Handbook of AI-based metaheuristics / edited by Anand J. Kulkarni, Patrick Siarry.

Contributor(s):

Material type: Text

TextSeries: Advances in metaheuristicsEdition: First editionDescription: xix, 398 pagesISBN:

9780367753030
9780367755355

Subject(s):

DDC classification:

620.004 23 KUL

Contents:

Socio-inspired methods -- Physics and chemistry-based methods -- Bio-inspired methods -- Swarm-based methods.

Summary: "At the heart of the optimization domain are mathematical modelling of the problem and the solution methodologies. In recent times, the problems are becoming larger, with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to resort to Artificial Intelligence (AI) based nature-inspired solution methodologies or algorithms. The Handbook of AI-based Metaheuristics provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural and physics-based methods or algorithms; their testing and validation, along with detailed illustrative solutions and applications, as well as newly devised metaheuristic algorithms. The book will be a valuable reference to researchers from industry and academia, as well as Masters and PhD students around the globe working in the metaheuristics and applications domain"--

Tags from this library: No tags from this library for this title. Log in to add tags.

Holdings
Item type	Current library	Home library	Collection	Call number	Status	Date due	Barcode
Book	Dept. of Futures Studies General Stacks	Dept. of Futures Studies	Non-fiction	620.004 KUL (Browse shelf(Opens below))	Available		DFS4480

Browsing Dept. of Futures Studies shelves, Shelving location: General Stacks, Collection: Non-fiction Close shelf browser (Hides shelf browser)

Previous								Next
Previous	519.6 HOY Ordinal optimization : soft optimization for hard problems /	530.12 MAT Mathematical horizons for quantum physics /	530.15635 LAU Geometry of time-spaces : non-commutative algebraic geometry, applied to quantum theory /	620.004 KUL Handbook of AI-based metaheuristics /	620.1 ZOH An introduction to computational micromechanics /	621.391 KAS Fundamentals of Quantum Computing: Theory and Practice/	624.171 MAT Mathematical models for structural reliability analysis /	Next

Includes works by Mohammed El-Abd and many others.

Includes bibliographical references and index.

Socio-inspired methods -- Physics and chemistry-based methods -- Bio-inspired methods -- Swarm-based methods.

"At the heart of the optimization domain are mathematical modelling of the problem and the solution methodologies. In recent times, the problems are becoming larger, with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to resort to Artificial Intelligence (AI) based nature-inspired solution methodologies or algorithms. The Handbook of AI-based Metaheuristics provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural and physics-based methods or algorithms; their testing and validation, along with detailed illustrative solutions and applications, as well as newly devised metaheuristic algorithms. The book will be a valuable reference to researchers from industry and academia, as well as Masters and PhD students around the globe working in the metaheuristics and applications domain"--

There are no comments on this title.

to post a comment.