Recent Advances in Memetic Algorithms

Memetic algorithms are evolutionary algorithms that apply a local search process to refine solutions to hard problems. Memetic algorithms are the subject of intense scientific research and have been successfully applied to a multitude of real-world problems ranging from the construction of optimal u...

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Détails bibliographiques
Cote:Libro Electrónico
Collectivité auteur: SpringerLink (Online service)
Autres auteurs: Hart, William E. (Éditeur intellectuel), Krasnogor, Natalio (Éditeur intellectuel), Smith, J.E (Éditeur intellectuel)
Format: Électronique eBook
Langue:Inglés
Publié: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2005.
Édition:1st ed. 2005.
Collection:Studies in Fuzziness and Soft Computing, 166
Sujets:
Probabilities.
Software engineering.
Engineering mathematics.
Engineering-Data processing.
Artificial intelligence.
Probability Theory.
Software Engineering.
Mathematical and Computational Engineering Applications.
Artificial Intelligence.
Accès en ligne:Texto Completo
Table des matières:
  • to Memetic Algorithms
  • Memetic Evolutionary Algorithms
  • Applications of Memetic Algorithms
  • An Evolutionary Approach for the Maximum Diversity Problem
  • Multimeme Algorithms Using Fuzzy Logic Based Memes For Protein Structure Prediction
  • A Memetic Algorithm Solving the VRP, the CARP and General Routing Problems with Nodes, Edges and Arcs
  • Using Memetic Algorithms for Optimal Calibration of Automotive Internal Combustion Engines
  • The Co-Evolution of Memetic Algorithms for Protein Structure Prediction
  • Hybrid Evolutionary Approaches to Terminal Assignment in Communications Networks
  • Effective Exploration & Exploitation of the Solution Space via Memetic Algorithms for the Circuit Partition Problem
  • Methodological Aspects of Memetic Algorithms
  • Towards Robust Memetic Algorithms
  • NK-Fitness Landscapes and Memetic Algorithms with Greedy Operators and k-opt Local Search
  • Self-Assembling of Local Searchers in Memetic Algorithms
  • Designing Efficient Genetic and Evolutionary Algorithm Hybrids
  • The Design of Memetic Algorithms for Scheduling and Timetabling Problems
  • Memetic Algorithms for Multiobjective Optimization: Issues, Methods and Prospects
  • Related Search Technologies
  • A Memetic Learning Classifier System for Describing Continuous-Valued Problem Spaces
  • Angels & Mortals: A New Combinatorial Optimization Algorithm.

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