Construction Program Management – Decision Making and Optimization Techniques

188 Pages·2016·2.801 MB·English

by  Ali D. Haidar (auth.)

Ali D. Haidar
Construction
Program
Management –
Decision Making
and Optimization
Techniques
–
Construction Program Management Decision
Making and Optimization Techniques
Ali D. Haidar
Construction Program
–
Management Decision
Making and Optimization
Techniques
123
Ali D.Haidar
DaralRiyadh-EngineeringandArchitecture
Riyadh
SaudiArabia
ISBN978-3-319-20773-5 ISBN978-3-319-20774-2 (eBook)
DOI 10.1007/978-3-319-20774-2
LibraryofCongressControlNumber:2015948783
SpringerChamHeidelbergNewYorkDordrechtLondon
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Preface
The recent trend in the construction industry is how to manage large and complex
programs. Multiple projects being built simultaneously, as part of government or
private programs, will need structured and sophisticated program management
techniques in order to deliver the vast and complex building works at hand with a
relatively short period. Without proper program management procedures, these
often huge, complex, multi-projects can take decades to construct with draining
budgets. With program management, the building works can be relatively short
spanning years with significant cost reduction.
Although program management methods have been applied successfully in the
USA (NASA and ARMY programs as an example), Europe (Marshall Plan), and
someoftheUnited Nationprograms,there havenotbeenliteraturenorresearchto
sustainthetheoriesbehindthesuccessfulimplementationofthesemethodsnortheir
proper and scientific know-how. All the focus has been on project management
techniques with their apparent short-folds for program constructability.
This book will look on the different program management methods, ranging
fromsimpledecision-makingtechniquesandstatisticsanalysistothemorecomplex
linear programming, and how program managers, directors, clients, stakeholders,
contractors, and consultants can benefit from the availability of these different
techniques. The book is unique in a way as it looks on how to apply new and
developedtechniquestooptimizeforthedeliveryofprogramsmainlyinthefieldof
artificial intelligence especially knowledge-based systems and genetic algorithms.
Theauthor’suniqueexperienceincomplexmanagement,programmanagement,
and his past research andstudiesinanalytical analysis and mathematical modeling
andartificialintelligencehasinducedhimtowritethisbooktowellinformreaders
about the different techniques that can be applied for future program execution.
No doubt indeed, the future of the construction industry will be in how to
execute programs, especially the Middle East war torn areas such as Syria, Libya,
Iraq, and now Yemen.As well, African countries and Asian countries will needto
beabletoexecutewell-managedprogramstobuildtheirinfrastructurewithlimited
time and constraint budgets.
v
Contents
1 Program Management Perspective . . . . . . . . . . . . . . . . . . . . . . . . 1
Introduction to Program Management. . . . . . . . . . . . . . . . . . . . . . . . 1
Program Framework. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
The Role of the Program Manager. . . . . . . . . . . . . . . . . . . . . . . . . . 5
Program Management Objectives. . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Necessity for the Development of Structured Systems . . . . . . . . . . . . 9
Program Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Decision-Making Approach for Program Management . . . . . . . . . . . . 13
Operations Research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Significance of Operations Research. . . . . . . . . . . . . . . . . . . . . . . . . 17
Optimization Models for Program Management. . . . . . . . . . . . . . . . . 18
Statistics and Forecasting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Linear Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Artificial Intelligent Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2 Decision-Making Principles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Decision Theory in Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Information Feed in Decisions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Program Management Quality. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
Organization Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
Program Organization Structure. . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
Responsibilities and Functions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
The Scalar Principle. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
System Understanding—A Program Approach. . . . . . . . . . . . . . . . . . 36
System Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
System Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
System Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Contingency View. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
Open and Closed Systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
Decision-Making Principles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
vii
viii Contents
Improving the Accuracy of Decision Making . . . . . . . . . . . . . . . . . . 44
Methodology and Knowledge Preparation. . . . . . . . . . . . . . . . . . . . . 44
Evaluation of Decision-Making Methods . . . . . . . . . . . . . . . . . . . . . 46
Contextual Influences. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
Formalization Advantages. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
Formalization Complexity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
Program Complexity as a Contingency Factor. . . . . . . . . . . . . . . . . . 51
Decision-Making Formalization Methods . . . . . . . . . . . . . . . . . . . . . 52
Reliability and Validity of Decision Making . . . . . . . . . . . . . . . . . . . 53
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3 Planning and Scheduling—A Practical and Legal Approach. . . . . . 57
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
Scheduling and Planning Development. . . . . . . . . . . . . . . . . . . . . . . 59
Critical Path Method Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
Activity Duration. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
Logical Relationship . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Forward Pass and Backward Pass . . . . . . . . . . . . . . . . . . . . . . . . . . 67
Critical Path . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
Advantages and Disadvantages of the Critical Path Method. . . . . . . . . 70
Float . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
Total Float and Free Float. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
Interfering Float. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
Independent Float . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Float Ownership . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Methods of Calculating Delays . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
Other Aspects of Time-Related Issues . . . . . . . . . . . . . . . . . . . . . . . 77
Critical Path Method’s Dynamic Nature—The Legal Approach . . . . . . 79
US Construction Case Law Pertinent to Extension
of Time and Delays. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
Standard Forms of Contract and Scheduling . . . . . . . . . . . . . . . . . . . 87
The Critical Path Method and Standard Forms of Contract . . . . . . . . . 89
The JCT Standard Form of Building Contract, 1998 Edition (JCT 98)
and 2005 Edition (JCT 2005) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
NEC3 Engineering and Construction Contract. . . . . . . . . . . . . . . . . . 91
ICE Conditions of Contract, Measurement Version, 7th Edition,
September 1999 (ICE 7th) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
Completion, Early Completion, and Acceleration. . . . . . . . . . . . . . . . 94
