Metaheuristics in Water, Geotechnical and Transport Engineering
Published on 3. September 2012
Book
Hardback
496 pages
978-0-12-398296-4 (ISBN)
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.
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.
More details
Language
English
Place of publication
United States
Target group
Professional and scholarly
Academic researchers and lecturers in civil engineering and computer sciences as well as industrial practitioners.
Dimensions
Height: 229 mm
Width: 152 mm
Weight
920 gr
ISBN-13
978-0-12-398296-4 (9780123982964)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Xin-She Yang | Siamak Talatahari | Amir Hossein Alavi
Metaheuristics in Water, Geotechnical and Transport Engineering
E-Book
12/2012
Elsevier
€75.95
Available for download
Xin-She Yang | Siamak Talatahari | Amir Hossein Alavi
Metaheuristics in Water, Geotechnical and Transport Engineering
Book
09/2012
Elsevier
€92.50
Shipment within 15-20 days
Persons
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 in Modelling and Simulation at Middlesex University London, Fellow of the Institute of Mathematics and its Application (IMA) and a Book Series Co-Editor of the Springer Tracts in Nature-Inspired Computing. He has published more than 25 books and more than 400 peer-reviewed research publications with over 82000 citations, and he has been on the prestigious list of highly cited researchers (Web of Sciences) for seven consecutive years (2016-2022). 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. Amir Hossein Alavi is an Assistant Professor in the Department of Civil and Environmental Engineering, and holds courtesy appointments in the Department of Bioengineering and Department of Mechanical Engineering and Materials Science, at the University of Pittsburgh, United States. His multidisciplinary scientific studies are organized around three research thrusts: 1) mechanics and electronics of multifunctional materials and structures, 2) embedded self-powered sensing systems, and 3) data-driven characterization, design and discovery of engineering systems.
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. Amir Hossein Alavi is an Assistant Professor in the Department of Civil and Environmental Engineering, and holds courtesy appointments in the Department of Bioengineering and Department of Mechanical Engineering and Materials Science, at the University of Pittsburgh, United States. His multidisciplinary scientific studies are organized around three research thrusts: 1) mechanics and electronics of multifunctional materials and structures, 2) embedded self-powered sensing systems, and 3) data-driven characterization, design and discovery of engineering systems.
Editor
School of Science and Technology, Middlesex University, UK
Department of Civil Engineering, University of Tabriz, Tabriz, Iran.
School of Civil and Environment Engineering, University of New South Wales, Sydney, Australia.
School of Civil and Environment Engineering, University of New South Wales, Sydney, Australia.
Department of Civil and Environmental Engineering, Department of Bioengineering, University of Pittsburgh, Pittsburgh, USA
Content
1. Optimization and Metaheuristic Algorithms in Engineering 2.Application of Soft Computing Methods in Water Resources Engineering (Hazi Mohammad Azamathulla) 3.Genetic Algorithms and Their Applications to Water resources Systems
4.Application of Hybrid HS-Solver Algorithm to the Solution of Groundwater Management Problems
5.Evolutionary Multi-objective Optimization of the Water Distribution Networks
6.Ant Colony Optimization for Parameters Estimating of Flood Frequency Distributions
7.Optimal Reservoir Operation for Irrigation Planning Using Swarm Intelligence Algorithm
8.Artificial Intelligence in Geotechnical Engineering: Applications, Modelling Aspects and Future Directions
9.Hybrid heuristic optimization methods in geotechnical engineering
10.Artificial neural network in geotechncial engineering: modelling and application issues
11.Geotechnical Applications of Bayesian Neural Networks
12.Linear and Tree-Based Genetic Programming for Solving Geotechnical Engineering Problems
13.A New Approach to Modelling the Behaviour of Geomaterials
14.Slope Stability analysis using Metaheuristics
15.Scheduling Transportation Networks and Reliability Analysis of Geostructures using Metaheuristics
16.Metaheuristic Applications in Highway and Rail Infrastructure Planning and Design: Implications to Energy and Environmental Sustainability
17.Multi-Objective Optimization of Delay and Stops in Traffic Signal Networks
18.An improved Hybrid Algorithm for Stochastic Bus-Network Design
19.Hybrid method and its application toward smart Pavement Management
4.Application of Hybrid HS-Solver Algorithm to the Solution of Groundwater Management Problems
5.Evolutionary Multi-objective Optimization of the Water Distribution Networks
6.Ant Colony Optimization for Parameters Estimating of Flood Frequency Distributions
7.Optimal Reservoir Operation for Irrigation Planning Using Swarm Intelligence Algorithm
8.Artificial Intelligence in Geotechnical Engineering: Applications, Modelling Aspects and Future Directions
9.Hybrid heuristic optimization methods in geotechnical engineering
10.Artificial neural network in geotechncial engineering: modelling and application issues
11.Geotechnical Applications of Bayesian Neural Networks
12.Linear and Tree-Based Genetic Programming for Solving Geotechnical Engineering Problems
13.A New Approach to Modelling the Behaviour of Geomaterials
14.Slope Stability analysis using Metaheuristics
15.Scheduling Transportation Networks and Reliability Analysis of Geostructures using Metaheuristics
16.Metaheuristic Applications in Highway and Rail Infrastructure Planning and Design: Implications to Energy and Environmental Sustainability
17.Multi-Objective Optimization of Delay and Stops in Traffic Signal Networks
18.An improved Hybrid Algorithm for Stochastic Bus-Network Design
19.Hybrid method and its application toward smart Pavement Management