Development of a scheduling model in the construction industry based on project quality under limited resource constraints

Articles in Press

Document Type : Research Article

Authors

1 Ph.D. candidate, Department of Civil Engineering, RO.C., Islamic Azad University, Roudehen, Iran.

2 Department of civil engineering, Roudehen Branch, Islamic Azad University, Tehran, Iran

Abstract

Project scheduling in the construction industry, especially under resource constraints, has always been a major challenge in project management. In this study, a multi-objective model was presented for scheduling multi-state projects with limited resources, which, in addition to time and cost, also considers the quality of activity execution as an independent objective function. In line with the NP-hard nature of this problem, two meta-heuristic algorithms, PSO and NSGA-III, were used to generate 3D Pareto fronts. The results showed that the NSGA-III algorithm was able to provide answers with relatively low time and cost-effective costs in both resource scenarios; especially in the second case, where the lowest cost of 3572 million rials for a period of 21 days and a quality of 69% was obtained. In contrast, PSO outperformed in the first case in achieving higher quality, producing solutions with a quality of 74% and a similar duration of 17 days, albeit at a higher cost (4304 million rials). Pareto front analysis showed that PSO produced a higher diversity of responses and provided balanced combinations among the three objectives, while NSGA-III tended to produce uniform responses with a focus on cost reduction. The main innovation of this research is the independent inclusion of the quality function in the scheduling model and the in-depth comparison of the performance of the two algorithms under different resource conditions, which can be used as an efficient tool for project decision makers to select the optimal option based on strategic priorities.

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Amirkabir Journal of Civil Engineering

Articles in Press, Accepted Manuscript
Available Online from 10 November 2025

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