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
4 Mathematical Methods—Statistics and Forecasting . . . . . . . . . . . . 99
Statistics Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Sampling Theory. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
Variables, Index, and Summation. . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Contents ix
Index. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Averages or Measures of Central Tendency. . . . . . . . . . . . . . . . . . . . 102
Median. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
Mode. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
Dispersion or Variation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
Range . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
Mean Deviation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
Standard Mean of Deviation Is . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
Sampling Distribution. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
Unbiased Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
Confidence Interval Estimates of Population Parameters. . . . . . . . . . . 105
Confidence Intervals of Means . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
Forecasting. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
Delphi Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
Time Series Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
Least Square Estimates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
Moving Average . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
Exponential Smoothing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
Time Series Analysis—Decomposition. . . . . . . . . . . . . . . . . . . . . . . 114
Additive Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
Multiplicative Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
Double Moving Averages. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Forecasting a Series with Trend Using a Linear Moving Average . . . . 115
Double Exponential Smoothing: Holt’s Two-Parameter Method. . . . . . 117
Curve Fitting. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
Method of Least Squares . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
Forecasting Methods’ Uses and Disadvantages . . . . . . . . . . . . . . . . . 123
Applications of Statistics and Forecasting Methods
for Program Management. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
5 Operations Research and Optimization Techniques . . . . . . . . . . . . 131
Operations Research—Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 131
Operations Research Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
Operations Research Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
General Mathematical Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
Network Flow Programming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
Integer Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
Nonlinear Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
Dynamic Programming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
Stochastic Programming. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
Combinatorial Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
x Contents
Constraint Satisfaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
Convex Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
Heuristic Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
Optimization Techniques and Mathematical Programming. . . . . . . . . . 139
Linear Programming—An Introduction. . . . . . . . . . . . . . . . . . . . . . . 142
Linear Programming—Problem Formulation . . . . . . . . . . . . . . . . . . . 143
Terminology. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
Assumptions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
Basic Transformations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
Graphical Solution for Linear Programming—An Example. . . . . . . . . 146
A Standard Form for all Linear Programming Problems . . . . . . . . . . . 148
Linear Programming Practical Examples in Construction . . . . . . . . . . 148
Applications of Linear Programming in Program Management . . . . . . 154
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
6 Techniques for Intelligent Decision Support Systems . . . . . . . . . . . 159
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
Concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
Architecture and Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
Knowledge Base . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
The Rule Base. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
Knowledge Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
Working Memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
Inference Engine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
User Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
System Environments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
Knowledge Management in Construction . . . . . . . . . . . . . . . . . . . . . 170
Knowledge-Based Systems in Program Management . . . . . . . . . . . . . 170
Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
Genetic Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
Process. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
Evolution Operators. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
Time–Cost Trade-off . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
Construction Material Delivery Schedules. . . . . . . . . . . . . . . . . . . . . 180
Resource Leveling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
Finance-Based Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
Chapter 1
Program Management Perspective
Abstract Program management is concerned with the construction of a group of
related projects, carried out to achieve a defined objective or benefit to a client,
fallingundertheauspicesofaprogram.Theprogrammanagementprocessbalances
the key program constraints and provides a tool for making decisions throughout
the program cycle based on benchmark values, performance metrics, established
procedures,andtheprogramaims.Inordertofindbettersolutionsformanyaspects
of a program, including planning and scheduling, distribution of resources such as
labor and staff, optimizing the procurement process and minimizing costs while
achieving the program objectives, a program manager must be familiar with the
fundamental methodologies of heuristics methods, operations research, and
sophisticated intelligent techniques to deal with these complex issues. This book
will focus on the fundamental rules in planning and scheduling for program
activities,theapplicationofmethodsandtechniquesinthedecision-makingprocess
for often very complex situations, operations research and optimization and
mathematical modeling, and lately, the use of complex, efficient, and intelligent
systems in order to provide optimal solutions to program managers. The book
serves as an introduction for program managers for the above and introduces the
basic elements in critical path method (CPM), statistics and forecasting methods,
linear programming, knowledge-based systems, and genetic algorithms and their
applications as decision-making tools in key areas in program management.
Introduction to Program Management
Program management applies techniques that allow organizations to run multiple
related projects concurrently and obtain significant benefits from them as a col-
lection. A group of related projects, not managed as a program, is likely to run off
course and fail to achieve the desired outcome.
Program management is a fairly new technique and as such is not always well
understood. It is, however, clear that program management is an area of growing
©SpringerInternationalPublishingSwitzerland2016 1
A.D.Haidar,ConstructionProgramManagement–DecisionMaking
andOptimizationTechniques,DOI10.1007/978-3-319-20774-2_1