Metaheuristic Applications in Structures and Infrastructures

Metaheuristic Applications in Structures and Infrastructures

1st Edition - January 31, 2013

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  • Editors: Amir Hossein Gandomi, Xin-She Yang, Siamak Talatahari, Amir Hossein Alavi
  • eBook ISBN: 9780123983794
  • Hardcover ISBN: 9780123983640

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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.

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.


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

Table of Contents

  • 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


    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


    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


    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


    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


    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


    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


    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


    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


    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


    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


    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



    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


    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



    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



    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


    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


    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


    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


    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


    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



    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


    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



Product details

  • No. of pages: 568
  • Language: English
  • Copyright: © Elsevier 2013
  • Published: January 31, 2013
  • Imprint: Elsevier
  • eBook ISBN: 9780123983794
  • Hardcover ISBN: 9780123983640

About the Editors

Amir Hossein Gandomi

Dr. Amir H. Gandomi is anARC DECRA Fellow at the Faculty of Engineering andInformation Technology, University of Technology Sydney, Australia. Prior to joining UTS, Dr. Gandomi was an Assistant Professor at Stevens Institute of Technology, USA and a Distinguished Research Fellow in BEACON center, Michigan State University, USA. Dr. Gandomi has published over two hundred journal papers and seven books which collectively have been cited 19,000+ times. He has been named as one of the most influential scientific mindsand Highly Cited Researcher (top 1% publications and 0.1% researchers) for four consecutive years, 2017 to 2020. He also ranked 18th in GP bibliography among more than 12,000 researchers. He has served as associate editor, editor and guest editor in several prestigious journals such as AE of SWEVO, IEEE TBD, and IEEE IoTJ. Dr. Gandomi is active in delivering keynotes and invited talks. His research interests are global optimization andbigdata analytics using Machine Learning and evolutionary computations in particular.

Affiliations and Expertise

The University of Akron, USA

Xin-She Yang

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

Siamak Talatahari

Dr. Siamak Talatahari received his Ph.D degree in Structural Engineering from University of Tabriz, Iran. After graduation, he joined the University of Tabriz where he is presently Professor of Structural Engineering. He is the author of more than 100 papers published in international journals, 30 papers presented at international conferences and 8 international book chapters. Dr. Talatahari has been recognized as Distinguished Scientist in the Ministry of Science and Technology and as Distinguished Professor at the University of Tabriz. He also teaches at the Yakin Dogu University, Nicosia, Cyprus. In addition, he is a co-author with our author Xin-She Yang of Swarm Intelligence and Bio-Inspired Computation: Structural Optimization Using Krill Herd Algorithm; Metaheuristics in Water, Geotechnical and Transport Engineering, and Metaheuristic Applications in Structures and Infrastructures, all published by as Insights by Elsevier.

Affiliations and Expertise

Department of Civil Engineering, University of Tabriz, Tabriz, Iran. School of Civil and Environment Engineering, University of New South Wales, Sydney, Australia.

Amir Hossein Alavi

Affiliations and Expertise

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

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