Construction scheduling, cost optimization, and management: a new model based on neurocomputing and object technologies

BOOK COVER......Page 1
TITLE......Page 2
COPYRIGHT......Page 3
DEDICATION......Page 4
CONTENTS......Page 5
PREFACE......Page 11
ACKNOWLEDGMENT......Page 12
ABOUT THE AUTHORS......Page 13
1 INTRODUCTION......Page 14
2.1 INTRODUCTION......Page 16
2.2.3 Resource Allocation and Scheduling......Page 17
2.2.5 Other Applications of BP and Other Neural Network Models in Construction Engineering and Management......Page 18
2.3.1 Pattern Recognition and Machine Learning in Structural Analysis and Design......Page 19
2.3.2 Design Automation and Optimization......Page 21
2.3.4 Structural Condition Assessment and Monitoring......Page 22
2.3.5 Structural Control......Page 23
2.3.7 Structural Material Characterization and Modeling......Page 24
2.4 ENVIRONMENTAL AND WATER RESOURCES ENGINEERING......Page 25
2.5 TRAFFIC ENGINEERING......Page 26
2.7 GEOTECHNICAL ENGINEERING......Page 27
2.8.3 Radial Basis Function Neural Networks......Page 28
2.9.2 Fuzzy Logic......Page 29
2.9.3 Wavelets......Page 30
3.2 COLD-FORMED STEEL DESIGN OPTIMIZATION......Page 32
3.3 MINIMUM WEIGHT DESIGN OF COLD-FORMED STEEL BEAMS......Page 33
3.3.1 Bending Strength Constraint......Page 35
3.3.4 Constraint on Web Crippling Strength......Page 37
3.3.6 Deflection Constraint......Page 38
3.3.8 Local Buckling Constraints......Page 39
3.4 NEURAL DYNAMICS OPTIMIZATION MODEL......Page 40
3.5 NEURAL DYNAMICS MODEL FOR OPTIMIZATION OF COLD-FORMED STEEL BEAMS......Page 41
3.6 APPLICATION OF THE MODEL......Page 44
3.6.2 Example 2......Page 45
3.6.3 Example 3......Page 47
3.7 GLOBAL OPTIMUM DESIGN CURVES FOR HAT-SHAPED BEAMS......Page 50
3.7.1 Parametric Studies and Search for Global Optima......Page 51
3.7.2 Design Curves for Hat-Shapes......Page 52
3.8 CONCLUDING REMARKS......Page 53
4.1 INTRODUCTION......Page 60
4.2.2 Life Cycle......Page 62
4.2.5 States of a Project......Page 64
4.2.6 Project Time and Cost......Page 65
4.3.2 Component Models......Page 66
Progress Monitoring......Page 67
Change Order Management......Page 68
4.4.2 Work Breakdown Structure......Page 69
Logic Constraints......Page 71
Buffer Constraints......Page 72
4.5.3 Network Diagrams......Page 73
4.5.4 Linear Planning Chart......Page 74
4.6.1 Introduction......Page 76
4.6.2 Features......Page 77
Task Floats......Page 78
Phases 2: Forward Pass......Page 79
Phase 5: Critical Path Identification......Page 80
4.6.5 Example......Page 81
5.1 INTRODUCTION......Page 84
5.2 COST-DURATION RELATIONSHIP OF A PROJECT......Page 85
5.3.1 Breakdown the Work into Tasks, Crews, and Segments......Page 87
5.3.3 Specify the External Logic of Repetitive and Non-Repetitive Tasks......Page 88
5.4 CONCLUSION......Page 90
6.2 FORMULATION OF THE NEURAL DYNAMICS CONSTRUCTION COST OPTIMIZATION MODEL......Page 91
6.3 TOPOLOGICAL CHARACTERISTICS......Page 93
6.4.1 General Description......Page 95
6.4.3 Scheduling Logic......Page 97
6.4.4 Solution of the Problem......Page 100
6.5 CONCLUSION......Page 102
7.2 CHANGE ORDER MANAGEMENT......Page 104
7.4 OBJECT-ORIENTED METHODOLOGY AND CONSTRUCTION ENGINEERING......Page 105
7.5 AN OBJECT-BASED INFORMATION MODEL FOR CONSTRUCTION SCHEDULING, COST OPTIMIZATION, AND CHANGE ORDER MANAGEMENT......Page 108
7.6 SOFTWARE REUSE TECHNIQUES: COMPONENTS, DESIGN PATTERNS, AND FRAMEWORKS......Page 109
7.7 DEVELOPMENT ENVIRONMENT......Page 112
7.8 AN APPLICATION ARCHITECTURE FOR THE CONSTRUCTION DOMAIN......Page 114
7.9 BRIEF DESCRIPTION OF CLASSES IN FIGURE 7.6......Page 116
8.2.1 Introduction......Page 119
8.2.2 Object Model......Page 120
8.2.3 Model Description......Page 121
8.4 BRIEF DESCRIPTION OF CLASSES IN THE CONSCOM FRAMEWORK (FIGURES 8.1–8.9)......Page 132
8.5.1 Attributes......Page 134
8.5.2 Operations......Page 135
9.2 INTEGRATED CONSTRUCTION SCHEDULING AND COST MANAGEMENT......Page 136
9.3 FEATURES OF CONSCOM......Page 137
9.5 USER INTERFACE CHARACTERISTICS......Page 138
9.6 EXAMPLE—RETAINING WALL PROJECT......Page 143
9.7 CONCLUDING REMARKS......Page 147
10.1 INTRODUCTION......Page 150
10.2 ESTIMATION, LEARNING AND NOISY CURVE FITTING......Page 151
10.3 REGULARIZATION NETWORKS......Page 153
10.4 DETERMINATION OF WEIGHTS OF REGULARIZATION NETWORK......Page 155
10.6 INPUT AND OUTPUT NORMALIZATION......Page 156
10.7.1 Example 1......Page 158
10.7.2 Example 2......Page 159
10.8 CONCLUSION......Page 160
BIBLIOGRAPHY......Page 164
SUBJECT INDEX......Page 176