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Metaheuristic Applications in Structures and Infrastructures
 
 

Metaheuristic Applications in Structures and Infrastructures, 1st Edition

 
Metaheuristic Applications in Structures and Infrastructures, 1st Edition,Amir Hossein Gandomi,Xin-She Yang,Siamak Talatahari,Amir Hossein  Alavi ,ISBN9780123983640
 
 
 

Gandomi   &   Yang   &   Talatahari   &   Alavi   

Elsevier

9780123983640

9780123983794

568

229 X 152

Provides a comprehensive summary of metaheuristic methods with applications in structural engineering, construction engineering and earthquake engineering.

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Key Features

  • Review of the latest development of metaheuristics in engineering.
  • Detailed algorithm descriptions with focus on practical implementation.
  • Uses practical case studies as examples and applications.

Description

Due to an ever-decreasing supply in raw materials and stringent constraints on conventional energy sources, demand for lightweight, efficient and low-cost structures has become crucially important in modern engineering design. This requires engineers to search for optimal and robust design options to address design problems that are commonly large in scale and highly nonlinear, making finding solutions challenging. In the past two decades, metaheuristic algorithms have shown promising power, efficiency and versatility in solving these difficult optimization problems.

This book examines the latest developments of metaheuristics and their applications in structural engineering, construction engineering and earthquake engineering, offering practical case studies as examples to demonstrate real-world applications. Topics cover a range of areas within engineering, including big bang-big crunch approach, genetic algorithms, genetic programming, harmony search, swarm intelligence and some other metaheuristic methods. Case studies include structural identification, vibration analysis and control, topology optimization, transport infrastructure design, design of reinforced concrete, performance-based design of structures and smart pavement management. With its wide range of everyday problems and solutions, Metaheursitic Applications in Structures and Infrastructures can serve as a supplementary text for design courses and computation in engineering as well as a reference for researchers and engineers in metaheuristics, optimization in civil engineering and computational intelligence.

Readership

Advanced students, researchers and professional engineers in metaheursitics, optimization and computational intelligence and computational methods in civil engineering.

Amir Hossein Gandomi

Affiliations and Expertise

The University of Akron,USA

View additional works by Amir Hossein Gandomi

Xin-She Yang

Xin-She Yang obtained his DPhil in Applied Mathematics from the University of Oxford. He then worked at Cambridge University and National Physical Laboratory (UK) as a Senior Research Scientist. He is currently a Reader at Middlesex University London, Adjunct Professor at Reykjavik University (Iceland) and Guest Professor at Xi’an Polytechnic University (China). He is an elected Bye-Fellow at Downing College, Cambridge University. He is also the IEEE CIS Chair for the Task Force on Business Intelligence and Knowledge Management, and the Editor-in-Chief of International Journal of Mathematical Modelling and Numerical Optimisation (IJMMNO).

Affiliations and Expertise

School of Science and Technology, Middlesex University, UK

View additional works by Xin-She Yang

Siamak Talatahari

Affiliations and Expertise

University of Tabriz, Iran

View additional works by Siamak Talatahari

Amir Hossein  Alavi

Affiliations and Expertise

Iran University of Science and Technology, Iran The Institute of Higher Education of Eqbal Lahoori, Iran

