> On May 15, 2017, at 4:43 PM, Kaushik Matia <[email protected]> wrote: > And for those if I implement the derivative of the rounding constraints > (where C_i are the rounding constraints for each i=1 to N) as > d C_i/ dx_i = if ( x_i - 0.01* integer part (x_i/0.01) + 0.005) < epsilon > then huge_value else 0.
This issue, where are trying to enforce discrete values of the optimization variables but still want to use derivative-based local-optimization methods, shows up a lot in topology optimization A popular approach is called the "SIMP" method (google "SIMP optimization" and you will get a lot of links). Basically, you pass your variable x_i through a nonlinear step-like function that you slowly make steeper and steeper. _______________________________________________ NLopt-discuss mailing list [email protected] http://ab-initio.mit.edu/cgi-bin/mailman/listinfo/nlopt-discuss
