Fuzzy Hybrid Computing in Construction Engineering and Management: Theory and Applications

Front Cover
......Page 1
Fuzzy Hybrid Computing in Construction Engineering and Management: Theory and applications......Page 4
Copyright Page
......Page 5
Acknowledgements......Page 8
Contents......Page 10
List of Figures......Page 12
List of Tables......Page 18
About the Editor......Page 22
About the Authors......Page 24
Foreword......Page 28
Introduction......Page 30
Purpose and Structure of the Book......Page 31
Fuzzy Arithmetic Operations: Theory and Applications in Construction Engineering and Management......Page 32
Fuzzy Consensus and Fuzzy Aggregation Processes for Multi-criteria Group Decision-making Problems in Construction Engineering and Management......Page 33
Flexible Management of Essential Construction Tasks Using Fuzzy OLAP Cubes......Page 34
Crane Guidance Gesture Recognition Using Fuzzy Logic and Kalman Filtering......Page 35
Future Directions......Page 36
Part 1: Introduction to Fuzzy Logic and Overview of Fuzzy Hybrid Techniques in Construction Engineering and Management......Page 38
Introduction to Fuzzy Logic in Construction Engineering and Management......Page 40
List of Notations......Page 41
Fuzzy Logic for Handling Uncertainty in Construction Engineering and Management......Page 42
Fuzzy Sets and Membership Functions......Page 44
Representing Membership Functions......Page 46
Characteristics of Membership Functions......Page 48
Fuzzy Variables and Fuzzy Partitions......Page 50
Basic Set Operations on Fuzzy Sets......Page 51
Fuzzy Relations and Fuzzy Composition......Page 52
Defuzzification......Page 53
Non-probabilistic Entropy: Measuring the Degree of Fuzziness......Page 54
Fuzzy Numbers......Page 55
Direct Assignment of Membership Functions: Horizontal and Vertical Methods......Page 57
Pairwise Comparison Using the Analytic Hierarchy Process......Page 58
Statistical Methods......Page 59
Methods Based on Clustering......Page 60
Fuzzy Rule-based Systems......Page 61
Fuzzy Hybrid Modelling in Construction......Page 66
References......Page 68
Overview of Fuzzy Hybrid Techniques in Construction Engineering and Management......Page 74
Introduction......Page 75
Systematic Literature Review Methodology......Page 76
Fuzzy Hybrid Optimization......Page 78
Fuzzy Hybrid Evolutionary Models......Page 80
Fuzzy Hybrid Particle Swarm Optimization Models......Page 87
Hybridisation of Fuzzy Logic with the Artificial Neural Network Technique......Page 89
Fuzzy Clustering Techniques......Page 103
Fuzzy AHP......Page 107
Fuzzy TOPSIS......Page 117
Fuzzy VIKOR......Page 119
Fuzzy Simulation......Page 120
Fuzzy Monte Carlo Simulation......Page 121
Fuzzy Discrete Event Simulation......Page 125
Fuzzy System Dynamics......Page 127
Fuzzy Agent-based Modelling......Page 128
Fuzzy Hybrid Optimization......Page 129
Fuzzy Multi-criteria Decision-making......Page 130
Future Research Directions......Page 131
References......Page 133
Part 2: Theoretical Approaches of Fuzzy Hybrid Computing in Construction Engineering and Management......Page 146
Fuzzy Arithmetic Operations: Theory and Applications in Construction Engineering and Management......Page 148
Fuzzy Arithmetic Operations: Exact Mathematical Methods......Page 149
Exact Mathematical Method for Implementation of Standard Fuzzy Arithmetic......Page 150
Exact Mathematical Method for Implementation of Extended Fuzzy Arithmetic......Page 153
Fuzzy Arithmetic Operations: Computational Methods......Page 156
Computational Method for the Implementation of Standard Fuzzy Arithmetic......Page 158
Computational Method for the Implementation of Extended Fuzzy Arithmetic......Page 160
Extended Fuzzy Addition Using the Algebraic Product t-norm......Page 161
Extended Fuzzy Multiplication Using the Algebraic Product t-norm......Page 163
Extended Fuzzy Arithmetic Using the Bounded Difference t-norm......Page 168
Extended Fuzzy Multiplication Using the Bounded Difference t-norm......Page 169
Extended Fuzzy Multiplication Using the Drastic Product t-norm.......Page 174
Fuzzy Arithmetic Operations in Construction Applications......Page 178
Conclusions and Future Work......Page 182
References......Page 183
Fuzzy Simulation Techniques in Construction Engineering and Management......Page 186
Introduction......Page 187
Discrete Event Simulation......Page 188
System Dynamics......Page 189
Agent-based Modelling......Page 191
Limitations of Simulation Techniques......Page 192
Fuzzy Discrete Event Simulation......Page 194
Fuzzy System Dynamics......Page 196
Fuzzy Agent-based Modelling......Page 199
