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March 8, 2015 23:22
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Quadratic programming: Use matrix inputs to solve a QP with ipoptr
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ipoptr_qp <- function(Dmat, dvec, Amat, bvec, ub=100){ | |
# Solve the quadratic program | |
# | |
# min -d^T x + 1/2 x^T D x | |
# s.t. A%*%x>= b | |
# | |
# with ipoptr. | |
n <- length(bvec) | |
# Jacobian structural components | |
j_vals <- unlist(Amat[Amat!=0]) | |
j_mask <- make.sparse(ifelse(Amat!=0, 1, 0)) | |
# Hessian structural components | |
h_mask <- make.sparse(ifelse(upper.tri(Dmat, diag=TRUE) & Dmat!=0, 1, 0)) | |
h_vals <- do.call(c, sapply(1:length(h_mask), function(i) Dmat[i,h_mask[[i]]])) | |
# build the ipoptr inputs | |
eval_f <- function(x) return(-t(dvec)%*%x + 0.5*t(x)%*%Dmat%*%x) | |
eval_grad_f <- function(x) return(-dvec + Dmat%*%x) | |
eval_h <- function(x, obj_factor, hessian_lambda) return(obj_factor*h_vals) | |
eval_h_structure <- h_mask | |
eval_g <- function(x) return(t(Amat)%*%x) | |
eval_jac_g <- function(x) return(j_vals) | |
eval_jac_g_structure <- j_mask | |
constraint_lb <- bvec | |
constraint_ub <- rep( ub, n) | |
# initialize with the global unconstrained minimum, as done in quadprog package | |
# NOTE: This will only work if lb <= x0 <= ub. If this is not the case, | |
# use x0 = lb can be used instead. | |
x0 <- solve(Dmat, dvec) | |
# call the solver | |
sol <- ipoptr(x0 = x0, | |
eval_f = eval_f, | |
eval_grad_f = eval_grad_f, | |
eval_g = eval_g, | |
eval_jac_g = eval_jac_g, | |
eval_jac_g_structure = eval_jac_g_structure, | |
constraint_lb = constraint_lb, | |
constraint_ub = constraint_ub, | |
eval_h = eval_h, | |
eval_h_structure = eval_h_structure) | |
return(sol) | |
} |
Hi, Thanks for the implementation, but I have an error running it:
> error in ipoptr_qp(Dmat, dvec, t(Amat), bvec) : Function "make.sparse" not found
any idea?
Thanks
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Hello, thanks for this code. I have been trying to reproduce the solve.QP example from quadprog R library using ipoptr_qp, but I have not been success. These are the lines I have tested:
Do you have any hint to solve this?
Thanks in advance!