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Springer Advances in Multi-Objective Nature Inspired Computing - Springer

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Description

This comprehensive reference from Springer explores recent advances in multi-objective, nature-inspired computing and metaheuristics for solving complex combinatorial optimisation problems. Designed for both non-experts seeking an overview and researchers looking to deepen their knowledge, this volume collects contributions that demonstrate the state-of-the-art developments in nature-inspired approaches. The book aims to motivate researchers and practitioners in operations research and computational intelligence to engage with this rapidly evolving field, providing practical insights into how evolutionary algorithms, swarm intelligence, and other biologically-inspired techniques can address real-world multi-objective challenges across various domains.

Key Features

Springer's comprehensive reference covering recent advances in nature-inspired metaheuristics and multi-objective optimisation.

Provides an accessible overview of the field suitable for non-experts whilst offering depth for experienced researchers in operations research.

Collects state-of-the-art contributions demonstrating practical applications of multi-objective, nature-inspired computing to combinatorial optimisation problems.

Motivates researchers and practitioners to explore evolutionary algorithms and biologically-inspired techniques for complex problem-solving.

Part of Studies in Computational Intelligence series (volume 272), positioning it within established academic literature on AI and machine learning.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
04 May 2012
Listed Since
11 May 2012

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