Recent Advances in Memetic Algorithms

• Corporate Author: SpringerLink (Online service)
• Other Authors: Hart, William E. (Editor), Smith, J. E. (Editor), Krasnogor, N. (Editor)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2005.
• Series: Studies in Fuzziness and Soft Computing, 166
• Subjects: Mathematics.; Software engineering.; Artificial intelligence.; Probabilities.; Applied mathematics.; Engineering mathematics.; Probability Theory and Stochastic Processes.; Software Engineering/Programming and Operating Systems.; Appl.Mathematics/Computational Methods of Engineering.; Artificial Intelligence (incl. Robotics).

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...

Table of Contents:

• 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.