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Complex Ranking Procedures

Sandrasagra B., Soltys M.

Fundamenta Informaticae

2016

Vol. 144, nr 3/4

223--240

We propose a research program for developing a formal framework for ranking procedures based on the Pairwise Comparisons method. We are interested in the case where relatively few items are to be ranked with a complex procedure and according to a large number of criteria. A typical example of this scenario is a competition where several companies bid for a contract, and where the selection of the winner is done with multiple criteria according to an intricate selection procedure. Several other applications are suggested.

On the Properties of the Priority Deriving Procedure in the Pairwise Comparisons Method

Kułakowski K.

Fundamenta Informaticae

2015

Vol. 139, nr 4

403--419

The pairwise comparisons method can be used when the relative order of preferences among different concepts (alternatives) needs to be determined. There are several popular implementations of this method, including the Eigenvector Method, the Least Squares Method, the Chi Squares Method and others. Each of the above methods comes with one or more inconsistency indices that help to decide whether the consistency of input guarantees obtaining a reliable output, thus taking the optimal decision. This article explores the relationship between inconsistency of input and error of output. An error describes to what extent the obtained results correspond to the single expert’s assessments. On the basis of the inconsistency and the error, two properties of the weight deriving procedure are formulated. These properties are proven for eigenvector method and Koczkodaj’s inconsistency index. Several estimates using Koczkodaj’s inconsistency index for a principal eigenvalue, Saaty’s inconsistency index and the Condition of Order Preservation are also provided.

Heuristic Rating Estimation Approach to The Pairwise Comparisons Method

Kułakowski K.

Fundamenta Informaticae

2014

Vol. 133, nr 4

367--386

The Heuristic Ratio Estimation (HRE) approach proposes a new way of using the pairwise comparisons matrix. It allows the assumption that the weights of some alternatives (herein referred to as concepts) are known and fixed, hence the weight vector needs to be estimated only for the other unknown values. The main purpose of this paper is to extend the previously proposed iterative HRE algorithm and present all the heuristics that create a generalized approach. Theoretical considerations are accompanied by a few numerical examples demonstrating how the selected heuristics can be used in practice.