Package 'scip'

Print method for scip_control objects

Description

Print method for scip_control objects

Usage

## S3 method for class 'scip_control'
print(x, ...)

Arguments

x	A scip_control object.
...	Ignored.

Value

Invisible x.

---

Add an indicator constraint to a SCIP model

Description

If binvar = 1 then sum(coefs * x[vars]) <= rhs.

Usage

scip_add_indicator_cons(model, binvar, vars, coefs, rhs, name = NULL)

Arguments

model	A SCIP model.
binvar	Integer; 1-based index of the binary indicator variable.
vars	Integer vector; 1-based variable indices.
coefs	Numeric vector; coefficients.
rhs	Numeric; right-hand side.
name	Character; constraint name.

Value

Integer; 1-based constraint index.

---

Add a linear constraint to a SCIP model

Description

Adds lhs <= sum(coefs * x[vars]) <= rhs.

Usage

scip_add_linear_cons(model, vars, coefs, lhs = -Inf, rhs = Inf, name = NULL)

Arguments

model	A SCIP model.
vars	Integer vector; 1-based variable indices.
coefs	Numeric vector; coefficients (same length as vars).
lhs	Numeric; left-hand side. Default -Inf.
rhs	Numeric; right-hand side. Default Inf.
name	Character; constraint name. Default auto-generated.

Value

Integer; 1-based constraint index.

---

Add a quadratic constraint to a SCIP model

Description

Adds lhs <= linexpr + quadexpr <= rhs where quadexpr = sum(quadcoefs[k] * x[quadvars1[k]] * x[quadvars2[k]]).

Usage

scip_add_quadratic_cons(
  model,
  linvars = integer(0),
  lincoefs = double(0),
  quadvars1 = integer(0),
  quadvars2 = integer(0),
  quadcoefs = double(0),
  lhs = -Inf,
  rhs = Inf,
  name = NULL
)

Arguments

model	A SCIP model.
linvars	Integer vector; 1-based variable indices for linear part.
lincoefs	Numeric vector; linear coefficients.
quadvars1, quadvars2	Integer vectors; 1-based variable indices for quadratic terms.
quadcoefs	Numeric vector; quadratic coefficients.
lhs, rhs	Numeric; constraint bounds.
name	Character; constraint name.

Value

Integer; 1-based constraint index.

---

Add a SOS1 constraint to a SCIP model

Description

At most one variable in the set can be nonzero.

Usage

scip_add_sos1_cons(model, vars, weights = NULL, name = NULL)

Arguments

model	A SCIP model.
vars	Integer vector; 1-based variable indices.
weights	Numeric vector; weights determining branching order.
name	Character; constraint name.

Value

Integer; 1-based constraint index.

---

Add a SOS2 constraint to a SCIP model

Description

At most two adjacent variables in the set can be nonzero.

Usage

scip_add_sos2_cons(model, vars, weights = NULL, name = NULL)

Arguments

model	A SCIP model.
vars	Integer vector; 1-based variable indices.
weights	Numeric vector; weights determining adjacency order.
name	Character; constraint name.

Value

Integer; 1-based constraint index.

---

Add a variable to a SCIP model

Description

Add a variable to a SCIP model

Usage

scip_add_var(model, obj, lb = 0, ub = Inf, vtype = "C", name = NULL)

Arguments

model	A SCIP model (external pointer from scip_model).
obj	Numeric; objective coefficient.
lb	Numeric; lower bound. Default 0.
ub	Numeric; upper bound. Default Inf.
vtype	Character; variable type: "C" (continuous), "B" (binary), or "I" (integer). Default "C".
name	Character; variable name. Default auto-generated.

Value

Integer; 1-based variable index.

---

Add multiple variables to a SCIP model

Description

Add multiple variables to a SCIP model

Usage

scip_add_vars(model, obj, lb = 0, ub = Inf, vtype = "C", names = NULL)

Arguments

model	A SCIP model.
obj	Numeric vector; objective coefficients.
lb	Numeric; lower bounds (scalar or vector). Default 0.
ub	Numeric; upper bounds (scalar or vector). Default Inf.
vtype	Character; variable types (scalar or vector). Default "C".
names	Character vector; variable names. Default auto-generated.

Value

Integer; 1-based index of first variable added.

---

SCIP solver control parameters

Description

Create a list of control parameters for the SCIP solver. Parameters are organized into logical groups: output, limits, tolerances, presolving, LP, branching, and heuristics. Any SCIP parameter can also be set directly using its native path via ....

