Is this an analytical gradient? Perhaps it is incorrect. For minimization, its clear from this gradient where the direction of steepest descent is. So if it can’t use this information to get closer to a local minimum, then I would think there is something wrong with the input or bizarre about the function.
Best, Grey > On May 11, 2015, at 4:00 PM, Joshua N Pritikin <[email protected]> wrote: > > During optimization, I have a problem that gets to a point where the > gradient looks like this, > > [0] gradient = t( matrix(c( # 51x1 > -31780.195562, -38508.674735, -50973.208738, -55408.084812, > -66931.026056, -74286.656477, -80710.037658, -32059.100573, > -40421.260358, -47351.363022, -56331.397546, -67570.244335, > -71730.720066, -80617.938563, -30100.959330, -40235.309256, > -47047.853982, -56263.225828, -67009.403836, -75987.083372, > -84897.553874, -62848.356157, -210680.805240, -214470.061730, > -234536.487353, -241645.958717, -262177.928304, -278085.836093, > -286557.250051, -63655.124325, -214492.388535, -219036.315591, > -224526.862707, -240634.971741, -248375.386046, -263267.566427, > -289505.767031, -64899.664139, -213624.942908, -222084.527486, > -223847.520561, -236782.323103, -258931.376366, -276562.312245, > -304241.522192, -25035.332609, -25125.410641, -25003.755675, > -4302.824452, -4986.836691, -3574.837605), byrow=TRUE, nrow=1, ncol=51)) > > This point is nowhere near the minimum. Is it significant that all the > gradients are negative? Is that why SLSQP cannot determine a search > direction? When this occurs, could SLSQP use the gradient as the search > direction? > > -- > Joshua N. Pritikin > Department of Psychology > University of Virginia > 485 McCormick Rd, Gilmer Hall Room 102 > Charlottesville, VA 22904 > http://people.virginia.edu/~jnp3bc > > _______________________________________________ > NLopt-discuss mailing list > [email protected] > http://ab-initio.mit.edu/cgi-bin/mailman/listinfo/nlopt-discuss _______________________________________________ NLopt-discuss mailing list [email protected] http://ab-initio.mit.edu/cgi-bin/mailman/listinfo/nlopt-discuss
