Tuning the PBIL algorithm to solve a real-world FAP problem
by Jose M. Chaves-Gonzalez, Miguel A. Vega-Rodriguez, David Dominguez-Gonzalez, Juan A. Gomez-Pulido, Juan M. Sanchez-Perez
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 2, No. 1, 2010

Abstract: Frequency planning, also known as frequency assignment problem (FAP), is a very important task for current GSM operators. FAP basically tries to minimise the number of interferences (or conflicts in the communications) caused when a limited number of frequencies has to be assigned to a quite high number of transceivers (and there are much more transceivers than frequencies). In this work, we focus on solving this problem for a realistic-sized, real-world GSM network using the population-based incremental learning (PBIL) algorithm. The work described here is divided in two parts. In the first one, we analyse and fix the standard PBIL algorithm to solve the FAP; whereas in the second, we take as initial point the results obtained with the standard version of PBIL and we perform a complete study with the most relevant variations of the algorithm to discover which approach can compute the best frequency plans for real-world instances.

Online publication date: Wed, 02-Dec-2009

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