Title

BIM-Based model for the automatic generation and optimization of planning and 4-D scheduling for concrete skeleton: A graph theory approach

Abstract

With the rapid increase in complexity in the building industry, project managers are facing more and more complex decision environments and problems. Therefore, it would be beneficial to aid project managers in making sound decisions regarding the intelligent knowledgeable selection of the optimal construction methodology for concrete skeletons while making use of Building Information Modelling (BIM). BIM models’ usage fused with modelling, and simulation tools allow efficiently prototyping a building and examining its construction activities before breaking the ground. For this purpose, an intelligent framework with advanced computational tools and algorithms is designed and created to achieve a higher degree of design-construction integration and spatial integration of individual building elements in order to achieve an optimized sequencing of building elements (in terms of time and resource utilization). This research presents a model framework that extracts building elements, along with their topological relationships and geometrical properties, from an existing fully designed Building Information Model (BIM Model) to be mapped into a directed acyclic Elemental Graph Data Model (EGDM). The framework incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. The EGDM can undergo a broad range of measures that aids in discovering more information about the construction of the project under study. By electing elemental construction method(s) available in the construction site for each element category, Elemental Construction Method Graph(s) (ECMG) are generated, and Entra-elemental relationships are added in order to mimic any practical constraints in real life. Using graph search algorithms, Depth First Search (DFS) and topological sortings, and an innovative Genetic Algorithm (GA) inspired by Tabu Search (TS), possible construction sequences are generated. The sequences were, then, simulated, hence, recommending the Optimized Elemental Construction Method, Schedule & Resources, and, hence, generating 4D BIM models. An application was developed to implement the framework and test its robustness. It was implemented with the aid of AutoDesk Revit APIs in a C# platform. Ultimately, the model was tested, verified and validated. Testing and verification were performed with the aid of a set of automatically generated test cases which were built by means of an add-in just developed for testing purposes. Thereafter, the model was validated with the aid of a set of real case studies. Results revealed an improvement in project’s total construction duration, a significant saving in the time of generation of the 4-D construction schedule, in addition to human interference elimination. Moreover, this shows how promising the area of planning through the generation of construction sequences is. Keywords: Building Information Modelling (BIM), Elemental Graph Data Model (EGDM), Geometric and topological data models, Graph theory, Elemental Construction Method Graph (ECMG), Depth-first Search, Topological Sorting, Construction Sequence, Genetic Optimization, Tabu Search, and Automated Construction Scheduling.

Department

Construction Engineering Department

Graduation Date

2-1-2019

Online Submission Date

January 2019

First Advisor

Nassar, Khaled

Committee Member 1

Nassar, Khaled

Committee Member 2

Ezeldin, Samer

Document Type

Doctoral Dissertation

Extent

300 p.

Rights

The author retains all rights with regard to copyright. The author certifies that written permission from the owner(s) of third-party copyrighted matter included in the thesis, dissertation, paper, or record of study has been obtained. The author further certifies that IRB approval has been obtained for this thesis, or that IRB approval is not necessary for this thesis. Insofar as this thesis, dissertation, paper, or record of study is an educational record as defined in the Family Educational Rights and Privacy Act (FERPA) (20 USC 1232g), the author has granted consent to disclosure of it to anyone who requests a copy.

IRB

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