A model for project team formation in complex engineering projects under uncertainty: A knowledge-sharing approach. Issue 7 (7th August 2017)

• Record Type: Journal Article
• Authors: Hosseini, S. Mahdi; Akhavan, Peyman
• Is Part Of: Kybernetes. Volume 46:Issue 7(2017)
• Page Start: 1131
• Page End: 1157
• Publication Date: 2017-08-07
• Subjects: Multi-objective optimization -- Knowledge sharing -- Fuzzy sets -- NSGA-II -- Credibility measure -- Team formation; Cybernetics -- Periodicals; Systems engineering -- Periodicals; 003.505
• DOI: 10.1108/K-06-2015-0150
• Languages: English
• ISSNs: 0368-492X

Abstract

Abstract : 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.