A New Approach to a Derivation of a Priority Vector from an Interval Comparison Matrix in a Group AHP Framework

A famous paper that has been cited more than four hundred times tried to combine (a) the preference ranking organization method for enrichment evaluations (PROMETHEE) and (b) the analytic hierarchy process (AHP) to construct a new method for multicriteria decision-making problems. The paper developed a consistent comparison matrix for their AHP by the defined first row and then they allowed the expert to change several entries in the comparison matrix. Hence, how to construct a new comparison matrix that is (i) consistent and (ii) satisfying the assigned values by the expert becomes a challenging problem. A recent article provided a reply to the above problem by the construction of all entries for the comparison matrix. However, they did not follow the original design proposed by the famous paper. In this paper, we present a new approach with a proposition that satisfies the original design of the famous paper and also achieves two goals (i) and (ii). The research gap of proof is fulfilled by this paper. Our findings explain that the original construction of the famous paper to develop a consistent comparison matrix only by the first row with several assigned values by an expert is indeed workable under two additional restrictions proposed by the recent article. We believe that after our proposition, researchers have the confidence to execute the original design of the paper that has been cited more than four hundred times.

Download Full-text

Production Yield Estimation by the Metamodel Method With a Boundary-Focused Experiment Design

Volume 3: 9th International Design Theory and Methodology Conference ◽

10.1115/detc97/dtm-3870 ◽

1997 ◽

Author(s):

Chinghsin Tu ◽

Russell R. Barton

Keyword(s):

Monte Carlo ◽

Robust Design ◽

Simulation Models ◽

Experiment Design ◽

Production Yield ◽

Design Stage ◽

Yield Estimation ◽

Simulation Code ◽

New Approach ◽

A Priority

Abstract The need for yield estimation strategies in the design stage is a priority recognized by industry. Yield estimates can be employed to assess the manufacturability of a design, and allow for modification to produce a robust design. Therefore, low yield of products can be avoided and costs for manufacturing can be reduced. This paper presents an accurate and time-efficient yield estimation approach for use with simulation models. We use a metamodel-based method, which is time-efficient compared to crude Monte Carlo yield estimation using the original simulation code. The approach employs a boundary-focused experiment design, which overcomes the inaccuracy of yield estimates that can occur when using a metamodel method. The results of two examples demonstrate the effectiveness of this new approach.

Download Full-text

Two Approximation Models of Fuzzy Weight Vector from a Comparison Matrix

Advances in Fuzzy Systems ◽

10.1155/2018/1975768 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9

Author(s):

Tomoe Entani

Keyword(s):

Analytic Hierarchy Process ◽

Weight Vector ◽

Analytic Hierarchy ◽

Lower Approximation ◽

Comparison Matrix ◽

Fuzzy Weight ◽

Interval Weight ◽

Hierarchy Process ◽

Interval Comparison ◽

Approximation Models

In this study, our uncertain judgment on multiple items is denoted as a fuzzy weight vector. Its membership function is estimated from more than one interval weight vector. The interval weight vector is obtained from a crisp/interval comparison matrix by Interval Analytic Hierarchy Process (AHP). We redefine it as a closure of the crisp weight vectors which approximate the comparison matrix. The intuitively given comparison matrix is often imperfect so that there could be various approaches to approximate it. We propose two of them: upper and lower approximation models. The former is based on weight possibility and the weight vector with it includes the comparison matrix. The latter is based on comparison possibility and the comparison matrix with it includes the weight vector.

Download Full-text