Abstract

Repetitive, multi-stage linear projects, such as pipelines or highways, are primarily impacted by spatial and resource constraints during their execution. Cost overruns, delays, and inefficient resource allocation make construction management for such projects complex. Traditional scheduling techniques, such as Critical Path Method (CPM) and Line of Balance (LOB), are less efficient for scheduling dynamic, complex, and multi-objective projects. There are more advanced scheduling methods that can be applied as a decision-making process to determine the optimal timing of activities and achieve other objectives. One of those techniques is the Flexible Flow Shop model (FFS), which can be effectively applied to linear infrastructure projects due to its multi-stage and parallel machine structure. Such linear projects can be modeled as an FFS scheduling problem, in which jobs (pipeline segments or highway stations) pass through sequential stages (excavation, installation, backfilling) with flexible, non-identical machines (crews or equipment).

This research study introduces a novel framework that integrates Building Information Modeling (BIM) with the Flexible Flow Shop (FFS) scheduling model to develop, implement, and validate an advanced framework for scheduling linear infrastructure projects. The proposed framework applies the FFS advanced scheduling technique to enhance the scheduling efficiency of linear infrastructure projects and improve their visualization and execution effectiveness. The Non-dominated Sorting Genetic Algorithm (NSGA-II) is applied as a multi-objective optimization technique to minimize total costs, including both direct and indirect costs, total duration (or makespan), as well as total idle time of machines or crews. The proposed optimization model is developed in the powerful and widely used Python programming language to generate a Pareto front comprising non-dominated solutions, which enables stakeholders to select the best trade-offs between time and total cost based on their preferences.

Building Information Modeling (BIM) is utilized to connect the 3D infrastructure model and the schedule optimization model. BIM is used as a modeling and visualization tool to improve the interoperability and accuracy of projects. It is also applied to automate repetitive tasks and extract data and quantities. Additionally, a 4D simulation (3D + time) is created to visualize the schedule, enabling planners and decision-makers to monitor and control progress over time.

To verify the scheduling optimization model, a random generation model is developed to generate simple FFS problems. Those simple problems are solved by the FFS optimization model, allowing for a comparison between exact solutions obtained through exhaustive enumeration and the outputs of the developed optimization model. Such a comparison shows that optimization solutions match or approximate the exact results, indicating the accuracy of the developed model and the quality of its generated results. To validate the FFS model, it is applied to literature case studies, and the results of the developed optimization model outperformed literature results in generating a Pareto front of better solutions in terms of total cost, duration, and idle time. Specifically, the FFS model can achieve a reduction of up to 14.5% in the total makespan, reductions in idle time ranging from 10% to 18%, and cost savings of up to 8%.

The BIM-FFS framework is applied to a real-world linear infrastructure project to ensure the functionality of the BIM integration modules, including Autodesk Civil 3D, Dynamo for data extraction to Excel, and Synchro Pro for integrating the 3D model with the FFS-optimized schedule. The data compatibility and workflow show that the framework is accurate and practical. The results of the framework implementation include an optimized schedule, cost savings, reduced total duration, improved resource utilization efficiency, and enhanced visualization through the enhanced Gantt Chart and 4D simulation. Based on the project implementation and results, expert questionnaire responses indicate that more than 80% strongly agree on the framework's capability in reducing total cost, duration, and idle time of infrastructure linear projects, and more than 88% of responses strongly support its adaptation to such projects.

The developed BIM-based FFS scheduling framework is generic, since it can be applied to various categories of linear infrastructure projects with different construction methods. It is scalable, as it can process problems with varying numbers of jobs (units), stages (activities), and machines (crews). It is also flexible due to the flexibility associated with the execution sequence and the assignment of jobs to machines. Therefore, the implementation of the developed framework will be advantageous for linear infrastructure projects, improving informed decision-making processes.

School

School of Sciences and Engineering

Department

Construction Engineering Department

Degree Name

PhD in Construction Engineering

Graduation Date

Winter 1-31-2026

Submission Date

9-17-2025

First Advisor

Ossama Hosny

Second Advisor

Khaled Nassar

Committee Member 1

Samer Ezeldin

Committee Member 2

Ibrahim Abotaleb

Committee Member 3

Mohamed Mahdy Marzouk, Emad Elbeltagi

Extent

202 P.

Document Type

Doctoral Dissertation

Institutional Review Board (IRB) Approval

Approval has been obtained for this item

Disclosure of AI Use

Thesis editing and/or reviewing; Code/algorithm generation and/or validation

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Available for download on Thursday, September 17, 2026

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