Multi Mode Resource Constraint Construction Project Scheduling Problem (MRCPSP) Considering the Uncertainty in the Activities Duration and Delays
Choosing construction methods and how resources are allocated are important in the project control. The multi-mode resource constrained project scheduling problem (MRCPSP) is a significant subject in project management. The development of the above model for construction projects is an important iss...
Guardado en:
| Autores principales: | , , |
|---|---|
| Formato: | article |
| Lenguaje: | FA |
| Publicado: |
Iranian Society of Structrual Engineering (ISSE)
2019
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/581e2366051946ada0f959057cca76e5 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | Choosing construction methods and how resources are allocated are important in the project control. The multi-mode resource constrained project scheduling problem (MRCPSP) is a significant subject in project management. The development of the above model for construction projects is an important issue because of uncertainty. Fuzzy logic has been used to display the uncertainty in the duration of activities and the delay between them. This paper examines this problem and schedules project with providing an intelligent algorithm combining fuzzy sets and genetic algorithms (GAs). The Fuzzy MRCPSP problem can be considered as the scheduling of a set of activities with the aim of finding an activity operation mode and the activity operation priority; so that the resource constraints (renewable resources and non-renewable resources) as well as the precedence constraints are met simultaneously and the time for completion of the project is minimal. In the first step, the above problem is modeled mathematically, and then the model is coded using GA-based algorithm in Matlab software and finally the model is solved. The results of the implementation of this algorithm on the standard instances of the PSPLIB site, in comparison with the GAMS software, indicate the successful performance of the combined GA algorithm with fuzzy sets. The approach used in this research can be easily used by project managers. This prevents human errors caused by people who are responsible for controlling the project at resource leveling phase and is a way to the optimized project scheduling. |
|---|