Closed junhyeokahn closed 3 years ago
Hi! It works without the option, although IPOPT might do some smarter tricks when you additionally set that option, I haven't experimented with that yet.
Generally I've found it's quite difficult to warm-start interior point methods like IPOPT, because of the way they solve the problem: The initial variables are often changed a lot to move into the center of the constraints during the first iteration. SQP methods, like SNOPT, might be a better choice if you have trustworthy information of the initial values (like in Model-Predictive-Control, where the initial values can be the solution of the previous solve).
Thanks for your kind reply!
Hi! It works without the option, although IPOPT might do some smarter tricks when you additionally set that option, I haven't experimented with that yet.
Generally I've found it's quite difficult to warm-start interior point methods like IPOPT, because of the way they solve the problem: The initial variables are often changed a lot to move into the center of the constraints during the first iteration. SQP methods, like SNOPT, might be a better choice if you have trustworthy information of the initial values (like in Model-Predictive-Control, where the initial values can be the solution of the previous solve).
Hi @awinkler, I have the same question about using SNOPT. Do I just set the variables with good initial values or I should also change the parameter "Cold" in the snopt_sovler.cc? Once I set Cold = 2, which stands for warm starting, SNOPT gives warnings of "Invalid argument Fstate" and it seems that Fstate are not assigned with any meaningful values in SnoptAdapter. Thank you!
Hello! I appreciate your efforts in maintaining this nice repo.
I have a quick question about the warm starting of the optimizer. Can I just set variables with the numbers I want to initialize as you do in here? Or should I call extra method such as
SetOption("warm_start_init_point", "yes");
?