TY  - JOUR
AB  - Purpose This paper aims to develop a model for selecting project team members. In this model, while knowledge sharing among individuals is maximized, the project costs and the workload balance among employees are also optimized.Design/methodology/approach The problem of project team formation is formulated as a fuzzy multi-objective 0-1 integer programming model. Afterward, to deal with uncertainty in the decision-making on the candidates’ abilities and the project requirements, the fuzzy multi-objective chance-constrained programming approach is adopted. Finally, by combining the non-dominated sorting genetic algorithm II and the fuzzy simulation algorithms, a method is proposed to solve the problem.Findings The computational results of the proposed model in a case study of project team formation in a large Iranian company from the shipbuilding industry evidently demonstrated its effectiveness in providing Pareto-optimal solutions for the team composition.Originality/value Seemingly for the first time, this paper develops a model to optimize knowledge sharing and improve the project efficiency through the selection of appropriate project team members.
VL  - 46
IS  - 7
SN  - 0368-492X
DO  - 10.1108/K-06-2015-0150
UR  - https://doi.org/10.1108/K-06-2015-0150
AU  - Hosseini S. Mahdi
AU  - Akhavan Peyman
PY  - 2017
Y1  - 2017/01/01
TI  - A model for project team formation in complex engineering projects under uncertainty: A knowledge-sharing approach
T2  - Kybernetes
PB  - Emerald Publishing Limited
SP  - 1131
EP  - 1157
Y2  - 2024/05/12
ER  -