Does anyone know of such a library that performs mathematical optimization (linear programming, convex optimization, or more general types of problems)? I'm looking for something like MATLAB, but with the ability to handle larger problems. Do I have to write my own implementations, or buy one of those commercial products (CPLEX and the l...
I'm trying to use DSDP (semidefinite programming package) with cvxopt. I have both of them installed (matlab version for DSDP). I have Python 2.5.2. When trying to use dsp(..., solver='dsdp') I get an errors mentioning solvers.dsdp is not installed. How to I make them work together? ...
I am using CPLEX for solving huge optimization models (more than 100k variables) now I'd like to see if I can find an open source alternative, I solve mixed integer problems (MILP) and CPLEX works great but it is very expensive if we want to scale so I really need to find an alternative or start writing our own ad-hoc optimization librar...
I have been working on Support Vector Machine for about 2 months now. I have coded SVM myself and for the optimization problem of SVM, I have used Sequential Minimal Optimization(SMO) by Mr. John Platt. Right now I am in the phase where I am going to grid search to find optimal C value for my dataset. ( Please find details of my project...
I have a queatoin about IloLPMatrix and addGe. I was trying to follow the example of AdMIPex5.java to generate user defined cutting planes based on the solution to the LP relaxation. The difference is that eh initial MIP model is not read in from a mps file, but set up in the code using methods like addGe, addLe etc. I think this is wh...
I fully realize that Convex Optimization packages, like Linear Algebra packages, should be things you use, not implement. However, for purely education purposes -- is there any good resource -- link / book on how to implement a convex optimization package? (like for quadratic programs with quadratic constraints?) Thanks! ...
I would like to solve something like the following: maximize the sum (over i) of v_i * g_i(w) subject to w (a vector) summing to 1 (or <1,w>=1), where g_i(w) is defined as the argmax of w^t*x (or ), subject to x is in a convex ellipsoid, E_i , and x is in the nonnegative orthant. Now, solving each program is fairly simple, but I have se...
I found some solutions, but they're too messy. ...