Review of Soils Design, Construction, and Prototype Observations, Grenada Dam, Mississippi
Author: Waterways Experiment Station (U.S.)
Publisher:
Published: 1962
Total Pages: 134
ISBN-13:
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Author: Waterways Experiment Station (U.S.)
Publisher:
Published: 1962
Total Pages: 134
ISBN-13:
DOWNLOAD EBOOKAuthor: Edward Belk Perry
Publisher:
Published: 1979
Total Pages: 172
ISBN-13:
DOWNLOAD EBOOKAuthor: Waterways Experiment Station (U.S.)
Publisher:
Published: 1964
Total Pages: 98
ISBN-13:
DOWNLOAD EBOOKAuthor: U.S. Army Engineer Waterways Experiment Station
Publisher:
Published: 1976
Total Pages: 430
ISBN-13:
DOWNLOAD EBOOKAuthor: United States. Army. Corps of Engineers
Publisher:
Published:
Total Pages: 130
ISBN-13:
DOWNLOAD EBOOKAuthor: Waterways Experiment Station (U.S.)
Publisher:
Published: 1973
Total Pages: 322
ISBN-13:
DOWNLOAD EBOOKAuthor: Rose Mary Peck
Publisher:
Published: 1985
Total Pages: 608
ISBN-13:
DOWNLOAD EBOOKAuthor: United States Committee on Large Dams
Publisher:
Published: 1958
Total Pages: 164
ISBN-13:
DOWNLOAD EBOOKAuthor:
Publisher: Department of Homeland Security
Published: 2004
Total Pages: 40
ISBN-13:
DOWNLOAD EBOOKAuthor: Marco Dorigo
Publisher: MIT Press
Published: 2004-06-04
Total Pages: 324
ISBN-13: 9780262042192
DOWNLOAD EBOOKAn overview of the rapidly growing field of ant colony optimization that describes theoretical findings, the major algorithms, and current applications. The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses. The book first describes the translation of observed ant behavior into working optimization algorithms. The ant colony metaheuristic is then introduced and viewed in the general context of combinatorial optimization. This is followed by a detailed description and guide to all major ACO algorithms and a report on current theoretical findings. The book surveys ACO applications now in use, including routing, assignment, scheduling, subset, machine learning, and bioinformatics problems. AntNet, an ACO algorithm designed for the network routing problem, is described in detail. The authors conclude by summarizing the progress in the field and outlining future research directions. Each chapter ends with bibliographic material, bullet points setting out important ideas covered in the chapter, and exercises. Ant Colony Optimization will be of interest to academic and industry researchers, graduate students, and practitioners who wish to learn how to implement ACO algorithms.