Optimized Scheduling of Repetitive Construction Projects under Uncertainty

193 Pages·2014·3.76 MB·English

Optimized Scheduling of Repetitive Construction
Projects under Uncertainty

Ibrahim Bakry

A thesis in the
Department
of
Building, Civil and Environmental Engineering

Presented in Partial Fulfillment of the Requirements
For the Degree of
Doctor of Philosophy (Building Engineering) at
Concordia University
Montreal, Quebec, Canada

June 2014
© Ibrahim Bakry, 2014
CONCORDIA UNIVERSITY
School of Graduate Studies
This is to certify that the thesis prepared
By: Ibrahim Bakry
Entitled: Optimized Scheduling of Repetitive Construction Project
under Uncertainty
and submitted in partial fulfillment of the requirements for the degree of

Doctor of Philosophy (Building Engineering)
complies with the regulations of the University and meets the accepted standards with
respect to originality and quality.
Signed by the final examining committee:
_________________________________Chair
Dr. Constantinos Constantinides
_________________________________External Examiner
Dr. Janaka Y. Ruwanpura
_________________________________External to Program
Dr. A. Dolatabadi
_________________________________Examiner
Dr. A. Hammad
_________________________________Examiner
Dr. Z. Zhu
_________________________________Thesis Co-Supervisor
Dr. O. Moselhi
_________________________________Thesis Co-Supervisor
Dr. T. Zayed
Approved by _________________________________
Dr. M. Elektorowicz
Graduate Program Director
June 16th 2014 _________________________________
Dr. C. Trueman, Interim Dean
Faculty of Engineering and Computer Science
Abstract
Optimized Scheduling of Repetitive Construction Projects under Uncertainty

Ibrahim Bakry, Ph.D. Candidate
Concordia University, 2014
Uncertainty is an inherent characteristic of construction projects. Neglecting uncertainties
associated with different input parameters in the planning stage could well lead to
misleading and/or unachievable project schedules. Many attempts have been made in the
past to account for uncertainty during planning for construction projects and many tools
and techniques were presented to facilitate modelling of such uncertainty. Some of the
presented techniques are widely accepted and used frequently like Project Evaluation and
Review Technique (PERT) and Monte Carlo Simulation, while others are more
complicated and less popular, such as fuzzy set-based scheduling. Although accounting
for uncertainty has been a topic of interest for more than four decades, it was rarely
attempted to account for uncertainty when scheduling repetitive construction projects.
Repetitive projects impose an additional challenge to the already complicated
construction scheduling process that accounts for the need to maintain crew work
continuity throughout project execution. This special characteristic necessitates
producing scheduling techniques specifically suited to resource driven scheduling.
Therefore, the main objective of this research is to produce a comprehensive scheduling,
monitoring and control methodology for repetitive construction projects that is capable of
iii
accounting for uncertainties in various input parameters, while allowing for optimized
acceleration and time-cost trade-off analysis. The proposed methodology encompasses
three integrated models; Optimized Scheduling and Buffering Model, Monitoring and
Dynamic Rescheduling Model and Acceleration Model. The first model presents an
optimization technique that accounts for uncertainty in input parameters. It employs a
modified dynamic programming technique that utilizes fuzzy set theory to model
uncertainties. This model includes a schedule defuzzification tool and a buffering tool.
The defuzzification tool converts the optimized fuzzy schedule into a deterministic one,
and the buffering tool utilizes user’s required level of confidence in the produced
schedule to build and insert time buffers, thus providing protection against anticipated
delays affecting the project. The Monitoring and Dynamic Rescheduling Model
capitalizes on the repetitive nature of these projects, by using actual progress on site to
reduce uncertainty in the remaining part of the schedule. This model also tracks project
progress through comparing the actual buffer consumption to the planned buffer
consumption. The Acceleration Model presents an iterative unit based optimized
acceleration procedure. It comprises a modified algorithm for identifying critical units of
the project to accelerate. This model presents queuing criteria that accounts for
uncertainty in additional cost of acceleration and for contractor’s judgment in relation to
prioritizing critical units for acceleration. Moreover, this model offers six strategies for
schedule acceleration and maintains crew work continuity.
Together, the three developed models offer an integrated system that is capable of
accounting for uncertainty in different variables through different project stages, aiming
at helping managers keep repetitive construction projects on track. The presented
iv
optimization technique is automated in an Object Oriented program; coded in C#
programming language. A number of case studies are analyzed and presented to
demonstrate and validate the capabilities and features of the presented methodology.

