R HIGHS Interface

remotes::install_gitlab("roigrp/solver/highs")

library("highs")

args(highs_solve)
#> function (Q = NULL, L, lower, upper, A, lhs, rhs, types, maximum = FALSE, 
#>     offset = 0, control = list(), dry_run = FALSE) 
#> NULL

# Minimize
#  x_0 +  x_1 + 3
# Subject to
#                 x_1 <= 7
#  5 <=   x_0 + 2 x_1 <= 15
#  6 <= 3 x_0 + 2 x_1
#  0 <=   x_0         <= 4
#  1 <=           x_1
A <- rbind(c(0, 1), c(1, 2), c(3, 2))
s <- highs_solve(L = c(1.0, 1), lower = c(0, 1), upper = c(4, Inf),
                 A = A, lhs = c(-Inf, 5, 6), rhs = c(7, 15, Inf),
                 offset = 3)
str(s)
#> List of 6
#>  $ primal_solution: num [1:2] 0.5 2.25
#>  $ objective_value: num 5.75
#>  $ status         : int 7
#>  $ status_message : chr "Optimal"
#>  $ solver_msg     :List of 6
#>   ..$ value_valid: logi TRUE
#>   ..$ dual_valid : logi TRUE
#>   ..$ col_value  : num [1:2] 0.5 2.25
#>   ..$ col_dual   : num [1:2] 0 0
#>   ..$ row_value  : num [1:3] 2.25 5 6
#>   ..$ row_dual   : num [1:3] 0 0.25 0.25
#>  $ info           :List of 18
#>   ..$ valid                     : logi TRUE
#>   ..$ mip_node_count            : num -1
#>   ..$ simplex_iteration_count   : int 2
#>   ..$ ipm_iteration_count       : int 0
#>   ..$ qp_iteration_count        : int 0
#>   ..$ crossover_iteration_count : int 0
#>   ..$ primal_solution_status    : chr "Feasible"
#>   ..$ dual_solution_status      : chr "Feasible"
#>   ..$ basis_validity            : int 1
#>   ..$ objective_function_value  : num 5.75
#>   ..$ mip_dual_bound            : num 0
#>   ..$ mip_gap                   : num Inf
#>   ..$ num_primal_infeasibilities: int 0
#>   ..$ max_primal_infeasibility  : num 0
#>   ..$ sum_primal_infeasibilities: num 0
#>   ..$ num_dual_infeasibilities  : int 0
#>   ..$ max_dual_infeasibility    : num 0
#>   ..$ sum_dual_infeasibilities  : num 0

# Minimize
#  0.5 x^2 - 2 x + y
# Subject to
#  x <= 3
zero <- .Machine$double.eps * 100
Q <- rbind(c(1, 0), c(0, zero))
L <- c(-2, 1)
A <- t(c(1, 0))

cntrl <- list(log_dev_level = 0L)
s <- highs_solve(Q = Q, L = L, A = A, lhs = 0, rhs = 3, control = cntrl)
str(s)
#> List of 6
#>  $ primal_solution: num [1:2] 2e+00 -1e+07
#>  $ objective_value: num -1e+07
#>  $ status         : int 7
#>  $ status_message : chr "Optimal"
#>  $ solver_msg     :List of 6
#>   ..$ value_valid: logi TRUE
#>   ..$ dual_valid : logi TRUE
#>   ..$ col_value  : num [1:2] 2e+00 -1e+07
#>   ..$ col_dual   : num [1:2] 0 0
#>   ..$ row_value  : num 2
#>   ..$ row_dual   : num 0
#>  $ info           :List of 18
#>   ..$ valid                     : logi TRUE
#>   ..$ mip_node_count            : num -1
#>   ..$ simplex_iteration_count   : int 0
#>   ..$ ipm_iteration_count       : int 0
#>   ..$ qp_iteration_count        : int 5
#>   ..$ crossover_iteration_count : int 0
#>   ..$ primal_solution_status    : chr "Feasible"
#>   ..$ dual_solution_status      : chr "Feasible"
#>   ..$ basis_validity            : int 0
#>   ..$ objective_function_value  : num -1e+07
#>   ..$ mip_dual_bound            : num 0
#>   ..$ mip_gap                   : num Inf
#>   ..$ num_primal_infeasibilities: int 0
#>   ..$ max_primal_infeasibility  : num 0
#>   ..$ sum_primal_infeasibilities: num 0
#>   ..$ num_dual_infeasibilities  : int 0
#>   ..$ max_dual_infeasibility    : num 0
#>   ..$ sum_dual_infeasibilities  : num 0

d <- highs_available_solver_options()
d[["option"]] <- sprintf("`%s`", d[["option"]])
knitr::kable(d, row.names = FALSE)