A parallel evolutionary algorithm applied to the minimum interference frequency assignment problem
This article presents the application of a Parallel Evolutionary Algorithm to solve the Minimum Interference Frequency Assignment Problem (MI-FAP). This is a capital problem in the mobile telecommunication field, which proposes to find an assignation of a set of frequencies to minimize the communica...
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| Autores principales: | , , , |
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2006
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/22625 |
| Aporte de: |
| Sumario: | This article presents the application of a Parallel Evolutionary Algorithm to solve the Minimum Interference Frequency Assignment Problem (MI-FAP). This is a capital problem in the mobile telecommunication field, which proposes to find an assignation of a set of frequencies to minimize the communication interference. MI-FAP is a NP-Complete optimization problem; so traditional exact algorithms are useless for solving real-life problem instances in reasonable execution times.
This work proposes to use a metaheuristic approach to find good quality solutions for real-life MIFAP instances never faced before using Evolutionary Algorithms. Evaluation experiments performed on those real-life instances report promising numerical results for both serial and parallel models of the algorithm proposed. In addition, the parallel version shows high levels of computational efficiency, demonstrating a superlinear speedup behavior for the instances studied |
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