> >
> >ICASE Report No. 96-71
> >--------------------------------------------------------------------------
> >
> >
> >		RANK ORDERING AND POSITIVE BASES IN
> >		    PATTERN SEARCH ALGORITHMS
> >
> >	      Robert Michael Lewis & Virginia Torczon
> >
> >
> >We present two new classes of pattern search algorithms for unconstrained
> >minimization: the rank ordered and the positive basis pattern search
> >methods.  These algorithms can nearly halve the worst case cost of an
> >iteration compared to the classical pattern search algorithms.  The rank
> >ordered pattern search methods are based on a heuristic for approximating
> >the direction of steepest descent, while the positive basis pattern search
> >methods are motivated by a generalization of the geometry characteristic
> >of the patterns of the classical methods.  We describe the new classes of
> >algorithms and present the attendant global convergence analysis.
> >
> >
> >---------------------------------------------------------------------------
> >This ICASE Report is available at the following URL:
> >ftp://ftp.icase.edu/pub/techreports/96/96-71.ps