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Solve a Convex Optimization Problem

Source: R/132_problems_problem.R
psolve.Rd

Solves the problem and returns the optimal objective value. After solving, variable values can be retrieved with value, constraint dual values with dual_value, and solver information with solver_stats.

Usage

psolve(
  problem,
  solver = NULL,
  gp = FALSE,
  qcp = FALSE,
  verbose = FALSE,
  warm_start = FALSE,
  feastol = NULL,
  reltol = NULL,
  abstol = NULL,
  num_iter = NULL,
  ...
)

Arguments

problem

A Problem object.

solver

Character string naming the solver to use (e.g., "CLARABEL", "SCS", "OSQP", "HIGHS"), or NULL for automatic selection.

gp

Logical; if TRUE, solve as a geometric program (DGP).

qcp

Logical; if TRUE, solve as a quasiconvex program (DQCP) via bisection. Only needed for non-DCP DQCP problems.

verbose

Logical; if TRUE, print solver output.

warm_start

Logical; if TRUE, use the current variable values as a warm-start point for the solver.

feastol

Numeric or NULL; feasibility tolerance. Mapped to the solver-specific parameter name (e.g., tol_feas for Clarabel, eps_prim_inf for OSQP). If NULL (default), the solver's own default is used.

reltol

Numeric or NULL; relative tolerance. Mapped to the solver-specific parameter name (e.g., tol_gap_rel for Clarabel, eps_rel for OSQP/SCS). If NULL (default), the solver's own default is used.

abstol

Numeric or NULL; absolute tolerance. Mapped to the solver-specific parameter name (e.g., tol_gap_abs for Clarabel, eps_abs for OSQP/SCS). If NULL (default), the solver's own default is used.

num_iter

Integer or NULL; maximum number of solver iterations. Mapped to the solver-specific parameter name (e.g., max_iter for Clarabel/OSQP, max_iters for SCS). If NULL (default), the solver's own default is used.

...

Additional solver-specific options passed directly to the solver. If a solver-native parameter name conflicts with a standard parameter (e.g., both feastol = 1e-3 and tol_feas = 1e-6 are given), the solver-native name in ... takes priority. For DQCP problems (qcp = TRUE), additional arguments include low, high, eps, max_iters, and max_iters_interval_search.

Value

The optimal objective value (numeric scalar), or Inf / -Inf for infeasible / unbounded problems.

See also

Problem, status, solver_stats, solver_default_param

Examples

x <- Variable()
prob <- Problem(Minimize(x), list(x >= 5))
result <- psolve(prob, solver = "CLARABEL")