A method for member selection of R&D teams using the individual and collaborative information

The member selection is an important decision problem in the formation of R&D teams. Selecting suitable members will facilitate the success of R&D projects. In the existing methods for partner selection, the individual information to measure the individual performance of members is mostly used, while the collaborative information to measure the collaborative performance between members is seldom considered. Therefore, this paper proposes a method for member selection of R&D teams, in which both the individual information of members and the collaborative information between members are considered. In order to select desired members, a bi-objective 0-1 programming model is built using the individual and collaborative information. To solve the model, a muiti-objective genetic algorithm is developed since the model is NP-hard. A practical example followed by simulation experiment is used to illustrate the applicability of the proposed method. Additionally, the experimental results show that the proposed method can support satisfactory and high quality member selection. (C) 2008 Elsevier Ltd. All rights reserved.