzzy Shapley value was developed to accommodate uncertain stakeholders' payoff. In addition, uncertain risk and value added were considered for a reasonable profit allocation. This model succeeded in a case study of finding a fair profit allocation in the sugarcane agro-industry supply chain taking into account uncertain risk and value added. The model validation showed that sugarcane farmers, mills, and distributors achieved 35.38%, 30.11%, and 34.51% of profit share, respectively. Stakeholders achieved their profit share based on their marginal contribution, risk potential, and valueadded contribution, which may increase supply chain stability.

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“…Observe that interval-valued fuzzy sets allow to deal not only with vagueness (lack of sharp class boundaries) but also with uncertainty (lack of information). Meng et al 30 proposed a generalized form of fuzzy games with interval characteristic functions. For example, cooperative games where the knowledge about the worth of coalitions is described by fuzzy intervals have been introduced by Mares, 20 considering the core as a fuzzy set.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, Collins and Hu 29 studied interval-valued matrix games with fuzzy logic, extending the results of classical matrix games into interval-valued games, and defining fuzzy relational operators for intervals to compare every pair of possible interval payoffs. Meng et al 30 proposed a generalized form of fuzzy games with interval characteristic functions. Brião et al 31 introduced two approaches for the solution of interval-valued fuzzy zero-sum games, based on interval fuzzy linear programming problems.…”

Section: Introductionmentioning

confidence: 99%

On Two-Player Interval-Valued Fuzzy Bayesian Games

Asmus

Dimuro

Bedregal

2016

Int. J. Intell. Syst.

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Game theory is an important basis to simulate several situations where multiple agents interact strategically for decision making and support. In many applications, such as auctions, frequently used for resource management involving two or more agents competing for the resources, the interacting agents only know their own characteristics and must make decisions while having to estimate the characteristics of the others. When probabilities are assigned for the different types of the interacting agents, this kind of strategic interaction constitutes a Bayesian game. In cases in which it is very difficult to characterize the private information of each agent, the payoffs can be given by approximate (not probabilistic) values, but the concept of Bayesian Nash equilibrium cannot be applied in this context. Fuzzy set theory is an excellent basis for studying this type of game, where the payoffs are represented by fuzzy numbers. When it is the case that there is also uncertainty about such fuzzy numbers, the use of interval fuzzy numbers appears as a good modeling alternative. This paper introduces an approach for interval‐based fuzzy Bayesian games, based on interval‐valued fuzzy probabilities for modeling the types of agents involved in the interaction. We present two different case studies, namely the (Interval) Fuzzy Bayesian Hiring Game and (Interval) Fuzzy Bayesian Prisoner's Dilemma with Moral Standards, comparing the results obtained with the crisp, fuzzy and interval fuzzy approaches, highlighting a particular case in which the interval fuzzy approach presents a solution although the two other do not.

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Cooperative fuzzy games with interval characteristic functions

Cited by 32 publications

References 43 publications

Multiplicative consistency analysis for interval fuzzy preference relations: A comparative study

Multiplicative consistency analysis for interval fuzzy preference relations: A comparative study

Supply Chain Fair Profit Allocation Based on Risk and Value Added for Sugarcane Agro-industry

On Two-Player Interval-Valued Fuzzy Bayesian Games

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