Quality yarn index using AHP and Fuzzy method

Hassen, Mohamed Ben; Halim, Mohamed Taher; Abualsauod, Emad H.; Othman, Asem Majed

doi:10.35530/it.071.05.1699

Cited by 2 publications

(3 citation statements)

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“…These methods should combine the "best features" of currently applied approaches (including those presented in this paper). Examples of creating such hybrid methods are described in [12][13][14]19].…”

Section: Discussion Of the Results Obtained In The Study Of Methods Of Structural And Parametric Identification Of The Estimation Modelmentioning

confidence: 99%

“…Numerous publications show the popularity of using this approach in practice. For example, the NAP is used in [19] to evaluate and compare the quality of yarn and the problem of choosing an all-terrain vehicle model for equipping military units is solved in [20]. Study [21] addresses the development of a method for evaluating employee work effectiveness in order to rank them based on the ANP application.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…To do this, it is necessary to find the midpoint for the system of constraints (19), i.e. the value * * ,…”

Section: Solving the Problem Of Structural And Parametric Identification Of The Estimation Modelmentioning

confidence: 99%

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Devising a method for identifying the model of multi-criteria expert estimation of alternatives

Петров

Кобзев²,

Orlov³

et al. 2021

EEJET

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An approach to constructing mathematical models of individual multicriterial estimation was proposed based on information about the ordering relations established by the expert for a set of alternatives. Structural identification of the estimation model using the additive utility function of alternatives was performed within axiomatics of the multi-attribute utility theory (MAUT). A method of parametric identification of the model based on the ideas of the theory of comparative identification has been developed. To determine the model parameters, it was proposed to use the midpoint method that has resulted in the possibility of obtaining a uniform stable solution of the problem. It was shown that in this case, the problem of parametric identification of the estimation model can be reduced to a standard linear programming problem. The scalar multicriterial estimates of alternatives obtained on the basis of the synthesized mathematical model make it possible to compare them among themselves according to the degree of efficiency and, thus, choose "the best" or rank them. A significant advantage of the proposed approach is the ability to use only non-numerical information about the decisions already made by experts to solve the problem of identifying the model parameters. This enables partial reduction of the degree of expert’s subjective influence on the outcome of decision-making and reduces the cost of the expert estimation process. A method of verification of the estimation model based on the principles of cross-validation has been developed. The results of computer modeling were presented. They confirmed the effectiveness of using the proposed method of parametric model identification to solve problems related to automation of the process of intelligent decision making.

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Section: Discussion Of the Results Obtained In The Study Of Methods Of Structural And Parametric Identification Of The Estimation Modelmentioning

confidence: 99%