Project team selection using fuzzy optimization approach


Baykasoglu A., Dereli T., Das S.

CYBERNETICS AND SYSTEMS, vol.38, no.2, pp.155-185, 2007 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 38 Issue: 2
  • Publication Date: 2007
  • Doi Number: 10.1080/01969720601139041
  • Journal Name: CYBERNETICS AND SYSTEMS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.155-185
  • Dokuz Eylül University Affiliated: No

Abstract

With their high potential, high motivation, great problem-solving ability and flexibility, project teams are important work structures for the business life. The success of these teams is highly dependent upon the people involved in the project team. This makes the project team selection an important factor for project success. The project team selection can be defined as selecting the right team members, which will together perform a particular project/task within a given deadline. In this article, an analytical model for the project team selection problem is proposed by considering several human and nonhuman factors. Because of the imprecise nature of the problem, fuzzy concepts like triangular fuzzy numbers and linguistic variables ire used. The proposed model is a fuzzy multiple objective optimization model with fuzzy objectives and crisp constraints. The skill suitability of each team candidate is reflected to the model by suitability values. These values are obtained by using the fuzzy ratings method. The suitability values of the candidates and the size of the each project team are modeled as fuzzy objectives. The proposed algorithm takes into account the time and the budget limitations of each project and interpersonal relations between the team candidates. These issues are modeled as hard-crisp constraints. The proposed model uses fuzzy objectives and crisp constraints to select the most suitable team members to form the best possible team for a given project. A simulated annealing algorithm is developed to solve the proposed fuzzy optimization model. Software based on C++ computer programming language is also developed to experiment on the proposed model in forming project teams.