A Comparison of Several Evolutionary Heuristics for the Frequency Assignment Problem

Authors:
Carlos Cotta;José M. Troya
Affiliations:
-;-
Venue:
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Connectionist Models of Neurons, Learning Processes and Artificial Intelligence-Part I
Year:
2001

Citing 3
Cited 0

The Breeder Genetic Algorithm for Frequency Assignment

PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A Permutation Based Genetic Algorithm for Minimum Span Frequency Assignment

PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Genetic forma recombination in permutation flowshop problems

Evolutionary Computation

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Abstract

The Frequency Assignment Problem (FAP) is a very important problem of practicalinterest. This work compares several evolutionary approaches to this problem, based both in the forma analysis framework, and in the decoder paradigm. All approaches are studied from the point of view of two different quality measures of assignments: the number of distinct frequencies, and the frequency span. It is shown that using decoders as embedded heuristics is more adequate than performing a direct search in the feasiblesolution space. Furthermore, despite the apparent symmetry of the problem, a recombination operator based on multiple-emitter-to-frequemcy preservation performs better than focusing on multiple-frequemcy-to-emitter preservation.