I need to solve a linear program in R where the variables are matrices.
More specifically, my optimizing function looks like this.
Max X(A+B)Y - x - y,
where X,Y,A,B are matrices and x,y are scalars. Solve for X,Y,x,y
Subject to bunch of constraints like any linear program
Is there a way to solve this in R?
I checked out linprog and limsolve packages in R. They solve linear programs of scalars.
Is there a way to do the same for matrices in R.
Thanks for your help.
Googling for R linear programming matrices yielded a number of interesting links, of which the following might be interesting:
Simplex Method for Linear Programming Problems, for the boot package.
Related
I am trying to use cplexAPI to solve quadratic programs or linear programs with a quadratic constraint.
While it seems to be pretty straightforward to use cplexAPI to solve linear programs (with the vignette at https://cran.r-project.org/web/packages/cplexAPI/vignettes/cplexAPI.pdf), it seems that using cplexAPI to solve quadratic programs or linear programs with a quadratic constraint is much more difficult. I tried to look over the package documentation, but I have no clue on how to do so.
Therefore, may I know how to use cplexAPI to solve quadratic programs or linear programs, or if there is any code samples for these two tasks?
In addition, the package Rcplex seems to be pretty similar, but its last update is already more than 5 years ago. So it would be really nice to know how the above two tasks can be done using cplexAPI in R. Thanks!
with cplexAPI you may use addQConstrCPLEX to add quadratic constraints
I have an optimization problem with the following characteristics :
Linear objective function with binary variables (only)
Non-linear constraints.
I am looking for an adapted algorithm in R. Any ideas?
When I have the same optimization problem but with linear constraints, I use the ROI:: suite with the Multiple Solution Binary Linear Problem plugin: ROI.plugin.msbinlp. I am checking out the Rsolnp package but I am yet unable to constraint the solution to integer/binary variables.
Any idea would be very much appreciated. Thank you in advance!
I have a mathematical optimization which I wish to solve in R consider this system/problem:
How Can I solve this problem in R?
In this model Budget, p_l for all l and mu_target are fixed constants while muis a given m-dimensional vector and R is a given n by m matrix.
I have looked into constrOptim and lp but I don't have the imagination to implement the constraints
Those functions require that I have a "constraint" matrix but my problem is that I simply don't know how to design that constraint matrix. There are not many examples with decision variables on both sides of the equations.
Have a look on the nloptr package. It has quite extensive documentation with examples. Lots of algorithms to choose from, depending what problem you are trying to resolve.
NLoptr link
I know that it's quite simple to solve the equation in Matlab. But is there a way to solve it in R as well? I need it for my Kalman filter implementations.
I am trying to do some computations using Laplace transforms in R. I used the
continued fractions approach to compute Laplace transform of a birth-death
process as described in Abate 1999. But I cannot find a simple numerical routine to compute the inverse Laplace transform (evaluated at 0 in my case). Does anyone have ideas on how to do this in R?
Computing inverse Laplace transforms numerically is tricky. I remember seeing some relatively recent results on the ACM. Googling around a bit, I found some
Python code implementing one of these algorithms. Maybe you can adapt it to your purposes.