Abstract
Construction projects that contain several identical or similar units are usually known as repetitive or linear projects. Repetitive projects are regarded as a wide umbrella that includes various categories of construction projects and represents a considerable portion of the construction industry, and contain uniform repetition of work. CPM has been proved to be inefficient in scheduling linear projects because CPM does not address two key aspects, which are maintaining crew work continuity, and achieving a constant rate of progress to meet a given deadline. Line-of-balance (LOB) is a linear scheduling methodology that produces a work schedule in which resource allocation is automatically performed to provide a continuous and uninterrupted use of resource. The fundamental principles of LOB have several shortfalls that raise many concerns about LOB, which need to be attuned and improved in order to suit the nature of construction projects. Hence, this thesis proposes a hybrid approach for scheduling linear projects that stresses on the limitation of LOB scheduling technique. To meet the physical limitation of resources in linear projects, this study presents a flexible optimization model for resolving resource constraint dilemma in linear scheduling problems .The proposed model utilizes a MATLAB code as the searching algorithm to automate the model formulation. The novelty of this model is supplementing a new optimization engine and a decision supporting system that formulate the optimal crews routing between different activities in different units and guarantee the optimal crew distribution for cost efficiency. This model investigates the mechanics of allocating a multi- task skilled workforce between different activities in different units that can lead to increased productivity, flexibility, and work continuity; besides, this model has the capability of accurately identifying the critical path in linear projects. Furthermore, to avoid day-to-day fluctuation in resource demands, this study encompasses a simulation model for handling the resource leveling in linear construction projects. The proposed model was implemented using crystal ball ribbon based on an entropy maximization metric. The entropy-maximization method accounts for such possibility of allowing activity duration to be stretched or crunched relying on activity type without affecting total completion date of a project and provides more optimized resource allocation solutions. A case study for a 4-km sewage pipeline is used to demonstrate the capability of the proposed models, which illustrates the implementation of the proposed models in construction projects.
Degree Name
MS in Construction Engineering
Graduation Date
2-1-2014
Submission Date
February 2015
First Advisor
Hosny, Ossama
Committee Member 1
Nassar, Khaled- Ezz el Din , Samer- Marzouk, Mohamed
Extent
171 p.
Document Type
Master's Thesis
Library of Congress Subject Heading 1
Maximum entropy method.
Library of Congress Subject Heading 2
Line of balance (Management)
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.
Institutional Review Board (IRB) Approval
Approval has been obtained for this item
Recommended Citation
APA Citation
Gouda, A.
(2014).Optimal crew routing for linear repetitive projects using graph theory and entropy maximization metric [Master's Thesis, the American University in Cairo]. AUC Knowledge Fountain.
https://fount.aucegypt.edu/etds/46
MLA Citation
Gouda, Ahmed. Optimal crew routing for linear repetitive projects using graph theory and entropy maximization metric. 2014. American University in Cairo, Master's Thesis. AUC Knowledge Fountain.
https://fount.aucegypt.edu/etds/46