Step 1. Determining the Architecture of the Agent-based Model.......Page 200
Step 2. Developing the Basic Structure of Agents: Agents, Agent Attributes and Agent Behaviours.......Page 201
Step 3. Defining Protocols Governing Interactions among Agents and Determining Agent Decision-making Rules.......Page 202
Step 4. Incorporating Fuzzy Logic into the Agent-based Model.......Page 203
The Appropriate Choice of Fuzzy Simulation Techniques for Construction Modelling......Page 204
Applications of Fuzzy System Dynamics: An FSD Model of Quality Management Practice in Construction......Page 205
Fuzzy Agent-based Modelling Applications: A Fuzzy ABM Model of Construction Crew Motivation and Performance......Page 207
Conclusions and Future Work......Page 208
References......Page 210
Fuzzy Set Theory and Extensions for Multi-criteria Decision-making in Construction Management......Page 216
List of Notations......Page 217
Introduction......Page 222
MCDM Process and Methods in Construction Management......Page 223
Weighted Sum Method......Page 225
Analytic Hierarchy Process......Page 226
Technique for Order of Preference by Similarity to Ideal Solution......Page 227
Elimination and Choice Expressing Reality......Page 228
Fuzzy Set Theory and Typical Extensions......Page 229
Intuitionistic Fuzzy Sets......Page 230
Hesitant Fuzzy Sets......Page 231
Type-2 Fuzzy Sets......Page 232
Fuzzy Sets-based Weighted Sum Method......Page 234
Fuzzy Sets-based Analytic Hierarchy Process......Page 235
Fuzzy Sets-based Technique for Order of Preference by Similarity to Ideal Solution......Page 237
Fuzzy Sets-based Elimination and Choice Expressing Reality......Page 239
F-MCDM Method Applications in Construction Management......Page 240
Intuitionistic Fuzzy Sets-based Analytic Hierarchy Process......Page 242
Intuitionistic Fuzzy Sets-based Technique for Order of Preference by Similarity to Ideal Solution......Page 243
Intuitionistic Fuzzy Sets-based Elimination and Choice Expressing Reality......Page 244
Intuitionistic Fuzzy Sets-based Preference Ranking Organisation Method Enrichment Evaluation......Page 246
Hesitant Fuzzy Sets-based Analytic Hierarchy Process......Page 247
Hesitant Fuzzy Sets-based Technique for Order of Preference by Similarity to Ideal Solution......Page 249
Hesitant Fuzzy Sets-based Elimination and Choice Expressing Reality......Page 250
Type-2 Fuzzy Sets-based Weighted Sum Method......Page 251
Type-2 Fuzzy Sets-based Analytic Hierarchy Process......Page 252
Type-2 Fuzzy Sets-based Technique for Order of Preference by Similarity to Ideal Solution......Page 253
Type-2 Fuzzy Sets-based Elimination and Choice Expressing Reality......Page 255
T2FS-MCDM Method Applications in Construction Management......Page 256
Conclusions......Page 257
References......Page 259
Fuzzy Consensus and Fuzzy Aggregation Processes for Multi-criteria Group Decision-making Problems in Construction Engineering and Management......Page 266
List of Notations......Page 267
Introduction......Page 268
Fuzzy Consensus-reaching Process......Page 270
Importance Degree of Experts......Page 271
Preference Representation Formats......Page 272
Fuzzy Consensus-reaching Process for Multi-criteria Group Decision-making Problems......Page 273
Fuzzy Aggregation Processes for Constructing Collective Opinions......Page 279
Classification of Fuzzy Aggregation Operators and Their Properties......Page 280
Fuzzy Weighted Average......Page 282
Linguistic Ordered Weighted Averaging......Page 283
Fuzzy Number Induced Ordered Weighted Averaging......Page 285
Fuzzy Prioritised Weighted Aggregation Operators......Page 288
The Fuzzy TOPSIS-based Approach for Prioritised Aggregation......Page 294
Fuzzy Consensus Reaching and Aggregation in Construction Industry Applications......Page 300
Building Design Applications......Page 301
Risk Analysis and Hazard Assessment Applications......Page 302
Construction Procurement and Project Delivery Applications......Page 303
Construction Bidding Applications......Page 305
Construction Productivity Applications......Page 306
Conclusions and Recommendations for Future Work......Page 307
References......Page 308
Fuzzy AHP with Applications in Evaluating Construction Project Complexity......Page 314
List of Notations......Page 315
Introduction......Page 316
Fuzzy Extensions of the Analytical Hierarchy Process......Page 317
Fuzzy Pairwise Comparisons......Page 318
Consistency of Fuzzy Pairwise Comparisons......Page 321
Fuzzy Weights and Defuzzification......Page 322
The Hierarchical Structure of Project Complexity......Page 325
Fuzzy Pairwise Comparison Matrices......Page 326
