Solving reviewer assignment problem in software peer review: An approach based on preference matrix and asymmetric TSP model

Optimized reviewer assignment can effectively utilize limited intellectual resources and significantly assure review quality in various scenarios such as paper selection in conference or journal, proposal selection in funding agencies and so on. However, little research on reviewer assignment of software peer review has been found. In this study, an optimization approach is proposed based on students' preference matrix and the model of asymmetric traveling salesman problem (ATSP). Due to the most critical role of rule matrix in this approach, we conduct a questionnaire to obtain students' preference matrixes and convert them to rule matrixes. With the help of software ILOG CPLEX, the approach is accomplished by controlling the exit criterion of ATSP model. The comparative study shows that the assignment strategies with both reviewers' preference matrix and authors' preference matrix get better performance than the random assignment. Especially, it is found that the performance is just a little better than that of random assignment when the reviewers' and authors' preference matrixes are merged. In other words, the majority of students have a strong wish of harmonious development even though high-level students are not willing to do that.