User Portlet
Featured Contributor
| Discussions |
|---|
| the one is part of the name In[7]:= a1 Out[7]= a1 |
| &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/68498321-fd6f-422a-bd77-7cd34e38a11a |
| &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/9653b1b8-eca3-4396-a907-967e7ba1210a |
| q1 and q2 aren't variables |
| &[Wolfram Notebook][1] [1]: https://www.wolframcloud.com/obj/fbc9708d-fe0a-4fad-8365-a1530a9f23bd |
| In[1]:= (* Square of the distance between two points *) distsqr[{{x1_, y1_}, {x2_, y2_}}] = (x1 - x2)^2 + (y1 - y2)^2; In[2]:= (* Derivative of the distance squared between a point {x,y} \ and a point on a line passing... |
| Henrik, Your method is much slower than mine. Since the objective function is quadratic and the constraints for a point to be in a polygon are linear, QuadraticOptimization is the best approach. Frank |
| Recently I've been using the Kuhn-Tucker approach to maximize the minimum separation between polygons inside a polygon border. I'm using ParametricIPOPTMinimize, rather than Reduce, to solve the resulting equations. ![enter image... |
| f[up_] := NIntegrate[Tan[x]/(x + Sin[x]), {x, 0, up}] Plot[f[up], {up, 0, 2}] ![enter image description here][1] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=9544int.jpg&userId=29126 |
| ListPlot[res2, PlotRange -> {{142, 158}, {205, 230}}] |