Volume 35, Issue 2 (IJIEPR 2024)                   IJIEPR 2024, 35(2): 1-18 | Back to browse issues page


XML Print


1- Department of Industrial Engineering, Faculty of Technology, and Engineering, University of Qom, Qom, Iran
2- Faculty of Industrial Engineering, Tarbiat Modares university, Tehran, Iran
3- Department of Industrial Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran , mokhtari_ie@kashanu.ac.ir
Abstract:   (962 Views)
Abstract. One of the important problems in managing construction projects is selecting the best alternative for activities' execution to minimize the project's total cost and time. However, uncertain factors often have negative effects on activity duration and cost. Therefore, it is crucial to develop robust approaches for construction project scheduling to minimize sensitivity to disruptive noise factors. Additionally, existing methods in the literature rarely focus on environmentally conscious construction management. Achieving these goals requires incorporating the project scheduling problem with multiple objectives. This study proposes a robust optimization approach to determine the optimal construction operations in a project scheduling problem, considering time, cost, and environmental impacts (TCE) as objectives. An analytical algorithm based on Benders decomposition is suggested to address the robust problem, taking into account the inherent uncertainty in activity time and cost. To evaluate the performance of the proposed solution approach, a computational study is conducted using real construction project data. The case study is based on the wall of the east coast of Amirabad port in Iran. The results obtained using the suggested solution approach are compared to those of the CPLEX solver, demonstrating the appropriate performance of the proposed approach in optimizing the time, cost, and environment trade-off problem.
Full-Text [PDF 647 kb]   (258 Downloads)    
Type of Study: Research | Subject: Project Control
Received: 2023/10/5 | Accepted: 2024/04/20 | Published: 2024/06/21

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.