A two-stage logarithmic goal programming method for generating weights from interval comparison matrices

Wang, Ying‐Ming; Yang, Jian-Bo; Xu, Dong-Ling

doi:10.1016/j.fss.2004.10.020

Cited by 297 publications

(129 citation statements)

References 39 publications

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“…Guo et al [34] brought out a method to revise inconsistent IMPRs to obtain dual interval weights. Wang et al [35] proposed a two-stage logarithmic goal-programming model, which firstly minimizes inconsistency then generates weights under the condition of minimal inconsistency for IMPRs. Wang et al [36] designed a goal-programming model which was able to derive all of the interval weights by solving only one programming model.…”

Section: Saaty and Vargasmentioning

confidence: 99%

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The Interval Cognitive Network Process for Multi-Attribute Decision-Making

Yin

Cheng

et al. 2017

Symmetry

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Aiming at combining the good characteristics of a differential scale in representing human cognition and the favorable properties of interval judgments in expressing decision-makers' uncertainty, this paper proposes the interval cognitive network process (I-CNP) to extend the primitive cognition network process (P-CNP) to handle interval judgments. The key points of I-CNP include a consistency definition for an interval pairwise opposite matrix (IPOM) and a method to derive interval utilities from an IPOM. This paper defines a feasible region-based consistency definition and a transitivity based consistency definition for an IPOM. Both of the two definitions are equivalent to the consistency definition for a crisp pairwise opposite matrix (POM) when an IPOM is reduced to a POM. Two methods that are able to derive interval utilities from both consistent and inconsistent IPOMs are developed based on the two definitions. Four numerical examples are used to illustrate the proposed methods and to compare I-CNP to interval analytic hierarchy process (IAHP). The results show that I-CNP reflects the decision-makers' cognition better, and that the suggestions provided by I-CNP are more convincing. I-CNP provides new useful alternative tools for multi-attribute decision-making problems.

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Section: Saaty and Vargasmentioning

confidence: 99%

“…It is obvious that the ideas of (5) and (36) are the same, so, (35) can also be used to derive crisp utility vectors from POMs.…”

Section: Deriving An Interval Utility Vector Based On a Transitivity mentioning

confidence: 99%

The Interval Cognitive Network Process for Multi-Attribute Decision-Making

Yin

Cheng

et al. 2017

Symmetry

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“…There are the several procedures to attain the priorities in FAHP. The fuzzy least square method (Xu, 2000), method based on the fuzzy modification of the LLSM (Boender et al, 1989), geometric mean method (Buckley, 1985), the direct fuzzification of the method of Csutora and Buckley (2001), synthetic extend analysis (Chang, 1996), Mikhailov's fuzzy preference programming (Mikhailov, 2003) and two-stage logarithmic programming (Wang et al, 2005) are some of these methods. Chang's extent analysis is utilized in this research to evaluate the focusing problem.…”

Section: Proposed Modelmentioning

confidence: 99%

Multiple criteria inventory classification using fuzzy analytic hierarchy process

Kabir¹,

Hasin²

2012

ijiec

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A systematic approach to the inventory control and classification may have a significant influence on company competitiveness. In practice, all inventories cannot be controlled with equal attention. In order to efficiently control the inventory items and to determine the suitable ordering policies for them, multi-criteria inventory classification is used. In this paper, fuzzy analytic hierarchy process for multiple criteria ABC inventory classification has been proposed. Fuzzy Analytic Hierarchy process (Fuzzy AHP) is used to determine the relative weights of the attributes or criteria, and to classify inventories into different categories. To accredit the proposed model, it is implemented for the 351 raw materials of switch gear section of Energypac Engineering Limited (EEL), a large power engineering company of Bangladesh. In this approach, at first, related criteria have been selected (Unit price, last year consumption or annual demand, last use date, supplier, criticality, durability) and the weights of these criteria was determined using Fuzzy AHP. Then a score to each item was assigned for each criterion as triangular fuzzy number and the final normalized weighted score of each item using fuzzy set theory is calculate. Finally, Chang's extent analysis was used for the comparison of fuzzy numbers and the final scores are compared with each other. Then all items were classified into three classes according to their final score.

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“…IVPRs include interval-valued fuzzy preference relations (IVFPRs) (Genç et al 2010; Xu and Chen 2008) and interval-valued multiplicative preference relations (IVMPRs) (Wang et al 2005; Wang and Elhag 2007), which can be mutually transformed (Liu et al 2012). In this paper, we mainly focus on the IVFPR.…”

Section: Introductionmentioning

confidence: 99%