HeuristicLab Grid - a flexible and extensible environment for parallel heuristic optimization

• Autorzy: Wagner S. , Affenzeller M.
• Języki publikacji: EN

Abstrakty

EN

Heuristic optimization techniques turned out to be very well suited for attacking various kinds of problems. However, when it comes to practical applications like scheduling problems, route planning, etc., also these algorithms still suffer from a very long running time mainly due to the rather large problem instances relevant in real world applications. Consequently, parallel optimization methods like parallel Genetic Algorithms are widely used to overcome this handicap. In this paper, the authors present a new environment for parallel heuristic optimization based upon the already proposed HeuristicLab. In contrast to other existing grid computing or parallel optimization projects, HeuristicLab Grid offers the possibility of rapid and easy use of existing optimization algorithms and problems in a parallel way without the need of complex installation and maintenance.

Słowa kluczowe

EN

genetic algorithm; parallel genetic algorithm; grid computing; route planning; heuristicLab grid

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Systems Science
• Rocznik: 2004
• Tom: Vol. 30, no 4
• Strony: 103--110
• Opis fizyczny: Bibliogr. 13 poz., rys.

Twórcy

autor

Wagner S.

• Institute of Systems Theory and Simulation, Johannes Kepler University, Altenbergerstrasse 69, A-4040 Linz, Austria

autor

Affenzeller M.

• Institute of Systems Theory and Simulation, Johannes Kepler University, Altenbergerstrasse 69, A-4040 Linz, Austria

Bibliografia

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