Timeline for Does removing some constraints in convex program change the optimal solution?
Current License: CC BY-SA 3.0
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| Jan 4, 2015 at 21:33 | comment | added | Ann | Hello Dirk, I was thinking of the following argument. Please let me know where it goes wrong. The problem is to minimize a convex function f(x_1,x_2) over a set of linear constraints. Call this convex program (i). I think it is true that removing the non-tight constraints doesn't matter. Then I remove all other tight constraints but two of them (like eliminate redundant equations). Call this program (ii). I think the optimal solution (x^*_1, x^*_2) of (ii) is a feasible solution of (i). So (x^*_1, x^*_2) should also be the optimal solution of (i), because objective functions are the same. | |
| Jan 4, 2015 at 21:10 | history | edited | Dirk | CC BY-SA 3.0 |
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| Jan 4, 2015 at 21:04 | comment | added | Dirk | Jupp, this is also true in two variables. | |
| Jan 4, 2015 at 16:38 | comment | added | Ann | Hello Dirk, in my case the convex program only has two variables. Maybe you didn't notice my description? | |
| Jan 4, 2015 at 16:15 | history | answered | Dirk | CC BY-SA 3.0 |