Lance D. Chambers (ed.)

The Practical Handbook of Genetic Algorithms

Applications, Second Edition
Herausgeber: Chambers, Lance D.

• Gebundenes Buch

Produktbeschreibung

Rapid developments in the field of genetic algorithms along with the popularity of the first edition precipitated this completely revised, thoroughly updated second edition of The Practical Handbook of Genetic Algorithms. Like its predecessor, this edition helps practitioners stay up to date on recent developments in the field and provides material they can use productively in their own endeavors. For this edition, the editor again recruited authors at the top of their field and from a cross section of academia and industry, theory and practice. Their contributions detail their own research, new applications, experiment results, and recent advances. Among the applications explored are scheduling problems, optimization, multidimensional scaling, constraint handling, and feature selection and classification. The science and art of GA programming and application has come a long way in the five years since publication of the bestselling first edition. But there still is a long way to go before its bounds are reached-we are still just scratching the surface of GA applications and refinements. By introducing intriguing new applications, offering extensive lists of code, and reporting advances both subtle and dramatic, The Practical Handbook of Genetic Algorithms is designed to help readers contribute to scratching that surface a bit deeper.

Produktdetails

• Verlag: Chapman and Hall/CRC
• 2. Auflage
• Seitenzahl: 544
• Erscheinungstermin: 7. Dezember 2000
• Englisch
• Abmessung: 235mm x 157mm x 34mm
• Gewicht: 929g
• ISBN-13: 9781584882404
• ISBN-10: 1584882409
• Artikelnr.: 21996434

Autorenporträt

Lance D. Chambers

Inhaltsangabe

Model Building, Model Testing, and Model Fitting. Compact Fuzzy Models and
Classifiers through Model Reduction and Evolutionary Optimization. On the
Application of Reorganization Operators for Solving a Language Recognition
Problem Using GA to Optimize the Selection and Scheduling of Road Projects.
Decoupled Optimization of Power electronics Circuits using GAs. Feature
Selection and Classification in the Diagnosis of Cervical Cancer.
Algorithms for Multidimensional Scaling. Genetic-Algorithms-Based Approach
for Transportation Optimization Problems. Solving Job-Shop Scheduling
Problems by means of GAs. Applying the Implicit Redundant Representation GA
in an Unstructured Problem Domain. How to Handle Constraints with
Evolutionary Algorithms. An Optimized Fuzzy Logic Controller for Active
Power Factor Corrector Using GAs.