An-Najah National University

Baker Abdalhaq


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  • Sunday, January 25, 2009
  • Evolutionary Optimization Techniques on Computational Grids
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  • Optimization of complex objective functions such as environmental models is a compute-intensive task, difficult to achieve by classical optimization techniques. Evolutionary techniques such as genetic algorithms present themselves as the best alternative to solving this problem. We present a friendly optimization framework for complex objective function on a computational grid platform, which allows easy incorporation of new optimization strategies. This framework was developed using the MW library and the Condor system. The framework architecture is described, and a case study of a forest-fire propagation simulator is then analyzed.
    This work was supported by the CICYT under contract TIC 98-0433 and partially supported by the DGICYT (Spain).
    Book Series Lecture Notes in Computer Science
    Publisher Springer Berlin / Heidelberg
    ISSN 0302-9743 (Print) 1611-3349 (Online)
    Volume Volume 2329/2002
    Book Computational Science — ICCS 2002
    DOI 10.1007/3-540-46043-8
    Copyright 2002
    ISBN 978-3-540-43591-4
    DOI 10.1007/3-540-46043-8_52
    Pages 513-522
    Subject Collection Computer Science
    SpringerLink Date Tuesday, January 01, 2002
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Baker Khaldoun Abdalhaq
Cmputer Science
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