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Metaheuristics in Water, Geotechnical and Transport Engineering
 
 

Metaheuristics in Water, Geotechnical and Transport Engineering, 1st Edition

 
Metaheuristics in Water, Geotechnical and Transport Engineering, 1st Edition,Xin-She Yang,Amir Hossein Gandomi,Siamak Talatahari,Amir Hossein  Alavi ,ISBN9780123983176
 
 
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Yang   &   Gandomi   &   Talatahari   &   Alavi   

Elsevier

9780123983176

496

Provides a comprehensive summary of metaheuristics in water, geotechnical and transport engineering over the past decade, including practical examples

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Key Features

  • Provides detailed descriptions of all major metaheuristic algorithms with a focus on practical implementation
  • Develops new hybrid and advanced methods suitable for civil engineering problems at all levels
  • Appropriate for researchers and advanced students to help to develop their work

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 often 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 water, geotechnical and transport engineering offering practical case studies as examples to demonstrate real world applications. Topics cover a range of areas within engineering, including reviews of optimization algorithms, artificial intelligence, cuckoo search, genetic programming, neural networks, multivariate adaptive regression, swarm intelligence, genetic algorithms, ant colony optimization, evolutionary multiobjective optimization with diverse applications in engineering such as behavior of materials, geotechnical design, flood control, water distribution and signal networks. This book can serve as a supplementary text for design courses and computation in engineering as well as a reference for researchers and engineers in metaheursitics, optimization in civil engineering and computational intelligence.

Readership

Academic researchers and lecturers in civil engineering and computer sciences as well as industrial practitioners.

