An algorithm and a decision support system for the panelist assignment problem: The case of TUBITAK

Abstract

Evaluation of project proposals in a proper manner and by the people who have expertise on the topics of the proposals is crucial not only for efficient deployment of resources, but also for credibility of the funding organizations. In this study, an algorithm and a decision support system (PaneLIST) are developed to provide a dynamic list of potential panelists from which the most appropriate set of panelists will be selected. PaneLIST, which is based on MS Excel VBA, has been validated by using the data of TUBITAK, primary organization responsible for research funding and conducts the comprehensive peer review activities for a long time. The results showed that the PaneLIST satisfies the required criteria to a great extent. Moreover, PaneLIST’s performance was compared with the results of the two integer programming models having the objectives of maximizing the sum of relevance scores (EBSkT) and minimizing the total deviation among the evalution levels of the proposals (EKSp) as well as a third model (EBSkT-5) which couples the two. The numerical experiments showed that PaneLIST attains high sum of relevance scores with a balanced distribution in terms of evaluation levels of proposals, thus shows regard to objectives of both EBSkT and EKSp at the same time; moreover, the results are so close (less than 1%) to the results of EBSkT-5 in which sum of relevance scores is maximized under a 5% constraint on the total deviation among the evalution levels of the proposals.