Usage

scip_control(
  verbose = TRUE,
  verbosity_level = 3L,
  display_freq = 100L,
  time_limit = Inf,
  node_limit = -1L,
  stall_node_limit = -1L,
  sol_limit = -1L,
  best_sol_limit = -1L,
  mem_limit = Inf,
  restart_limit = -1L,
  gap_limit = 0,
  abs_gap_limit = 0,
  feastol = 1e-06,
  dualfeastol = 1e-07,
  epsilon = 1e-09,
  presolving = TRUE,
  presolve_rounds = -1L,
  lp_threads = 1L,
  lp_iteration_limit = -1L,
  lp_scaling = TRUE,
  branching_score = "p",
  heuristics_emphasis = "default",
  threads = 1L,
  ...
)

Arguments

verbose	Logical; print solver output. Default TRUE.
verbosity_level	Integer 0–5; verbosity detail. Default 3.
display_freq	Integer; node display frequency. Default 100.
time_limit	Numeric; time limit in seconds. Default Inf.
node_limit	Integer; max nodes. Default -1L.
stall_node_limit	Integer; stall nodes. Default -1L.
sol_limit	Integer; solution limit. Default -1L.
best_sol_limit	Integer; improving solution limit. Default -1L.
mem_limit	Numeric; memory limit in MB. Default Inf.
restart_limit	Integer; restart limit. Default -1L.
gap_limit	Numeric; relative MIP gap. Default 0.
abs_gap_limit	Numeric; absolute gap. Default 0.
feastol	Numeric; feasibility tolerance. Default 1e-6.
dualfeastol	Numeric; dual feasibility tolerance. Default 1e-7.
epsilon	Numeric; zero tolerance. Default 1e-9.
presolving	Logical; enable presolving. Default TRUE.
presolve_rounds	Integer; presolve rounds. Default -1L.
lp_threads	Integer; LP solver threads. Default 1L.
lp_iteration_limit	Integer; LP iteration limit. Default -1L.
lp_scaling	Logical; LP scaling. Default TRUE.
branching_score	Character; score function. Default "p".
heuristics_emphasis	Character; heuristic emphasis. Default "default".
threads	Integer; parallel solving threads. Default 1L. See Parallel section for caveats.
...	Additional SCIP parameters as name-value pairs, using SCIP's native hierarchical parameter paths (e.g., "lp/fastmip" = 1, "conflict/enable" = FALSE). See the SCIP parameter documentation for the full list.

Value

A named list of class "scip_control" with components:

verbose

Logical; verbosity flag.

scip_params

Named list; all parameters as SCIP native paths.

Output

verbose

Logical; print solver output. Default TRUE.

verbosity_level

Integer 0–5; verbosity detail (0 = none, 3 = normal, 5 = full). Default 3. Ignored if verbose = FALSE.

display_freq

Integer; display a status line every this many nodes (-1 = never). Default 100.

Termination Limits

time_limit

Numeric; maximum solving time in seconds. Default Inf (no limit).

node_limit

Integer; maximum number of branch-and-bound nodes. Default -1L (no limit).

stall_node_limit

Integer; nodes without improvement before stopping. Default -1L (no limit).

sol_limit

Integer; stop after finding this many feasible solutions. Default -1L (no limit).

best_sol_limit

Integer; stop after this many improving solutions. Default -1L (no limit).

mem_limit

Numeric; memory limit in MB. Default Inf (no limit).

restart_limit

Integer; maximum restarts. Default -1L (no limit).

Tolerances

gap_limit

Numeric; relative MIP gap tolerance; solver stops when the gap falls below this value. Default 0 (prove optimality).

abs_gap_limit

Numeric; absolute gap between primal and dual bound. Default 0.

feastol

Numeric; feasibility tolerance for LP constraints. Default 1e-6.

dualfeastol

Numeric; dual feasibility tolerance. Default 1e-7.

epsilon

Numeric; absolute values below this are treated as zero. Default 1e-9.

Presolving

presolving

Logical; enable presolving. Default TRUE.

presolve_rounds

Integer; maximum presolving rounds (-1 = unlimited). Default -1L.

LP

lp_threads

Integer; number of threads for LP solver. Default 1L.

lp_iteration_limit

Integer; LP iteration limit per solve (-1 = no limit). Default -1L.

lp_scaling

Logical; enable LP scaling. Default TRUE.

Branching

branching_score

Character; branching score function: "s" (sum), "p" (product), "q" (quotient). Default "p".

Heuristics

heuristics_emphasis

Character; heuristic emphasis setting: "default", "aggressive", "fast", or "off". Default "default".

