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  • The Practical Handbook of Genetic Algorithms: Applications, Second Edition

    The Practical Handbook of Genetic Algorithms by Chambers, Lance D.;

    Applications, Second Edition

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      • Publisher's listprice GBP 240.00
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        114 660 Ft (109 200 Ft + 5% VAT)
      • Discount 20% (cc. 22 932 Ft off)
      • Discounted price 91 728 Ft (87 360 Ft + 5% VAT)

    114 660 Ft

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    Availability

    Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
    Not in stock at Prospero.

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Edition number 2, New edition
    • Publisher Chapman and Hall
    • Date of Publication 7 December 2000

    • ISBN 9781584882404
    • Binding Hardback
    • No. of pages544 pages
    • Size 229x152 mm
    • Weight 1170 g
    • Language English
    • Illustrations 200 Illustrations, black & white; 68 Tables, black & white
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    Short description:

    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: Applications. Like its predecessor, this edition provides practitioners with material they can use productively in their own endeavors. Among the applications explored are scheduling problems, optimization, multidimensional scaling, constraint handling, and feature selection and classification. All of the computer code offered in the book is available for download from the Internet.

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    Long description:

    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.

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    Table of Contents:

    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.

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