Metaheuristics in Water, Geotechnical and Transport Engineering

Metaheuristics in Water, Geotechnical and Transport Engineering

By (author)  , By (author)  , By (author)  , By (author) 

List price: US$99.95

Currently unavailable

We can notify you when this item is back in stock

Add to wishlist

AbeBooks may have this title (opens in new window).

Try AbeBooks

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.
show more

Product details

  • Hardback | 496 pages
  • 156 x 232 x 38mm | 920.79g
  • United States
  • English
  • 0123982960
  • 9780123982964

Table of contents

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
show more

About Amir Hossein Gandomi

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).
show more