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//!
//! Copyright : Copyright (c) MOSEK ApS, Denmark. All rights reserved.
//!
//! File : ceo1.rs
//!
//! Description:
//! Demonstrates how to solve a small conic exponential
//! optimization problem using the MOSEK API.
//!
//! Min x1 + x2
//! Such that
//! x1 + x2 + x3 = 1.0
//! |1 | |x1|
//! | 1 | x |x2| in K_exp
//! | 1| |x3|
//! x1,x2,x3 are free
//!
extern crate mosek;
use mosek::{Task,Boundkey,Objsense,Streamtype,Solsta,Soltype};
const INF : f64 = 0.0;
fn main() -> Result<(),String> {
let numcon = 1;
let numvar = 3;
let bkc = mosek::Boundkey::FX;
let blc = 1.0;
let buc = 1.0;
let bkx = vec![ Boundkey::FR,
Boundkey::FR,
Boundkey::FR ];
let blx = vec![ -INF, -INF, -INF ];
let bux = vec![ INF, INF, INF ];
let c = vec![ 1.0, 1.0, 0.0 ];
let a = vec![ 1.0, 1.0, 1.0 ];
let asub = vec![0, 1, 2];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut|msg| print!("{}",msg),
|task| task.with_callback(
&mut |caller| { println!("caller = {}",caller); false },
|task| {
/* Append 'numcon' empty constraints.
The constraints will initially have no bounds. */
task.append_cons(numcon)?;
/* Append 'numvar' variables.
The variables will initially be fixed at zero (x=0). */
task.append_vars(numvar)?;
/* Define the linear part of the problem */
task.put_c_slice(0, numvar, c.as_slice())?;
task.put_a_row(0, asub.as_slice(), a.as_slice())?;
task.put_con_bound(0, bkc, blc, buc)?;
task.put_var_bound_slice(0, numvar, bkx.as_slice(), blx.as_slice(), bux.as_slice())?;
/* Add a conic constraint */
task.append_afes(3)?;
let afeidxs = vec![0, 1, 2 ];
let b = vec![0.0,0.0,0.0];
let domidx = task.append_primal_exp_cone_domain()?;
task.put_afe_f_row_list(afeidxs.as_slice(),
vec![1,1,1].as_slice(),
vec![0,1,2].as_slice(),
vec![0,1,2].as_slice(),
vec![1.0,1.0,1.0].as_slice())?;
task.append_acc(domidx,afeidxs.as_slice(),b.as_slice())?;
task.put_obj_sense(Objsense::MINIMIZE)?;
println!("optimize");
/* Solve the problem */
task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
/* Get status information about the solution */
let solsta = task.get_sol_sta(Soltype::ITR)?;
assert!(solsta == Solsta::OPTIMAL);
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITR, & mut xx[..])?;
println!("Optimal primal solution");
for j in 0..numvar as usize {
println!("x[{}]: {:.4}",j,xx[j]);
}
Ok(())
}))
}
#[cfg(test)]
mod tests {
#[test]
fn test() {
super::main().unwrap();
}
}