Hybrid Metaheuristics: Powerful Tools for Optimization (Artificial Intelligence: Foundations, Theory, and Algorithms) - Image 1

£91.82

Springer Hybrid Metaheuristics: Powerful Tools for Optimization (Artificial Intelligence: Foundations, Theory, and Algorithms)

Name: Hybrid Metaheuristics: Powerful Tools for Optimization (Artificial Intelligence: Foundations, Theory, and Algorithms)
Brand: Springer
Price: 91.82 GBP
Availability: InStock

Managers' Guides to Computing

About as cheap as it gets. The only time it was cheaper was 3 months ago.

£92 today · all-time low £92 (Mar 2026) · usually the usual

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 40 days • 40 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 40 days • 1 price levels

Days at Price

Price Analysis

Most common price: £92 (40 days, 100.0%)

Price range: £92 - £92

Price levels: 1 different prices over 40 days

Description

This book explains the most prominent and some promising new, general techniques that combine metaheuristics with other optimization methods. A first introductory chapter reviews the basic principles of local search, prominent metaheuristics, and tree search, dynamic programming, mixed integer linear programming, and constraint programming for combinatorial optimization purposes. The chapters that follow present five generally applicable hybridization strategies, with exemplary case studies on selected problems: incomplete solution representations and decoders; problem instance reduction; large neighborhood search; parallel non-independent construction of solutions within metaheuristics; and hybridization based on complete solution archives. The authors are among the leading researchers in the hybridization of metaheuristics with other techniques for optimization, and their work reflects the broad shift to problem-oriented rather than algorithm-oriented approaches, enabling faster and more effective implementation in real-life applications. This hybridization is not restricted to different variants of metaheuristics but includes, for example, the combination of mathematical programming, dynamic programming, or constraint programming with metaheuristics, reflecting cross-fertilization in fields such as optimization, algorithmics, mathematical modeling, operations research, statistics, and simulation. The book is a valuable introduction and reference for researchers and graduate students in these domains.

Product Specifications

Brand: Springer
Format: hardcover
ASIN: 3319308823
Category: Books > Subjects > Business, Finance & Law > E-Commerce > Managers' Guides to Computing
Domain: Amazon UK
Release Date: 23 August 2016
Listed Since: 03 February 2016

Barcode

No barcode data available

Springer Hybrid Metaheuristics: Powerful Tools for Optimization (Artificial Intelligence: Foundations, Theory, and Algorithms)

About as cheap as it gets. The only time it was cheaper was 3 months ago.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Hybrid Metaheuristics: 434 (Studies in Computational Intelligence, 434)

Computing Tools for Modeling, Optimization and Simulation: Interfaces in Computer Science and Operations Research: 12 (Operations Research/Computer Science Interfaces Series, 12)

Computing Tools for Modeling, Optimization and Simulation: Interfaces in Computer Science and Operations Research: 12 (Operations Research/Computer Science Interfaces Series, 12)

Recent Metaheuristics Algorithms for Parameter Identification: 854 (Studies in Computational Intelligence, 854)

Recent Metaheuristics Algorithms for Parameter Identification: 854 (Studies in Computational Intelligence, 854)

Hybrid Metaheuristics: 434 (Studies in Computational Intelligence, 434)

Metaheuristics: Progress in Complex Systems Optimization: 39 (Operations Research/Computer Science Interfaces Series, 39)

Matheuristics: Hybridizing Metaheuristics and Mathematical Programming: 10 (Annals of Information Systems, 10)

Metaheuristics: Progress in Complex Systems Optimization: 39 (Operations Research/Computer Science Interfaces Series, 39)

Metaheuristic Algorithms: New Methods, Evaluation, and Performance Analysis: 1163 (Studies in Computational Intelligence, 1163)

Comprehensive Metaheuristics: Algorithms and Applications

Hybrid Metaheuristics: An Emerging Approach to Optimization: 114 (Studies in Computational Intelligence, 114)

Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance

Advances in Metaheuristics: Applications in Engineering Systems

Advances in Metaheuristics: Applications in Engineering Systems

Heuristics for Optimization and Learning: 906 (Studies in Computational Intelligence, 906)

Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization

Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization

Advanced Techniques for Modifying Metaheuristics - Morgan Kaufmann

Bioinspired Heuristics for Optimization: 774 (Studies in Computational Intelligence, 774)

Metaheuristics: From Design to Implementation

Handbook of Metaheuristics: 272 (International Series in Operations Research & Management Science, 272)

Integer Programming and Combinatorial Optimization: 11th International IPCO Conference, Berlin, Germany, June 8-10, 2005, Proceedings: 3509 (Lecture Notes in Computer Science, 3509)

Metaheuristics in Machine Learning: Theory and Applications: 967 (Studies in Computational Intelligence, 967)