Minimizing deviations from the group mean: a new linear programming approach for the two-group classification problem

Article Abstract:

A new linear programming method in solving the two-group classification problem in discriminant analysis is presented. It is grounded on the notion that objects within the same group should be more similar than objects between groups. When applied to the classification problem in discriminant analysis, the approach states that the classification score of an object should be nearer to its mean classification score but further from the mean classification score of the other group. In an actual managerial problem and simulated data, the approach proves to work well in groups separation and group-membership predictions of new objects.

Linear programming, Multivariate analysis, Discriminant analysis

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A unified approach to AHP with linking pins

Article Abstract:

A generalized formula for the generation of valid approaches for criteria comparison using the analytic hierarchy process (AHP) is presented. The technique has been developed as the need for prescribed rules in criteria paired comparison estimates and subsequent analysis has become apparent to decision makers. This is shown by the existence of alternative forms of AHP that relates the criterion level and the alternative level of the hierarchy.

Decision-making, Multiple criteria decision making, Decision making

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Magnitude adjustment for AHP benefit/cost ratios

Article Abstract:

Research describing analytic hierarchy process modeling is presented. In particular its application to cost-benefit ratios and the magnitude adjustments required for meaningful results are investigated.

Operations Research, Management science, Cost benefit analysis, Social hierarchies

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