A New Fuzzy MADM Approach and its Application to Project Selection Problem

Pahlavani, Ali

doi:10.1080/18756891.2010.9727681

Cited by 9 publications

(3 citation statements)

References 28 publications

(20 reference statements)

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“…Fuzzy control charts were used to increase the accuracy of PCA by determining whether or not the process is in statistical control. Also, fuzzy set theory is used for multi-criteria decision making applications, like Kahraman and Tolga 18 , and Pahlavani 19 .…”

Section: Published By Atlantis Pressmentioning

confidence: 99%

Evaluating the Packing Process in Food Industry Using Fuzzy X and S Control Charts

Erginel¹,

Şentürk²,

Kahraman³

et al. 2011

IJCIS

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The fuzzy set theory addresses the development of concepts and techniques for dealing with uncertainty or impression conditions. If the collected data from a process include vagueness due to human subjectively or measurement system, fuzzy control charts are available tools for monitoring and evaluating the process. The main contribution of fuzzy control charts is to provide flexibility to the control limits. When sample mean is too close to the control limits and the used measurement system is not so sensitive, the decision may be faulty. In this paper, the fuzzy standard deviation is firstly introduced to obtain fuzzy X and S control charts and then these fuzzy control charts are employed in food industry to monitor if the processes are under control or not. Additionally, the fuzzy X and S control charts are developed for the case that the population parameters (µ and σ) are known.

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Section: Published By Atlantis Pressmentioning

confidence: 99%

Evaluating the Packing Process in Food Industry Using Fuzzy X and S Control Charts

Erginel¹,

Şentürk²,

Kahraman³

et al. 2011

IJCIS

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“…MADM models are used to select best alternative from the large number of alternatives for a set of selection criteria. This approach has been effectively applied in broad range of decision-making problems in engineering and scientific fields (Perego and Rangone 1998;Pahlavani 2010). A variety of methods are reported under MADM category in literature (Chen et al 1992;Tönshoff et al 2007).…”

Section: Introductionmentioning

confidence: 99%

Efficacy of fuzzy MADM approach in Six Sigma analysis phase in automotive sector

2016

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Six Sigma is a strategy for achieving process improvement and operational excellence within an organization. Decisions on critical parameter selection in analysis phase are always very crucial; it plays a primary role in successful execution of Six Sigma project and for productivity improvement in manufacturing environment and involves the imprecise, vague and uncertain information. Using a case study approach; the paper demonstrates a tactical approach for selection of critical factors of machine breakdown in center less grinding (CLG) section at an automotive industry using fuzzy logic based multi attribute decision making approach. In this context, we have considered six crucial attributes for selection of critical factors for breakdown. Mean time between failure is found to be the pivotal selection criterion in CLG section. Having calculated the weights pertinent to criteria through two methods (fuzzy VIKOR and fuzzy TOPSIS) critical factors for breakdown are prioritized. Our results are in strong agreement with the perceptions of production and maintenance department of the company.

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“…It is difficult to express trust using traditional mathematical theory since trust can be subjective and uncertain. Fuzzy theory can thus be used to handle uncertainty effectively and has been widely used in many fields such as natural science, social science and management [15][16][17][18][19][20] .…”

Section: Introductionmentioning

confidence: 99%

Application of Fuzzy Comprehensive Evaluation Method in Trust Quantification

Ma¹,

He²,

Shuai³

2011

IJCIS

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Trust can play an important role for the sharing of resources and information in open network environments. Trust quantification is thus an important issue in dynamic trust management. By considering the fuzziness and uncertainty of trust, in this paper, we propose a fuzzy comprehensive evaluation method to quantify trust along with a trust quantification algorithm. Simulation results show that the trust quantification algorithm that we propose can effectively quantify trust and the quantified value of an entity's trust is consistent with the behavior of the entity.

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A New Fuzzy MADM Approach and its Application to Project Selection Problem

Cited by 9 publications

References 28 publications

Evaluating the Packing Process in Food Industry Using Fuzzy X and S Control Charts

Evaluating the Packing Process in Food Industry Using Fuzzy X and S Control Charts

Efficacy of fuzzy MADM approach in Six Sigma analysis phase in automotive sector

Application of Fuzzy Comprehensive Evaluation Method in Trust Quantification

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