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£113 today · previous high £113 · all-time low £108

Springer EVOLVE: Probability, Set Numerics & Evolutionary Computation

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Description

This Springer academic volume explores the intersection of probability theory, set-oriented numerics, and evolutionary computation through rigorous theoretical analysis. The book comprises 12 thoroughly refereed papers presented in consistent, well-structured chapter form, offering researchers and practitioners strong theoretical foundations for understanding evolutionary algorithm behaviour. Contributors present original research findings, practical optimization problems, and fresh perspectives on transdisciplinary topics that bridge computational mathematics with evolutionary methods. Ideal for computer scientists, mathematicians, and engineers seeking advanced insights into algorithm design, analysis, and application across complex problem spaces.

Key Features

Contains 12 peer-reviewed papers covering theoretical and practical aspects of evolutionary algorithms and computational intelligence.

Provides rigorous mathematical foundations connecting probability theory with evolutionary computation and set-oriented numerical methods.

Part of the Studies in Computational Intelligence series (volume 447) from Springer, a leading academic publisher.

Presents consistent, well-organised chapter structure making complex transdisciplinary research accessible and coherent.

Offers both theoretical findings and real-world optimization problems applicable to algorithm development and analysis.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
15 October 2014
Listed Since
16 October 2014

Barcode

No barcode data available

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