The Practical Handbook of Genetic Algorithms: New Frontiers, Volume 2

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Lance D. Chambers
CRC Press, Aug 15, 1995 - Mathematics - 448 pages
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The mathematics employed by genetic algorithms (GAs)are among the most exciting discoveries of the last few decades. But what exactly is a genetic algorithm? A genetic algorithm is a problem-solving method that uses genetics as its model of problem solving. It applies the rules of reproduction, gene crossover, and mutation to pseudo-organisms so those "organisms" can pass beneficial and survival-enhancing traits to new generations. GAs are useful in the selection of parameters to optimize a system's performance. A second potential use lies in testing and fitting quantitative models. Unlike any other book available, this interesting new text/reference takes you from the construction of a simple GA to advanced implementations. As you come to understand GAs and their processes, you will begin to understand the power of the genetic-based problem-solving paradigms that lie behind them.

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Locating Putative Protein Signal Sequences
Selection Methods for Evolutionary Algorithms
Parallel Cooperating Genetic Algorithms An Application to Robot Motion Planning
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Structure and Performance of FineGrain Parallelism in Genetic Search
Parameter Estimation for a Generalized Parallel Loop Scheduling Algorithm
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Vehicle Routing with Time Windows using Genetic Algorithms
Evolutionary Algorithms and Dialogue
Incorporating Redundancy and Gene Activation Mechanisms in Genetic search for Adapting to NonStationary Environments
Input Space Segmentation with a Genetic Algorithm for Generation of Rule Based Classifier Systems
An Indexed Bibliography of Genetic Algorithms

Controlling a Dynamic Physical Systems Using Genetic Based Learning Methods

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Page 24 - This work was supported in part by the UK Science and Engineering Research Council, under grant GR/D97757, and in part by the Applied Mathematical Sciences subprogram of the Office of Energy Research, US Department of Energy, under contract W-31-109-Eng-38. References [1] Khayri AM Ali. Or-parallel execution of Prolog on BC-Machine.
Page 25 - K. Deb and DE Goldberg, An investigation of niche and species formation in genetic function optimization...

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