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Springer Biologically-Inspired Optimisation Methods - Springer Studies 210

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Description

This comprehensive volume from Springer explores cutting-edge theories, applications and techniques in biologically-inspired optimisation methods, drawing on research presented at major workshops and international conferences focused on e-Science, grid computing and evolutionary computation. The book demonstrates how natural systems, built on simple rules and principles, solve complex problems across science, engineering and economics through adaptive strategies that work efficiently in dynamic environments. Perfect for researchers, academics and practitioners seeking to understand how biological inspiration drives innovation in computational optimisation and artificial intelligence.

Key Features

Springer Studies in Computational Intelligence Volume 210 presents peer-reviewed research from leading international conferences and workshops on evolutionary computation.

Covers biologically-inspired optimisation methods including algorithms derived from natural systems and adaptive mechanisms found in nature.

Explores real-world applications across science, engineering and economics, demonstrating practical problem-solving approaches inspired by biological systems.

Features theoretical frameworks and technical studies from experts in e-Science and grid computing communities.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
28 October 2010
Listed Since
28 December 2010

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