Multimodal Optimization by Means of Evolutionary Algorithms (Natural Computing Series) - Image 1

£76.41

Springer Multimodal Optimization by Means of Evolutionary Algorithms (Natural Computing Series)

Name: Multimodal Optimization by Means of Evolutionary Algorithms (Natural Computing Series)
Brand: Springer
Price: 76.41 GBP
Availability: InStock

AI & Machine Learning

About as cheap as it gets. The only time it was cheaper was 2 months ago.

£76 today · all-time low £76 (Apr 2026) · usually £76

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 72 days · 72 data points (no recent data)

Historical

Generating forecast…

Price Distribution

Price distribution over 72 days • 1 price levels

Days at Price

Price Analysis

Most common price: £76 (72 days, 100.0%)

Price range: £76 - £76

Price levels: 1 different prices over 72 days

Description

This book offers the first comprehensive taxonomy for multimodal optimization algorithms, work with its root in topics such as niching, parallel evolutionary algorithms, and global optimization. The author explains niching in evolutionary algorithms and its benefits; he examines their suitability for use as diagnostic tools for experimental analysis, especially for detecting problem (type) properties; and he measures and compares the performances of niching and canonical EAs using different benchmark test problem sets. His work consolidates the recent successes in this domain, presenting and explaining use cases, algorithms, and performance measures, with a focus throughout on the goals of the optimization processes and a deep understanding of the algorithms used. The book will be useful for researchers and practitioners in the area of computational intelligence, particularly those engaged with heuristic search, multimodal optimization, evolutionary computing, and experimental analysis.

Product Specifications

Brand: Springer
Format: hardcover
ASIN: 3319074067
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 15 December 2015
Listed Since: 25 April 2014

Barcode

No barcode data available

Springer Multimodal Optimization by Means of Evolutionary Algorithms (Natural Computing Series)

About as cheap as it gets. The only time it was cheaper was 2 months ago.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Multi-Objective Optimization using Evolutionary Algorithms: 16 (Wiley Interscience Series in Systems and Optimization)

Nature-Inspired Optimizers: Theories, Literature Reviews and Applications: 811 (Studies in Computational Intelligence, 811)

Evolutionary Multi-objective Optimization in Uncertain Environments: Issues and Algorithms: 186 (Studies in Computational Intelligence, 186)

Evolutionary Multi-objective Optimization in Uncertain Environments: Issues and Algorithms: 186 (Studies in Computational Intelligence, 186)

Multi-Objective Optimization Using Evolutionary Algorithms (Wiley Paperback)

Evolutionary Computation in Dynamic and Uncertain Environments: 51 (Studies in Computational Intelligence, 51)

Into a Deeper Understanding of Evolutionary Computing: Exploration, Exploitation, and Parameter Control: Volume 2: 51 (Emergence, Complexity and Computation, 51)

Theory of Evolutionary Computation: Recent Developments in Discrete Optimization (Natural Computing Series)

Evolutionary Computation: Theory and Applications

Evolutionary Learning: Advances in Theories and Algorithms

Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)

Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)

Evolutionary Optimization Algorithms

The Theory of Evolution Strategies (Natural Computing Series)

Applications of Evolutionary Computing: EvoWorkshops 2008: EvoCOMNET, EvoFIN, EvoHOT, EvoIASP, EvoMUSART, EvoNUM, EvoSTOC, and EvoTransLog: 4974 (Lecture Notes in Computer Science, 4974)

Exploring Critical Approaches of Evolutionary Computation

Self-Adaptive Heuristics for Evolutionary Computation: 147 (Studies in Computational Intelligence, 147)

Evolutionary Optimization in Dynamic Environments: 3 (Genetic Algorithms and Evolutionary Computation, 3)

Evolutionary Algorithms in Engineering and Computer Science: Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming, Genetic Programming and Industrial Applications

Exploring Critical Approaches of Evolutionary Computation (Advances in Computer and Electrical Engineering)

Advances in Evolutionary Computing for System Design: 66 (Studies in Computational Intelligence, 66)

Evolutionary Computation for Dynamic Optimization Problems: 490 (Studies in Computational Intelligence, 490)

Evolutionary Computation for Dynamic Optimization Problems: 490 (Studies in Computational Intelligence, 490)

Numerical and Evolutionary Optimization – NEO 2017: 785 (Studies in Computational Intelligence, 785)