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Construction Site Layout Planning Using Simulation Open Access


Other title
Site Layout Planning
Genetic Algorithm
Facility layout planning
Type of item
Degree grantor
University of Alberta
Author or creator
Razavialavi, Seyedreza
Supervisor and department
AbouRizk, Simaan (Department of Civil and Environmental Engineering)
Examining committee member and department
Rankin, Jeff ( University of New Brunswick, Civil Engineering Department)
Al-Hussein, Mohamed (Department of Civil and Environmental Engineering),
Pourrahimian, Yashar (School of Mining and Petroleum Engineering, Department of Civil and Environmental Engineering)
Lipsett, Mike (Mechanical Engineering Department)
Mohamed, Yasser (Department of Civil and Environmental Engineering)
Department of Civil and Environmental Engineering
Construction Engineering and Management
Date accepted
Graduation date
2016-06:Fall 2016
Doctor of Philosophy
Degree level
Site layout planning, which involves identifying sizes and locations of temporary facilities, can have significant impacts on the safety, cost, time, and productivity of projects. Despite considerable research undertaken to improve efficiency of planning construction site layouts, most models developed for this purpose have overlooked the impact of facility size on project cost and cannot thoroughly model the dual impact of site layout variables (i.e., facility size and location) and construction plan variables (e.g., production rate, resources, and material delivery). In this research, given its ability to model complex dependencies among variables and to quantify impact of various variables such as site layout and construction planning variables on project cost, simulation was adopted to bridge the gaps identified in the literature. In this study, simulation is first used to quantitatively analyze the impact of facility size on project cost, where facilities considered were those temporarily containing materials and referred to as “material-dependent” facilities. To promote application of simulation in site layout planning, two tools are then developed. Using these tools, the site layout plan can be created and visualized in the simulation environment, which provides seamless interactions between the simulation model and site layout model through predefined elements. The first tool, which is a generic layout planning tool, can be used for the majority of construction projects. The second tool is a customized layout planning tool for typical tunnelling projects executed by tunnel boring machines (TBMs). Next, two novel frameworks are developed to find the optimum site layout. In the first framework, simulation is fully integrated with a heuristic optimization method (i.e., genetic algorithm), enabling planners to plan for site layout variables (i.e., size, location, and orientation of temporary facilities), construction plan variables (e.g., resources and material delivery plan), and to simultaneously optimize them in a unified model. The second framework, which is a decision making framework, consists of three phases: (1) Functionality Evaluation Phase (FEP), which qualitatively evaluates the layouts using genetic algorithm, (2) Cost Evaluation Phase (CEP), which quantitatively evaluates the layouts using simulation, and (3) Value Evaluation phase (VEP), which selects the most desirable layout considering both qualitative and quantitative aspects. The use of simulation to evaluate project cost in these frameworks results in more realistic and cost-efficient plans in practice. The developed tools and frameworks are applied to tunnelling, steel erection, and earthmoving projects to demonstrate their adaptability and suitability. The novelty of this research is to (1) quantify the impact of size of material-dependent facilities on project cost and time using simulation, (2) promote application of simulation in construction site layout planning by developing a generic simulation tool, (3) promote application of simulation in site layout planning of tunnelling projects by developing a special-purpose simulation tool, (4) simultaneously optimize site layout variables and construction planning variables by developing an integrated GA-simulation framework, and (5) optimize site layout planning based on both qualitative measures and cost-efficiency aspects by developing a decision-making framework.
This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for the purpose of private, scholarly or scientific research. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
Citation for previous publication
a) RazaviAlavi, S. and AbouRizk, S. (2015). “A hybrid simulation approach for quantitatively analyzing the impact of facility size on construction projects.” Automation in Construction, 60, pp. 39-48. b) RazaviAlavi, S. and AbouRizk, S. (2016). “Genetic Algorithm–Simulation Framework for Decision Making in Construction Site Layout Planning.” Journal of Construction Engineering and Management.

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