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

Amir Hossein Gandomi

Affiliations and Expertise

The University of Akron,USA

View additional works by Amir Hossein Gandomi

Siamak Talatahari

Affiliations and Expertise

University of Tabriz, Iran

Amir Hossein  Alavi

Affiliations and Expertise

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

Metaheuristics in Water, Geotechnical and Transport Engineering, 1st Edition

List of contributors

1. Optimization and Metaheuristic Algorithms in Engineering

1.1 Introduction

1.2 Three Issues in Optimization

1.3 Metaheuristics

1.4 Artificial Neural Networks

1.5 Genetic Programming

References

PART ONE: Water Resources

2. A Review on Application of Soft Computing Methods in Water Resources Engineering

2.1 Introduction

2.2 Soft Computing Techniques

2.3 Implementation of Soft Computing Techniques

2.4 Conclusion

Acknowledgments

References

3. Genetic Algorithms and Their Applications to Water Resources Systems

3.1 Introduction

3.2 Genetic Algorithms

3.3 Review of GA Applications to Water Resource Problems

3.4 The GA Process for a Reservoir Operation Problem

3.5 Conclusions

References

4. Application of the Hybrid HS–Solver Algorithm to the Solution of Groundwater Management Problems

4.1 Introduction

4.2 Development of the Hybrid HS–Solver Algorithm

4.3 Formulation of the Management Problem

4.4 Numerical Applications

4.5 Conclusions

Acknowledgments

References

5. Water Distribution Networks Designing by the Multiobjective Genetic Algorithm and Game Theory

5.1 Introduction

5.2 The Objectives of WDN Optimization

5.3 The Hydraulic of WDN

5.4 Basic Concepts: GA, Multiobjective Optimization, and Game Theory

5.5 Methodology

5.6 Case Study

5.7 The Biobjective Optimization Problem

Acknowledgments

References

6. Ant Colony Optimization for Estimating Parameters of Flood Frequency Distributions

6.1 Introduction

6.2 A Review of Previous Work

6.3 Standard ACO

6.4 Improved ACO

6.5 Other Well-Known Methods of Parameter Estimation

6.6 Frequency Distributions

6.7 Simulation and Application

6.8 Results and Discussion

6.9 Conclusions

References

7. Optimal Reservoir Operation for Irrigation Planning Using the Swarm Intelligence Algorithm

7.1 Introduction

7.2 Literature Review

7.3 Method Description

7.4 Case Study

7.5 Mathematical Modeling

7.6 Results and Discussion

7.7 Conclusions

References

PART TWO: Geotechnical Engineering

8. Artificial Intelligence in Geotechnical Engineering: Applications, Modeling Aspects, and Future Directions

8.1 Introduction

8.2 AI Applications in Geotechnical Engineering

8.3 Overview of AI

8.4 Discussion and Conclusions

References

9. Hybrid Heuristic Optimization Methods in Geotechnical Engineering

9.1 Introduction

9.2 Some Basic Heuristic Optimization Algorithms

9.3 Demonstration of the Coupling Methods

9.4 Application of Coupling Methods in the Slope Stability Problem

9.5 Discussion and Conclusions

Acknowledgment

References

10. Artificial Neural Networks in Geotechnical Engineering: Modeling and Application Issues

10.1 Introduction

10.2 Basic Formulation

10.3 Modeling and Application Issues in General

10.4 Future Challenges

10.5 Conclusions

References

11. Geotechnical Applications of Bayesian Neural Networks

11.1 Introduction

11.2 Neural Networks

11.3 Bayesian Neural Network

11.4 Evolutionary Bayesian Back-Propagation Neural Network

11.5 Examples

11.6 Conclusions

References

12. Linear and Tree-Based Genetic Programming for Solving Geotechnical Engineering Problems

12.1 Introduction

12.2 Previous Studies on Applications of TGP and LGP in Geotechnical Engineering

12.3 Tree-Based Genetic Programming

12.4 Application to Geotechnical Engineering Problems

12.5 Discussion and Future Directions

12.6 Conclusions

References

13. An EPR Approach to the Modeling of Civil and Geotechnical Engineering Systems

13.1 Introduction

13.2 Evolutionary Polynomial Regression

13.3 Data Preparation

13.4 Stability Analysis of Slopes Using EPR

13.5 EPR Modeling of the Behavior of Rubber Concrete

13.6 Application of EPR in Constitutive Modeling of Materials

13.7 Summary and Conclusion

References

14. Slope Stability Analysis Using Multivariate Adaptive Regression Spline

14.1 Introduction

14.2 Method

14.3 Application of MARS to Slope Stability Analysis

14.4 Results and Discussion

14.5 Conclusion

References

PART THREE: Transport Engineering

15. Scheduling Transportation Networks and Reliability Analysis of Geostructures Using Metaheuristics

15.1 Introduction

15.2 Problem Statement and Research Impact

15.3 Metaheuristic Algorithms

15.4 Scheduling Transportation Networks

15.5 Reliability Analysis of Geostructures

15.6 Conclusions

References

16. Metaheuristic Applications in Highway and Rail Infrastructure Planning and Design: Implications to Energy and Environmental Sustainability

16.1 Introduction

16.2 Highway Infrastructure Planning and Design

16.3 Rail Infrastructure Planning and Design

16.4 Discussion of Metaheuristics Commonly Applied in Highway and Rail Infrastructure Planning and Design

16.5 GA Application in Highway and Rail Infrastructure Planning and Design

16.6 GA Application to Rail Infrastructure Planning and Design

16.7 The Ant Highway Alignment Optimization Algorithm

16.8 The Ant Algorithm Applied to the SLO Problem

16.9 Implications to Environment and Energy Sustainability

16.10 Conclusions and Future Works

Acknowledgments

References

17. Multiobjective Optimization of Delay and Stops in Traffic Signal Networks

17.1 Introduction

17.2 Background

17.3 Modifications to NSGA-II Design

17.4 Methodology

17.5 Results

17.6 Conclusion

References

18. An Improved Hybrid Algorithm for Stochastic Bus-Network Design

18.1 Introduction

18.2 The Main Entities of the BNDP: The Operator and the User

18.3 Hybrid Method for Stochastic Bus-Network Design

18.4 Practical Experience

18.5 Conclusions and Future Research Work

Acknowledgments

References

19. The Hybrid Method and its Application to Smart Pavement Management

19.1 Introduction

19.2 Methodology

19.3 Conclusions

References

 
 
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