The Multiple Attribute Decision-Making VIKOR Method and its Application

Wei, Jingzhu; Lin, Xiangyi

doi:10.1109/wicom.2008.2777

Cited by 35 publications

(22 citation statements)

References 12 publications

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“…It can solve discrete decision problems with conflicting and non-commensurable (different units) criteria and provide a solution that is the closest to the ideal. It concentrates on selection and priority of a set of alternatives, and determine the just results for issues with conflicting criteria, while helping decision makers to gain a consensus decision Tzeng, 2004, 2007;Wei and Lin, 2008;Opricovic, 2011;Liu et al, 2013).…”

Section: Review On Methodologymentioning

confidence: 99%

Application of fuzzy VIKOR for evaluation of green supply chain management practices

Rostamzadeh

Govindan

Esmaeili

et al. 2015

Ecological Indicators

368

150

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Section: Review On Methodologymentioning

confidence: 99%

Application of fuzzy VIKOR for evaluation of green supply chain management practices

Rostamzadeh

Govindan

Esmaeili

et al. 2015

Ecological Indicators

368

150

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“…In general, the threat degree of small target is the biggest, and the threat degree of reconnaissance plane is the least. In order to facilitate quantitative study, in this paper, the target threat attribute is quantified by G. A. Miller's nine levels quantization theory [6], the reconnaissance plane, small target and large target were quantified for 3, 5 and 8.…”

Section: Target Type (K)mentioning

confidence: 99%

Threat Assessment of Aerial Target Based on Modified PSO Optimized BP Neural Network

Chen¹,

Wang²

2017

IJCA

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Aerial target threat assessment is to infer degree of target threat to us through comprehensive analysis of the target information, then sort on target, to provide the basis for commander of task allocation and tactical decision; it is the core of the air defense combat command and control system. Consider the aerial target threat assessment problem, A target threat assessment method is proposed by using Modified Particle Swarm Optimization (MPSO) algorithm to optimize the BP neural network. Firstly, this paper carries out analysis on the main factors affecting target threat assessment, then introduces the basic principle of BP neural network and particle swarm optimization (PSO) algorithm and its improvement, and the MPSO-BP neural network assessment model is constructed. Finally, the model is verified by simulation. Results show that the error of this method is obviously less than that of BP neural network and PSO-BP neural network assessment method and has a good evaluation effect.

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“…i and j denote the i th criterion and the j th alternative, and i w is the weight of i th criterion, the main steps of the method may be summarized as follows (Opricovic and Tzeng, 2004;Wei and Lin, 2008) (4) and (5).…”

Section: 13mentioning

confidence: 99%

An integrated decision analytic framework of machine learning with multi-criteria decision making for multi-attribute inventory classification

Kartal

Oztekin

Gunasekaran

et al. 2016

Computers & Industrial Engineering

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The Multiple Attribute Decision-Making VIKOR Method and its Application

Cited by 35 publications

References 12 publications

Application of fuzzy VIKOR for evaluation of green supply chain management practices

Application of fuzzy VIKOR for evaluation of green supply chain management practices

Threat Assessment of Aerial Target Based on Modified PSO Optimized BP Neural Network

An integrated decision analytic framework of machine learning with multi-criteria decision making for multi-attribute inventory classification

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