Local and Global Weights of the Criteria and Sub-criteria......Page 327
Project Complexity and Performance......Page 330
Conclusions......Page 332
References......Page 334
Part 3: Applications of Fuzzy Hybrid Computing in Construction Engineering and Management......Page 338
The Fuzzy Analytic Hierarchy Process in the Investment Appraisal of Drilling Methods......Page 340
Introduction......Page 341
Risk Analysis in Projects......Page 342
Fuzzy Logic......Page 343
Fuzzy AHP in Risk Analysis......Page 345
Application of Fuzzy AHP Techniques in Oil Drilling......Page 347
Case Study......Page 348
Subsea Solution, Tied Back to Harald through a 7 km Long Pipe......Page 349
Economic Screening......Page 350
Dry-hole Risk for the Subsea Option......Page 351
Production Risk for the Subsea Option......Page 352
Fuzzy AHP Technique......Page 355
Fuzzy AHP Investment Appraisal for Oil Drilling Methods......Page 360
Fuzzy AHP Computation in the Subsea Drilling Option......Page 361
Discussion......Page 368
Conclusion and Recommendations......Page 369
References......Page 370
Modelling Risk Allocation Decisions in Public–Private Partnership Contracts using the Fuzzy Set Approach......Page 374
Introduction......Page 375
Previous Studies on Risk Allocation in PPPs......Page 376
Decision Criteria for Defining RM Capability......Page 378
Fuzzy Synthetic Evaluation and Risk Allocation......Page 379
Case Study......Page 380
Round Three of Delphi Survey for Risk Allocation......Page 381
Step 1: Establish Decision Criteria and Their Weightings to Assess RM Capability......Page 382
Representation of Fuzzy Set and Membership Functions......Page 383
Membership Functions of Decision Criteria and Relational Matrix......Page 384
Step 5: Determine the Fuzzy Evaluation Vector of RM Capability Using the Weighted Mean Model......Page 385
Step 7: Risk Allocation Decision......Page 387
Practitioners’ Feedback on the Methodology......Page 388
References......Page 389
Flexible Management of Essential Construction Tasks Using Fuzzy OLAP Cubes......Page 394
Introduction......Page 395
A General Idea About the Multi-dimensional Structure......Page 396
Operations......Page 397
The Fuzzy Multi-dimensional Model......Page 399
Structure......Page 400
Cost Management......Page 401
Safety Analysis......Page 402
Planning Analysis......Page 403
The Proposed Fuzzy Multi-dimensional Structure......Page 404
Time......Page 406
Project......Page 407
Type of Construction......Page 408
Task (WBS)......Page 409
Company......Page 411
Location......Page 412
Worker......Page 414
Injury......Page 415
Example of Queries Resolution......Page 416
Conclusions......Page 419
References......Page 421
Using an Adaptive Neuro-fuzzy Inference System for Tender Price Index Forecasting: A Univariate Approach......Page 426
Introduction......Page 427
The Need for the Application of Univariate Modelling Techniques in Tender Price Index Forecasting Research......Page 428
Box–Jenkins Model......Page 430
Adaptive Neuro-fuzzy Inference System......Page 431
Data......Page 432
Input Selection and Prediction Modelling......Page 433
Forecast Evaluation......Page 434
Box–Jenkins......Page 435
ANFIS Model......Page 436
SVM Model......Page 437
Forecast Accuracy of the Developed Models......Page 438
Discussion......Page 439
Practical Implications......Page 440
Limitations, Directions for Future Studies and Potential Applications of the Proposed Techniques......Page 441
Conclusion......Page 442
References......Page 443
Appendix: R-Code for Adaptive Neuro-fuzzy Inference System......Page 447
Modelling Construction Management Problems with Fuzzy Cognitive Maps......Page 450
Construction Management Benefits......Page 451
Enhancing Construction Management Tools and Practices with FCM......Page 454
Fuzzy Cognitive Map Modelling......Page 456
Construction Engineering and Project Management......Page 460
FCM Example 1: Simple Cause-and-effect Analysis......Page 461
FCM Example 2: Compound Cause-and-effect Analysis......Page 470
FCM Example 3: Complex Cause-and-effect Example......Page 471
Conclusions......Page 473
References......Page 484
List of Notations......Page 488
Introduction......Page 489
Dynamic Modelling of Arm Gestures......Page 490
Nonlinear System Dynamics......Page 492
Nonlinear Kalman Filtering-based Gesture Tracking and Sensor Fusion......Page 493
Extended Kalman Filter......Page 494
Unscented Kalman Filter......Page 495
Sugeno-type Fuzzy Inference System......Page 497
Motion Capture with Kinect Camera and Myo Armband Sensors......Page 500
Experimental Results......Page 503
Conclusion......Page 508
References......Page 509
Index......Page 512