Hi, All, I am wondering how we can do initialization in GLPK.
In my problems, I am optimizating several thousands of small LP problems. I need their solutions to be similar to each other. However, due to various noise in these problems, some of them are not feasible or not easy to converge. In result, the output from GLPK for these problems are not close to each other at all. One solution I am thinking about is to use the solution from one problem as the initial solution of the next problem. In this way, even if the next problem will not converge, the result might still be close to the initial solution. Could anybody tell me how to specify the initial solution for GLPK? Or is it possible to do? Thanks. -- Best wishes, Jinwei Gu
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