Optimal Allocation of Proposals to Reviewers to Facilitate Effective Ranking

Wade D. Cook · Boaz Golany · Moshe Kress · Michal Penn · Tal Raviv

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Game Theory and Voting Systems Multi-Criteria Decision Making Complexity and Algorithms in Graphs

Abstract

Peer review of research proposals and articles is an essential element in research and development processes worldwide. Here we consider a problem that, to the best of our knowledge, has not been addressed until now: how to assign subsets of proposals to reviewers in scenarios where the reviewers supply their evaluations through ordinal ranking. The solution approach we propose for this assignment problem maximizes the number of proposal pairs that will be evaluated by one or more reviewers. This new approach should facilitate meaningful aggregation of partial rankings of subsets of proposals by multiple reviewers into a consensus ranking. We offer two ways to implement the approach: an integer-programming set-covering model and a heuristic procedure. The effectiveness and efficiency of the two models are tested through an extensive simulation experiment.

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1991The reliability of peer review for manuscript and grant submissions: A cross-disciplinary investigation 1978Priority Ranking and Consensus Formation 1985Ranking with Partial Information: A Method and an Application 2001The Decision-Making Constraints and Processes of Grant Peer Review, and Their Effects on the Review Outcome 1998Peer Review for Journals as it Stands Today—Part 1 1988Deriving weights from pairwise comparison ratio matrices: An axiomatic approach 1992Ordinal Information and Preference Structures: Decision Models and Applications 2001Peer Review in the Funding of Research in Higher Education: The Australian Experience

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2010Assigning Papers to Referees 2006A hybrid knowledge and model approach for reviewer assignment 2015An intelligent decision support approach for reviewer assignment in R&D project selection 2010A decision support approach for assigning reviewers to proposals 2014Process Analytics Approach for R&D Project Selection

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