£88.51

Springer Nature-Inspired Algorithms and Applied Optimization

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Description

Explore the latest developments in computational intelligence with this comprehensive volume from Springer. This book provides an in-depth review of state-of-the-art nature-inspired algorithms and their practical applications across multiple disciplines. Whether you are interested in feature selection, engineering design optimization, scheduling, or vehicle routing, this text offers the technical depth required for advanced study. Each algorithm is introduced alongside its implementation through practical case studies and extensive literature reviews. To help you gain a deeper understanding of how these systems function, the book includes self-contained chapters focusing on theoretical analyses. These sections cover essential topics such as convergence analysis and no-free-lunch theorems, providing clear insights into the mechanics of current optimization methods. This is an essential resource for those studying AI, machine learning, and complex computational problem-solving.

Key Features

Covers state-of-the-art developments in nature-inspired algorithms and their wide range of applications in various scientific disciplines.

Provides practical implementation details for algorithms through specific case studies and detailed literature reviews.

Includes dedicated chapters on theoretical analysis, such as convergence analysis, to deepen your understanding of optimization mechanics.

Explores diverse application areas including feature selection, engineering design optimization, scheduling, and vehicle routing.

Offers insights into fundamental concepts like no-free-lunch theorems to provide a complete view of current optimization trends.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
18 October 2017
Listed Since
09 August 2017

Barcode

No barcode data available

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