A model for project team formation in complex engineering projects under uncertainty

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 fo...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Kybernetes Ročník 46; číslo 7; s. 1131 - 1157
Hlavní autoři: Hosseini, S. Mahdi, Akhavan, Peyman
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Emerald Publishing Limited 10.08.2017
Emerald Group Publishing Limited
Témata:
Classification
Composition effects
Computer simulation
Decision making
Design optimization
Employees
Fuzzy sets
Genetic algorithms
Integer programming
Multiple objective analysis
Product development
Shipbuilding
Sorting algorithms
Uncertainty
Knowledge sharing
Fuzzy sets
NSGA-II
Credibility measure
Multi-objective optimization
Team formation
ISSN:0368-492X, 1758-7883
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0368-492X
1758-7883
DOI:10.1108/K-06-2015-0150