Most of the literature on reviewer assignment problem(RAP)considers fitness or efficiency as the evaluation criterion of an assignment,e.g.,the degree of matching between reviewers and proposals.In this study,we consi...Most of the literature on reviewer assignment problem(RAP)considers fitness or efficiency as the evaluation criterion of an assignment,e.g.,the degree of matching between reviewers and proposals.In this study,we consider fairness of an assignment and establish two multi-objective linear integer programming models for proposal assignment.We introduce a definition of fairness based on the closeness of social relationships between scholars.The closeness of social relationships is quantified based on social networks among reviewers and serves as part of objective functions.An improved space-partitioning algorithm is designed to solve the multi-objective models with integer objectives.When the problem size is large,two meta-heuristic algorithms are applied.Experiments on real and randomly generated cases are provided to illustrate the effectiveness of the proposed models and algorithms.展开更多
基金supported by the National Natural Science Foundation of China(NSFC Proj.71831006,71771070,72171065)Zhejiang Provincial Natural Science Foundation of China under Grant No.LZ20G010001Zhejiang Provincial Philosophy and Social Science Planning Project(23SYS11ZD).
文摘Most of the literature on reviewer assignment problem(RAP)considers fitness or efficiency as the evaluation criterion of an assignment,e.g.,the degree of matching between reviewers and proposals.In this study,we consider fairness of an assignment and establish two multi-objective linear integer programming models for proposal assignment.We introduce a definition of fairness based on the closeness of social relationships between scholars.The closeness of social relationships is quantified based on social networks among reviewers and serves as part of objective functions.An improved space-partitioning algorithm is designed to solve the multi-objective models with integer objectives.When the problem size is large,two meta-heuristic algorithms are applied.Experiments on real and randomly generated cases are provided to illustrate the effectiveness of the proposed models and algorithms.
