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.
- 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.
List of Contributors
1. Metaheuristic Algorithms in Modeling and Optimization
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
3.2 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
4.2 Literature Survey
4.3 The Structural Optimization Problem
4.4 Problem Formulations
4.6 39-Bar Truss—Test Example
5. Multidisciplinary Design and Optimization Methods
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
6. Cost Optimization of Column Layout Design of Reinforced Concrete Buildings</p
- No. of pages:
- © Elsevier 2013
- 1st February 2013
- eBook ISBN:
- Hardcover ISBN:
The University of Akron,USA
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).
School of Science and Technology, Middlesex University, UK
University of Tabriz, Iran
Iran University of Science and Technology, Iran The Institute of Higher Education of Eqbal Lahoori, Iran