Leveling of Project Resources under Fuzzy- Stochastic Conditions

Due to the vital role resources play in the project's success or failure, in the last 60 years, much research has been done in the field of resource-leveling. The first studies considered the conditions of the project to be definite, but the following researches led to the uncertainty of the project conditions. Some of these uncertain studies assumed that the project conditions were only fuzzy, and some assumed that they were only stochastic. After introducing fuzzy-stochastic theory, project management research considered the conditions for a project to be fuzzy-stochastic. Due to the gap of this approach in resource leveling, this quantitative and developing research developed a multi-objective fuzzy-random resource-leveling model. In this research, the project execution time is considered as a fuzzy-random variable. Finally, the proposed model, which is among the NP-hard models, was solved by an NSGA-II algorithm in Matlab software. Two other algorithms developed this algorithm, namely control algorithm and variable decision preparation algorithm, and a control-memory, to solve the problem of project's diversity. The innovation of this research is noteworthy in two cases. The first is that the multi-objective resource-leveling model was presented in a fuzzy-random manner, and the second is that the NSGA-II algorithm was developed to solve it. Finally, the proposed algorithm's reproducibility, convergence, efficiency, and validity were discussed and approved.