Metaheuristics in Water, Geotechnical and Transport Engineering (Paperback)

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.

General

Imprint:	Elsevier - Health Sciences Division
Country of origin:	United States
Release date:	September 2012
First published:	2013
Editors:	Xin-She Yang • Amir Hossein Gandomi • Siamak Talatahari • Amir Hossein Alavi
Dimensions:	229 x 152 x 26mm (L x W x T)
Format:	Paperback
Pages:	504
ISBN-13:	978-0-323-28260-4
Categories:	Books > Professional & Technical > Environmental engineering & technology > Sanitary & municipal engineering > Water supply & treatment > General Promotions
LSN:	0-323-28260-1
Barcode:	9780323282604

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