Pairwise comparison

About: Pairwise comparison is a research topic. Over the lifetime, 6804 publications have been published within this topic receiving 174081 citations.

Facing scalability issues in requirements prioritization with machine learning techniques

Abstract: Case-based driven approaches to requirements prioritization proved to be much more effective than first-principle methods in being tailored to a specific problem, that is they take advantage of the implicit knowledge that is available, given a problem representation. In these approaches, first-principle prioritization criteria are replaced by a pairwise preference elicitation process. Nevertheless case-based approaches, using the analytic hierarchy process (AHP) technique, become impractical when the size of the collection of requirements is greater than about twenty since the elicitation effort grows as the square of the number of requirements. We adopt a case-based framework for requirements prioritization, called case-based ranking, which exploits machine learning techniques to overcome the scalability problem. This method reduces the acquisition effort by combining human preference elicitation and automatic preference approximation. Our goal in this paper is to describe the framework in details and to present empirical evaluations which aim at showing its effectiveness in overcoming the scalability problem. The results prove that on average our approach outperforms AHP with respect to the trade-off between expert elicitation effort and the requirement prioritization accuracy.

Multiple‐use planning of forest resources by using the analytic hierarchy process

Abstract: In this paper, a decision analysis method called the Analytic Hierarchy Process (AHP) is applied to multiple‐use planning of forest resources. Principles of the method are presented and its properties are discussed with regard to multiple‐use planning. An illustrative example is given, in which the decision alternatives are produced using linear programming. Both quantitative and qualitative decision elements can be dealt with when the decision alternatives are evaluated using the AHP. The preferences of the decision‐maker are accommodated by pairwise comparisons between the decision elements. An additive priority model is estimated based on comparisons. Due to its simplicity, flexibility, and high effectiveness in analysing complex decision problems, the AHP is very applicable in multiple‐use planning.

Mathematical Structure of Voting Paradoxes: II. Positional Voting

Abstract: A theory is developed to explain all positional voting outcomes that can result from a single but arbitrarily chosen profile. This includes all outcomes, paradoxes, and disagreements among positional procedure outcomes as well as all discrepancies in rankings as candidates are dropped or added. The theory explains why each outcome occurs while identifying all illustrating profiles. It is shown how to use this approach to derive properties of methods based on pairwise and positional voting outcomes. Pairwise voting is addressed in the preceding companion paper [15]; the theory for positional methods is developed here.

Extension Of The Rough Set Approach To Multicriteria Decision Support

Abstract: The original version of the rough sets theory has proved to be particularly useful in the analysis of multiattribute classification problems under inconsistency following from information granulation, i.e. objects having the same description but belonging to different classes. It fails, however, when attributes with preference-ordered domains (criteria) have to be taken into account. In order to deal with problems of multicriteria decision analysis (MCDA), such as sorting, choice or ranking, the authors have extended the original rough sets theory in a number of directions. The main extension is the substitution of the indiscernibility relation by a dominance relation which permits approximation of ordered decision classes in multicriteria sorting. Second extension was necessary to approximate preference relations in multicriteria choice and ranking problems; it requires substitution of the data table by a pairwise comparison table, where each row corresponds to a pair of actions described by bina...