Z-AHP: A Z-number extension of fuzzy analytical hierarchy process

Azadeh, A.; Saberi, Morteza; Atashbar, Nasim Zandi; Chang, Elizabeth; Pazhoheshfar, P.

doi:10.1109/dest.2013.6611344

Cited by 69 publications

(40 citation statements)

References 17 publications

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“…In order to determine the weight factors corresponding to each objective, fuzzy logic, the Z-number concept in particular, is used due to the existence of imprecise data given by experts in the production and manufacturing system, x [31]. The Z-number was introduced for the first time in 2011 [32].…”

Section: Z-ahpmentioning

confidence: 99%

Manufacturing Performance Measurement Using Fuzzy Multi-Attribute Utility Theory and Z-Number

Feylizadeh

Bagherpour

2018

TFAMENA

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SummaryThe Earned Value Management (EVM) has been extensively employed in the literature for analysing the schedule and cost performance indexes. However, the effects of risk factors on the project success have been previously ignored in the project management conventional context. In this paper, a well-organized project control and monitoring system is developed by incorporating the EVM basic principles, risk analysis, and utility theory for improving the performance of manufacturing systems. Weight values corresponding to the schedule performance index (SPI), the cost performance index (CPI), and the risk performance index (RPI) are calculated based on expert judgments using Z-number and Analytic Hierarchy Process (Z-AHP). Finally, a Multi-Attribute Utility Theory (MAUT) and Multi-Objective Linear Programming (MOLP) under fuzzy condition are utilized to demonstrate the applicability of the proposed approach. Sensitivity analysis indicated the risk performance is the most sensitive when compared with the schedule and the cost index. The approach given in this paper can be further employed by both academicians and managers in heavy intensive manufacturing systems. Key words: Manufacturing systems, Multi-Objective Linear Programming (MOLP), Earned Value Management (EVM), Risk analysis, Z-Number IntroductionThe Earned Value Management (EVM) is a famous tool assisting project managers in checking the project schedule and budget to see whether they are on track. The EVM provides an excellent insight into the current trend in the project as well as a study on the planning of the project budget and the time required for the project completion. Traditional EVM-based control systems are used to analyse and detect the current schedule and cost performance indexes. In addition, there are some other models tending to provide a good insight into the cost required for the completion of the project. Thus, the schedule performance index SPI(t) has been presented as a new metric in the EVM context where the schedule performance index has been calculated based on the earned schedule and not based on the conventional earned value.The EVM has rarely been merged with other fields under investigation. The EVM has also been incorporated within financial issues and a new index, entitled financial performance

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Section: Z-ahpmentioning

confidence: 99%

Manufacturing Performance Measurement Using Fuzzy Multi-Attribute Utility Theory and Z-Number

Feylizadeh

Bagherpour

2018

TFAMENA

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“…Various researches were conducted to incorporate uncertainty into AHP such as fuzzy AHP (FAHP; Chang, 1996;Wang, Luo, & Hua, 2008), Z-AHP (Azadeh, Saberi, Atashbar, Chang, & Pazhoheshfar, 2013), interval type-2 fuzzy AHP (IT2 FAHP; Kahraman, Öztayşi, Sarı, & Turanoğlu, 2014), AHP with intuitionistic fuzzy sets (IFAHP) (Sadiq & Tesfamariam, 2009), AHP with interval-valued intuitionistic fuzzy sets (IVIFAHP; Wu, Huang, & Cao, 2013), AHP with hesitant fuzzy linguistic term sets (Tüysüz & Şimşek, 2017), and rough-AHP (Aydogan, 2011) can be mentioned. In general, these studies consider either the degree of confidence of pairwise comparison value (IFAHP and IVIFAHP) or determine an interval of comparisons such as rough-AHP, IT2 FAHP and Z-AHP.…”

Section: Survey On Applications Of Uncertain Theories In Ahpmentioning

confidence: 99%

Maintenance strategy selection with risky evaluations using RAHP

Seiti

Tagipour

Hafezalkotob

et al. 2017

Multi Criteria Decision Anal

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In recent years, maintenance, especially its preventive type, has been seen as an effective and considerable factor in improving the functions of machines. Maintenance plays a vital role in organizations by keeping and increasing the reliability, accessibility, the quality of products, risk mitigation, return improvement, and safety. An effective maintenance programme can be realized by implementing a proper maintenance strategy. Therefore, maintenance and its strategies have a special status in industries. However, selecting a proper maintenance strategy has always been a complex process because maintenance is a nonrepetitive task. Likewise, the lack of failure records and constant changes in the conditions of machines makes it further complicated. Hence, the decision‐making also depends on experts' opinions and because some kind of risk and uncertainty are always there in experts evaluations, the reliability of evaluations is questionable. The present study was aimed to develop a risk‐based model grounded on the analytical hierarchical process, namely, RAHP, to meet this need of maintenance. A case study from a steel rolling company was considered to evaluate the effectiveness of this model.

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“…12.1 that fuzzy IF-THEN rules occur in both BCWW and ICWW problems. ACWW problems involve intricate assignments 2 Detailed discussions about these tests are given in [68, pp. 312-313].…”

Section: Because Words Mean Different Things To Different People Thementioning

confidence: 99%

“…Because the GEP is the main tool for manipulating Z-numbers [2,42,43,76,126,151], the connections between ACWW and computing with Z-numbers is also an interesting topic for future research.…”

Section: Advanced Computing With Words: Status Challenges and Futurementioning

confidence: 99%

Advanced Computing with Words: Status and Challenges

Mendel

Rajati

2015

Towards the Future of Fuzzy Logic

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In this chapter, we focus on the status of Advanced Computing with Words (ACWW) and the challenges that it may encounter in the future. First, we elaborate on the notion of Computing with Words (CWW) and its various subareas. Then we present some non-engineering ACWW problems and connect them to more realistic engineering problems, after which we provide a roadmap for solving ACWW problems, and show how the Generalized Extension Principle (GEP) can be used to formulate their solutions. We also propose a syllogistic approach to solving ACWW problems that also uses the Extension Principle but in a different way. Finally, we discuss present and future challenges to ACWW, i.e. we explain what challenges ACWW encounters given the current trend of data abundance and widespread use of Internet for dealing with questions posed in natural languages. Introduction: Computing with Words and Advanced Computing with WordsComputing with Words (CWW or CW) [11,29,34,66,69,70,75,91,104,109,142,144,147,154] was probably conceived as the main area of application of fuzzy logic [132] when the field was originated. It is a methodology of computation whose objects are words rather than numbers, although those words are linked to numbers and classical calculations that can be carried out by computing machinery, via membership functions of fuzzy sets associated with words. To do that, a process called precisiation of meaning [152] is essential, which, in a nutshell, is determining membership functions of the fuzzy sets that model the words. Zadeh distinguishes two subareas for CWW:1. Basic Computing with Words (BCWW), which mainly deals with descriptions of complex systems in terms of fuzzy IF-THEN rules [134]. Soft constraints are generally possibilistic, i.e. they describe (physical) attributes like speed, temperature,

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Z-AHP: A Z-number extension of fuzzy analytical hierarchy process

Cited by 69 publications

References 17 publications

Manufacturing Performance Measurement Using Fuzzy Multi-Attribute Utility Theory and Z-Number

Manufacturing Performance Measurement Using Fuzzy Multi-Attribute Utility Theory and Z-Number

Maintenance strategy selection with risky evaluations using RAHP

Advanced Computing with Words: Status and Challenges

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