Topic
Pairwise comparison
About: Pairwise comparison is a research topic. Over the lifetime, 6804 publications have been published within this topic receiving 174081 citations.
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TL;DR: The CRS4EAs was empirically compared to NHST within a computational experiment conducted on 16 evolutionary algorithms and a benchmark suite of 20 numerical minimisation problems, and the analysis of the results shows that the CRS3EAs is comparable with NHST but may also have many additional benefits.
110 citations
TL;DR: In this paper, it is shown that when point estimates are difficult to determine, distributions describing feasible judgments may be more appropriate than point estimates, and that levels of confidence can be developed, expected weights can be calculated and expected ranks can be determined.
110 citations
01 Jan 2006
TL;DR: Way in which pure pairwise testing approach needs to be modified to become practically applicable and on features tools need to offer to support a tester trying to use pairwise in practice are focused on.
Abstract: Pairwise testing has become an indispensable tool in a software tester’s toolbox. The technique has been known for almost twenty years [22] but it is the last five years that we have seen a tremendous increase in its popularity. Information on at least 20 tools that can generate pairwise test cases, have so far been published [1]. Most tools, however, lack practical features necessary for them to be used in industry. This paper pays special attention to usability of the pairwise testing technique. In particular, it does not describe any radically new method of efficient generation of pairwise test suites, a topic that has already been researched extensively, neither does it refer to any specific case studies or results obtained through this method of test case generation. It does focus on ways in which pure pairwise testing approach needs to be modified to become practically applicable and on features tools need to offer to support a tester trying to use pairwise in practice. The paper makes frequent references to PICT, an existing and publicly available tool built on top of a flexible combinatorial test case generation engine, which implements several of the concepts described herein.
109 citations
TL;DR: It is shown that the MVR problem is equivalent to the minimum distance problem, which can be represented in several forms-in particular as a problem of determining the minimum feedback edge set in a graph and as a mixed integer generalized network problem.
Abstract: This paper examines the problem of rank ordering a set of players or objects on the basis of a set of pairwise comparisons arising from a tournament. The criterion for deriving this ranking is to have as few cases as possible where player i is ranked above j while i was actually defeated by j in the tournament. Such a situation is referred to as a violation. The objective, therefore, is to determine the Minimum Violations Ranking MVR. While there are situations where this ranking would be allowed to contain ties among subsets of objects, we will concern ourselves herein with linear ordering no ties. A series of examples are given where this requirement would seem to be appropriate. In order to put the MVR problem into proper perspective we introduce the concept of a distance on the set of tournaments. A set of natural axioms is presented which any such distance measure should obey, and it is proven that in the presence of these axioms a unique such measure exists. It is then shown that the MVR problem is equivalent to the minimum distance problem, which can be represented in several forms-in particular as a problem of determining the minimum feedback edge set in a graph and as a mixed integer generalized network problem. This opens up a wide scope of possible solution procedures for the MVR problem. An optimal algorithm is presented along with computational results. In addition, various heuristics are discussed including an improved heuristic referred to as the Iterated Kendall method.
109 citations
TL;DR: In this article, the pairwise comparison input data is treated as random variables, which will allow the determination of whether the differences between alternatives are statistically significant, and the AHP has become a popular and practical tool for dealing with complex decision problems.
109 citations