Fuzzy Resource-Constrained Project Scheduling Under Learning Considerations


International Conference on Intelligent and Fuzzy Systems, INFUS 2021, İstanbul, Turkey, 24 - 26 August 2021, vol.307, pp.631-637 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 307
  • Doi Number: 10.1007/978-3-030-85626-7_74
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.631-637
  • Keywords: Fuzzy modeling, Fuzzy project scheduling, Learning curve
  • Sivas Cumhuriyet University Affiliated: Yes


© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.This study proposes a new model to minimize the project completion time under learning with fuzzy resource-constrained. Experience is a significant factor in performing a job effectively by using time and resources more efficiently and finishing the job under the required time, resources, and financial constraints. It can produce more output under the same constraints because repeated experiences in a work environment accumulate more competence and knowledge. While it is mainly used in studies done for manufacturing environments, its usage in project management is relatively insufficient. In comparison, the number of measurable tasks to observe the learning effect on the process are abundant in project management. Long-term projects such as pipeline and highway construction projects must perform repetitive tasks and benefit from learning effects. Besides, it is essential to specialize in specific projects for organizations in today’s work environment, which can be achieved by expanding their portfolios to include similar projects. In this way, an organization provides an effective way to increase its power of competition by reducing the overall usage of time and resources for similar projects. It is shown that the proposed model has great potential in the more realistic determination of the completion time of the projects. Furthermore, it is helpful for the performance evaluation of the labor involved in the project management.