View additional works by Amir Hossein Alavi

Metaheuristic Applications in Structures and Infrastructures, 1st Edition

List of Contributors

1. Metaheuristic Algorithms in Modeling and Optimization

1.1 Introduction

1.2 Metaheuristic Algorithms

1.3 Metaheuristic Algorithms in Modeling

1.4 Metaheuristic Algorithms in Optimization

1.5 Challenges in Metaheuristics

References

2. A Review on Traditional and Modern Structural Optimization: Problems and Techniques

2.1 Optimization Problems

2.2 Optimization Techniques

2.3 Optimization History

2.4 Structural Optimization

2.5 Metaheuristic Optimization Techniques

References

3. Particle Swarm Optimization in Civil Infrastructure Systems: State-of-the-Art Review

3.1 Introduction

3.2 Particle Swarm Optimization

3.3 Structural Engineering

3.4 Transportation and Traffic Engineering

3.5 Hydraulics and Hydrology

3.6 Construction Engineering

3.7 Geotechnical Engineering

3.8 Pavement Engineering

3.9 PSO Applications in Other Civil Engineering Fields

3.10 Concluding Remarks

References

Part One: Structural Design

4. Evolution Strategies-Based Metaheuristics in Structural Design Optimization

4.1 Introduction

4.2 Literature Survey

4.3 The Structural Optimization Problem

4.4 Problem Formulations

4.5 Metaheuristics

4.6 39-Bar Truss—Test Example

4.7 Conclusions

References

5. Multidisciplinary Design and Optimization Methods

5.1 Introduction

5.2 Coupled Multidisciplinary System

5.3 Classifications of MDO Formulations

5.4 Single-Level Optimization

5.5 Multilevel Optimization

5.6 Optimization Algorithms

5.7 High-Fidelity MDO Using Metaheuristic Algorithms

5.8 Test Problem

5.9 Conclusions

References

6. Cost Optimization of Column Layout Design of Reinforced Concrete Buildings

6.1 Introduction

6.2 Statement of the Problem

6.3 Formulation in a New Space

6.4 The Optimization Problem

6.5 ACO Algorithm for Column Layout Optimization

6.6 Conclusions

References

7. Layout Design of Beam–Slab Floors by a Genetic Algorithm

7.1 Introduction

7.2 A Representation of Beam–Slab Layouts

7.3 A Representative Optimization Problem

7.4 A GA for Beam–Slab Layout Design

7.5 Examples

7.6 Future Challenges

References

8. Optimum Design of Skeletal Structures via Big Bang–Big Crunch Algorithm

8.1 Introduction

8.2 Statement of the Optimization Design Problem

8.3 Review of the Utilized Methods

8.4 The Proposed Method

8.5 Design Examples

8.6 Concluding Remarks

References

9. Truss Weight Minimization Using Hybrid Harmony Search and Big Bang–Big Crunch Algorithms

9.1 Introduction

9.2 Statement of the Weight Minimization Problem for a Truss Structure

9.3 Harmony Search

9.4 Big Bang–Big Crunch

9.5 Simulated Annealing

9.6 Description of Test Problems

9.7 Results of Sensitivity Analysis

9.8 Results of the Large-Scale Optimization Problem

9.9 Summary and Conclusions

References

10. Graph Theory in Evolutionary Truss Design Optimization

10.1 Introduction

10.2 Truss Design

10.3 Graph Theory

10.4 Evolutionary Algorithm

10.5 Application

10.6 Conclusions

References

11. Element Exchange Method for Stochastic Topology Optimization

11.1 Introduction

11.2 Overview of Topology Optimization Methods

11.3 Element Exchange Method

11.4 EEM Application

11.5 Influence of EEM Operations and Parameters on Optimization Results

11.6 Conclusion

References

Part Two: Structural Control and Identification

12. Evolutionary Path-Dependent Damper Optimization for Variable Building Stiffness Distributions

12.1 Introduction

12.2 Concept of Adaptive Sensitivity

12.3 Structural Model with Passive Dampers

12.4 Critical Excitation for Variable Design

12.5 Optimal Design Problem

12.6 Optimality Conditions

12.7 Solution Procedure of Optimal Design Problem

12.8 Numerical Examples

12.9 Conclusions

Acknowledgments

References

13. Application of Genetic Algorithms in Ground Motion Selection for Seismic Analysis

13.1 An Introduction to Structural Nonlinear Response-History Analysis

13.2 A Snapshot of the Genetic Algorithm as One of the Popular Metaheuristics

13.3 Code-Conforming Ground Motion Selection

13.4 Ground Motion Record Selection in PBEE

13.5 Conclusions

References

14. Optimization of Tuned Mass Damper with Harmony Search

14.1 Introduction

14.2 A Passive Structural Control Device: Tuned Mass Damper

14.3 Optimization of TMDs with HS

14.4 Numerical Examples

14.5 Conclusion

Acknowledgments

References

15. Identification of Passive Devices for Vibration Control by Evolutionary Algorithms

15.1 Introduction

15.2 Parametric Identification of Fluid Viscous Dampers

15.3 Differential Evolution Algorithms

15.4 Particle Swarm Optimization Algorithms

15.5 Viscous Damper Identification Using Experimental Data

15.6 Conclusions

Acknowledgment

References

16. Structural Optimization for Frequency Constraints

16.1 Introduction

16.2 Formulation of a Structural Optimization Problem with Frequency Constraints

16.3 Formulation of Optimization Problem of an Arch Dam with Frequency Constraints

16.4 Metaheuristics

16.5 Neural Networks

16.6 Numerical Examples

16.7 Conclusions

References

17. Optimum Performance-Based Seismic Design of Frames Using Metaheuristic Optimization Algorithms

17.1 Introduction

17.2 A Brief Review of Metaheuristic Algorithms

17.3 Statement of Seismic Design of Frames

17.4 Pushover Analysis for Performance-Based Design

17.5 Utilized Metaheuristic Algorithms

17.6 Design Examples

17.7 Concluding Remarks

References

18. Expression Programming Techniques for Formulation of Structural Engineering Systems

18.1 Introduction

18.2 Genetic Programming

18.3 Application to Structural Engineering Problems

18.4 Model Validity

18.5 Conclusions

References

19. An Evolutionary Divide-and-Conquer Strategy for Structural Identification

19.1 Introduction

19.2 Recent Studies on Sub-SI

19.3 Multifeature GA

19.4 Divide-and-Conquer-Based Structural Identification

19.5 Numerical Study

19.6 Applications to Local Damage Detection

19.7 Experimental Verification

19.8 Conclusions

References

Part Three: Construction Management and Maintenance

20. Swarm Intelligence for Large-Scale Optimization in Construction Management

20.1 Introduction

20.2 SI-Based Optimization Algorithms

20.3 Experiments and Discussion

20.4 Conclusions

References

21. Network-Level Infrastructure Management Based on Metaheuristics

21.1 Introduction

21.2 Problem Description

21.3 Ant Colony Optimization

21.4 Genetic Algorithms

21.5 Test Case

21.6 Test Results

21.7 Summary and Outlook

Acknowledgments

References

22. Large-Scale Maintenance Optimization Problems for Civil Infrastructure Systems

22.1 Introduction

22.2 Large-Scale Maintenance Optimization Problem

22.3 Metaheuristic Solution Approaches

22.4 Case Studies

22.5 Summary

References

23. Metaheuristic Applications in Bridge Infrastructure Maintenance Scheduling Considering Stochastic Aspects of Deterioration

23.1 Introduction

23.2 Deterioration Modeling

23.3 Solution Algorithm

23.4 Experimental Procedure

23.5 Evaluation of FRP Composite Materials in Bridge Applications

23.6 Application of AFRP Bars in a Full-Scale Bridge Deck Slab

23.7 Experimental Results

23.8 Discussion

Acknowledgments

References

 
 
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