A Method of Partner Selection for Knowledge Collaboration Teams using Weighted Social Network Analysis

Abstract

Partner selection is the primary aspect of the formation of knowledge collaboration teams (KCTs). We propose a method of partner selection for KCTs based on a weighted social network analysis (SNA) method in which the individual knowledge competence and the collaboration performance of candidates are both considered. To select the desired partners, a biobjective 0-1 model is built, integrating the knowledge competence and collaboration performance, which is an NP-hard problem. Then, a multiobjective genetic algorithm (Moga) is developed to solve the proposed model. Finally, a real-world example is provided to illustrate the applicability of the model, and the Moga is implemented to search for Pareto solutions of partner selection for KCT in this case. Moreover, some simulation examples are used to test the efficiency of the algorithm. The results suggest that the proposed method can support effective and practical partner selection.