v
Acknowledgement
All praise and gratitude be to Allah, for it is only by his grace that good deeds are
accomplished.
I would like to express my deepest gratitude to my mentors, Dr. Moselhi and Dr. Zayed.
The years I spent learning from them are years that I will continue to cherish for the rest
of my life. Their support and encouragement have often been indispensable. Their
continuous guidance and advice on the academic and personal level is something I dearly
treasure.
I am grateful to my examining committee members, Dr. Janaka Ruwanpura, Dr. Amin
Hammad, Dr. Zhenhua Zhu and Dr. Ali Dolatabadi. Your comments and feedback played
a notable role in bringing my work to this level.
I want to thank my colleagues at the Automation and Construction Laboratory at
Concordia University, Ahmed Eweda, Hani Alzeraiee, Ali Montaser, Mona Abuhamad,
Sasan Golnaraghi, Ahmed Atef, Magdy Omar and Laya Sedghy I would also like to
thank Ibrahim Mashhour, Mohamed Gomaa and Ihab ElAghoury for their help and
support.
I want to extend my gratitude to the members of the Gezira Sporting Club Taekwondo
Team, your encouragement, although usually coming disguised as sarcasm, is much
appreciated.

vi
To my beloved mother, my inspiring father, my dear wife and to my
best friends, Mariam and Abdullatif

vii
Table of contents
LIST OF FIGURES .................................................................................................................... XII
LIST OF TABLES ....................................................................................................................... XV
LIST OF ACRONYMS ............................................................................................................XVII
CHAPTER 1: INTRODUCTION .............................................................................................. 1
1.1 Repetitive Construction Projects ...................................................................................................................... 1
1.2 Scheduling with Uncertainty ............................................................................................................................. 3
1.3 Problem Statement ............................................................................................................................................ 5
1.4 Research Objectives ........................................................................................................................................... 5
1.5 Methodology Overview ...................................................................................................................................... 6
1.6 Thesis Organization ........................................................................................................................................... 8
CHAPTER 2: LITERATURE REVIEW ................................................................................... 9
2.1 Introduction........................................................................................................................................................ 9
2.2 Scheduling of construction Projects ................................................................................................................. 9
2.2.1 Scheduling of Repetitive Construction Projects ....................................................................................... 10
2.2.2 Optimized Scheduling of Repetitive Construction Projects ..................................................................... 18
2.3 Using Buffers for Schedule Protection ........................................................................................................... 25
viii
2.3.1 Buffer Sizing Techniques Based on General representation of Uncertainty ............................................ 32
2.3.2 Buffer Sizing Techniques Addressing Specific Factors ........................................................................... 38
2.4 Schedule Acceleration ...................................................................................................................................... 45
2.5 Findings of Literature Review ........................................................................................................................ 51
CHAPTER 3: METHODOLOGY ............................................................................................ 54
3.1 Introduction...................................................................................................................................................... 54
3.2 Optimized Scheduling and Buffering Model ................................................................................................. 56
3.2.1 Modelling Uncertainty ............................................................................................................................. 59
3.2.2 Fuzzy Dynamic Programming .................................................................................................................. 61
3.2.3 Schedule Defuzzification and Buffering .................................................................................................. 66
3.2.4 Buffer Sizing and Insertion ...................................................................................................................... 68
3.3 Monitoring and Dynamic Rescheduling Model ............................................................................................. 80
3.3.1 Updating Activities .................................................................................................................................. 82
3.3.2 Reducing Uncertainty ............................................................................................................................... 83
3.3.3 Tracking Buffers ...................................................................................................................................... 86
3.4 Acceleration Model .......................................................................................................................................... 94
3.4.1 Identifying Activities to Accelerate.......................................................................................................... 95
3.4.2 Uncertainty in Additional Cost ................................................................................................................. 99
3.4.3 Contractors’ Judgment ........................................................................................................................... 100
3.4.4 Schedule Acceleration ............................................................................................................................ 101
CHAPTER 4: IMPLEMENTATION OF SCHEDULE OPTIMIZATION ....................... 104
4.1 Introduction.................................................................................................................................................... 104
ix
4.2 Design .............................................................................................................................................................. 105
4.2.1 Project Class ........................................................................................................................................... 106
4.2.2 Activity Class ......................................................................................................................................... 107
4.2.3 Crew Class ............................................................................................................................................. 108
4.2.4 Fuzzy Numbers ...................................................................................................................................... 109
4.3 OSRP ............................................................................................................................................................... 110
CHAPTER 5: CASE STUDIES ............................................................................................. 113
5.1 Introduction.................................................................................................................................................... 113
5.2 Optimized Scheduling and Buffering ........................................................................................................... 114
5.2.1 Least Cost Optimization ......................................................................................................................... 117
5.2.2 Least Duration Optimization .................................................................................................................. 129
5.2.3 Defuzzification and Buffering ................................................................................................................ 130
5.3 Schedule Acceleration .................................................................................................................................... 134
5.3.1 Case Study I ........................................................................................................................................... 134
5.3.2 Case Study II .......................................................................................................................................... 142
5.4 Results Analysis and Findings ...................................................................................................................... 148
5.4.1 Optimized Scheduling and Buffering ..................................................................................................... 148
5.4.2 Schedule Acceleration ............................................................................................................................ 152
CHAPTER 6: CONCLUSION ............................................................................................... 160
6.1 Summary and Concluding Remarks ............................................................................................................ 160
6.2 Research Contributions ................................................................................................................................. 163
x