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GECCO
2009
Springer

A stopping criterion based on Kalman estimation techniques with several progress indicators

9 years 1 months ago
A stopping criterion based on Kalman estimation techniques with several progress indicators
The need for a stopping criterion in MOEA’s is a repeatedly mentioned matter in the domain of MOOP’s, even though it is usually left aside as secondary, while stopping criteria are still usually based on an a-priori chosen number of maximum iterations. In this paper we want to present a stopping criterion for MOEA’s based on three different indicators already present in the community. These indicators, some of which were originally designed for solution quality measuring (as a function of the distance to the optimal Pareto front), will be processed so they can be applied as part of a global criterion, based on estimation theory to achieve a cumulative evidence measure to be used in the stopping decision (by means of a Kalman filter). The implications of this cumulative evidence are analyzed, to get a problem and algorithm independent stopping criterion (for each individual indicator). Finally, the stopping criterion is presented from a data fusion perspective, using the differen...
José Luis Guerrero, Jesús Garc&iacut
Added 26 May 2010
Updated 26 May 2010
Type Conference
Year 2009
Where GECCO
Authors José Luis Guerrero, Jesús García, Luis Martí, José Manuel Molina, Antonio Berlanga
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