% FB
@inproceedings{2003-FEA-Brglez,
author = "F. Brglez and X. Y. Li and M. Stallmann  and B. Militzer",
title  = "Reliable Cost Predictions for Finding Optimal Solutions to
           {LABS} Problem: Evolutionary and Alternative Algorithms",
booktitle = "Proceedings of The Fifth International Workshop on Frontiers
              in Evolutionary Algorithms {(FEA2003)},
              Cary, NC, USA, September 26-30, 2003
              ",
year = 2003,
month = "September",
pages = "331--334",
note = "See
         http://\-scsx01.sc.ehu.es/\-ccwgrrom/FEA2003/.
         For links to re-prints, data sets and experimental testbed, see also
          http://\-www.cbl.ncsu.edu/\-publications/",
abstract = "{
The {\em low-autocorrelation binary sequence} (LABS) problem
represents a major challenge to all search algorithms, with the
evolutionary algorithms claiming the best results so far. However,
the termination criteria for these types of stochastic algorithms
are not well-defined and no claims have been made about optimality.
Our approach to find the optima of the LABS problem is based on
(1) experiments with problem sizes for which optimal solutions are known,
(2) an asymptotic analysis of statistics generated by such experiments,
(3) reliable predictions of the cost required to find optimal 
solutions for larger problem sizes.
The proposed methodology provides a well-defined termination criterion for
evolutionary and alternative search algorithms alike.
}",
URLcrossref = "{
For context and related publications, see the LABSbed home page:
    http://www.cbl.ncsu.edu/OpenExperiments/LABS/ 
}",
}