Parallel

threads

Integer; number of threads for concurrent solving. Default 1L. Note: concurrent solving may require a SCIP build compiled with parallel support (e.g., PARASCIP=true); not all installations provide this.

See Also

scip_solve, scip_set_param

Examples

## Quick solve with 60-second time limit
ctrl <- scip_control(time_limit = 60)

## Quiet solve with 1% gap tolerance
ctrl <- scip_control(verbose = FALSE, gap_limit = 0.01)

## Aggressive heuristics, no presolving
ctrl <- scip_control(heuristics_emphasis = "aggressive", presolving = FALSE)

## Pass a native SCIP parameter directly
ctrl <- scip_control("conflict/enable" = FALSE, "separating/maxrounds" = 5L)

---

Get solver information

Description

Get solver information

Usage

scip_get_info(model)

Arguments

model

A SCIP model (after scip_optimize).

Value

A list with solve_time, nodes, iterations, gap, sol_count.

---

Get number of solutions found

Description

Get number of solutions found

Usage

scip_get_nsols(model)

Arguments

model

A SCIP model (after scip_optimize).

Value

Integer.

---

Get objective value of best solution

Description

Get objective value of best solution

Usage

scip_get_objval(model)

Arguments

model

A SCIP model (after scip_optimize).

Value

Numeric; objective value, or NA if no solution.

---

Get the k-th solution from the solution pool

Description

Get the k-th solution from the solution pool

Usage

scip_get_sol(model, k)

Arguments

model	A SCIP model.
k	Integer; 1-based solution index (1 = best).

Value

A list with objval and x.

---

Get the best solution

Description

Get the best solution

Usage

scip_get_solution(model)

Arguments

model

A SCIP model (after scip_optimize).

Value

A list with objval and x.

---

Get solver status

Description

Get solver status

Usage

scip_get_status(model)

Arguments

model

A SCIP model (after scip_optimize).

Value

Character; status string (e.g., "optimal", "infeasible").

---

Create a SCIP model

Description

Creates a new SCIP optimization model for incremental problem construction.

Usage

scip_model(name = "scip_model")

Arguments

name	Character; problem name. Default "scip_model".

Value

An external pointer representing the SCIP model.

---

Free a SCIP model

Description

Explicitly frees the SCIP model and all associated memory. The model is also freed automatically when garbage collected.

Usage

scip_model_free(model)

Arguments

model

A SCIP model.

Value

Invisible NULL.

---

Solve a SCIP model

Description

Solve a SCIP model

Usage

scip_optimize(model)

Arguments

model

A SCIP model.

Value

Invisible NULL. Use scip_get_status and scip_get_solution to retrieve results.

---

Set objective sense

Description

Set objective sense

Usage

scip_set_objective_sense(model, sense = "minimize")

Arguments

model	A SCIP model.
sense	Character; "minimize" (default) or "maximize".

Value

Invisible NULL.

---

Set a SCIP parameter

Description

Set a SCIP parameter

Usage

scip_set_param(model, name, value)

Arguments

model	A SCIP model.
name	Character; SCIP parameter name (e.g., "limits/time").
value	The parameter value (type is auto-detected by SCIP).

Value

Invisible NULL.

---

Solve a linear or mixed-integer program using SCIP

Description

One-shot interface to the SCIP solver. Formulates and solves:

$\min_{x} \; obj' x$

subject to constraint rows defined by A, b, sense, with variable types vtype and bounds lb, ub.

Usage

scip_solve(obj, A, b, sense, vtype = "C", lb = 0, ub = Inf, control = list())

Arguments

obj	Numeric vector of length n; objective coefficients.
A	Constraint matrix (m x n). Can be a dense matrix, dgCMatrix, or simple_triplet_matrix.
b	Numeric vector of length m; constraint right-hand side.
sense	Character vector of length m; constraint sense. Each element must be "<=", ">=", or "==".
vtype	Character; variable types. Either a single value applied to all variables, or a vector of length n. Values: "C" (continuous), "B" (binary), "I" (integer). Default "C".
lb	Numeric; lower bounds for variables. Single value or vector of length n. Default 0.
ub	Numeric; upper bounds for variables. Single value or vector of length n. Default Inf.
control	A list of solver parameters, typically from scip_control.

Value

A named list with components:

status

Character; solver status (e.g., "optimal", "infeasible", "unbounded").

objval

Numeric; optimal objective value (or NA if no solution).

x

Numeric vector; primal solution (or NULL if no solution).

sol_count

Integer; number of solutions found.

gap

Numeric; relative optimality gap.

info

List with additional solver information (solve_time, iterations, nodes).

---