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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Hyperheuristic for the Parameter Tuning of a Bio-Inspired Algorithm of Query Routing in P2P Networks
verfasst von : Paula Hernández, Claudia Gómez, Laura Cruz, Alberto Ochoa, Norberto Castillo, Gilberto Rivera
Erschienen in: Advances in Soft Computing
Verlag: Springer Berlin Heidelberg
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The computational optimization field defines the parameter tuning problem as the correct selection of the parameter values in order to stabilize the behavior of the algorithms. This paper deals the parameters tuning in dynamic and large-scale conditions for an algorithm that solves the
Semantic Query Routing Problem
(SQRP) in
peer-to-peer
networks. In order to solve SQRP, the HH_AdaNAS algorithm is proposed, which is an ant colony algorithm that deals synchronously with two processes. The first process consists in generating a SQRP solution. The second one, on the other hand, has the goal to adjust the
Time To Live
parameter of each ant, through a hyperheuristic. HH_AdaNAS performs adaptive control through the hyperheuristic considering SQRP local conditions. The experimental results show that HH_AdaNAS, incorporating the techniques of parameters tuning with hyperheuristics, increases its performance by 2.42% compared with the algorithms to solve SQRP found in literature.