How to faster solve a series of problems with different through parameters in objective function?

[Simon]

Dear Johan,

  I'm solving a large-scale integer programming problem by using Lagrangian Relaxation. One of the subproblems is solved by CPLEX through yalmip in each iteration, however, I found the total computing time is much larger than the "solvertime", i.e., the "yalmiptime" is 10+ larder than the "solvertime" in some cases. I wonder if there's some way to save the total computing time. Please check the attachment for the program coded in Matlab and I'll be happy if it can help you understanding my question. I'm looking forward to hearing back from you.

Regards,

Simon

[Mark L. Stone]

To hold you over until Johan sees this, use optimizer https://yalmip.github.io/optimizerupdates/ .