![Sample our Built Environment journals, sign in here to start your access, Latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5926/TOC-Subject-Sample-2021-Built-Environment.jpg"})
Abstract
The resource constrained project-scheduling problem (RCPSP) aims to minimize the duration of a project. RCPSP is prevalently used in programming the projects with high number of activities and resources such as construction projects. In this study, 240 projects such as residential, office, school, etc. are designed and programmed under limited resources. The resource amounts of these projects are determined using three priority rules, these are Latest Finish Time, Minimum Slack Time and Maximum Remaining Path Length which have the highest performance according to the literature, in the amounts of 2, 4, 6 and 8. The project times are estimated using artificial neural network (ANN). A correlation coefficient of 0.70 was obtained from the ANN estimation model.
Additional information
Notes on contributors
Ömer Özkan
Ömer ÖZKAN. He is a Visiting Researcher in University of Pittsburgh. He is an Assoc. Prof. Dr in the Technology Faculty, Civil Engineering Department at Sakarya University, Turkey. His research interests include the construction management, particularly resources constrained project scheduling.
Ümit Gülçiçek
Ümit GÜLÇIÇEK. He is a PhD student and works as an instructor in Kahramanmaras Sutcu Imam University. His research interests include the construction management, cost and forecasting of construction and particularly resources constrained project scheduling.