Search and Optimization by Metaheuristics Techniques and Algorithms Inspired by Nature

Search and Optimization by Metaheuristics Techniques and Algorithms Inspired by Nature / by Ke-Lin Du, M. N. S. Swamy.

This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphas...

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Bibliographic Details
Main Authors: Du, Ke-Lin (Author), Swamy, M. N. S. (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Birkhäuser, 2016.
Edition:1st ed. 2016.
Series:Springer eBook Collection.
Subjects:
Computer mathematics.
Algorithms.
Mathematical optimization.
Computer simulation.
Computational intelligence.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • Preface
  • Introduction
  • Simulated Annealing
  • Optimization by Recurrent Neural Networks
  • Genetic Algorithms and Genetic Programming
  • Evolutionary Strategies
  • Differential Evolution
  • Estimation of Distribution Algorithms
  • Mimetic Algorithms
  • Topics in EAs
  • Particle Swarm Optimization
  • Artificial Immune Systems
  • Ant Colony Optimization
  • Tabu Search and Scatter Search
  • Bee Metaheuristics
  • Harmony Search
  • Biomolecular Computing
  • Quantum Computing
  • Other Heuristics-Inspired Optimization Methods
  • Dynamic, Multimodal, and Constraint-Satisfaction Optimizations
  • Multiobjective Optimization
  • Appendix 1: Discrete Benchmark Functions
  • Appendix 2: Test Functions
  • Index.

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