Abstract
Key players problems aim to detect multiple players that optimize certain metrics on the network structure and function from two aspects, i.e., the negative effect and positive effect. However, most existing researches focus on modeling for the former, and how to model for the latter needs further exploration. In this paper, we first propose an integer linear programming model with distance-based connectivity for the positive effect. Then, to solve the proposed model, we design a novel heuristic algorithm by combining with local search enforcement in a greedy framework. Finally, we conduct many synthetic and real-world networks to validate the effectiveness and efficiency of the proposed approach. The experimental results show that the proposed approach achieves superior performance on detecting multiple key players, compared with some traditional methods.
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