1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
//!
//! Copyright : Copyright (c) MOSEK ApS, Denmark. All rights reserved.
//!
//! File : milo1.rs
//!
//! Purpose : Demonstrates how to solve a small mixed
//! integer linear optimization problem using the MOSEK Java API.
//!
extern crate mosek;
use mosek::{Task,Boundkey,Objsense,Streamtype,Solsta,Prosta,Soltype,Variabletype,Dparam};
fn main() -> Result<(),String> {
let numcon : i32 = 2;
let numvar : i32 = 2;
let infinity = 0.0; // only for symbolic purposes, value never used
let bkc = vec![Boundkey::UP, Boundkey::LO];
let blc = vec![ -infinity, -4.0 ];
let buc = vec![ 250.0, infinity ];
let bkx = vec![ Boundkey::LO, Boundkey::LO ];
let blx = vec![ 0.0, 0.0 ];
let bux = vec![ infinity, infinity ];
let c = vec![1.0, 0.64];
let asub = vec![0, 1,
0, 1];
let aval = vec![50.0, 3.0, 31.0, -2.0];
let ptrb : Vec<usize> = vec![ 0, 2 ];
let ptre : Vec<usize> = vec![ 2, 4 ];
/* Create the optimization task. */
Task::new().expect("Failed to create task")
.with_stream_callback(
Streamtype::LOG,
&mut |msg| print!("{}",msg),
|task| task.with_itg_sol_callback(
&mut |xx| { println!("Found a new solution = {:?}",xx); 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)?;
for ((((j,cj),bk),bl),bu) in (0..numvar).zip(c.iter()).zip(bkx.iter()).zip(blx.iter()).zip(bux.iter()) {
/* Set the linear term c_j in the objective.*/
task.put_c_j(j, *cj)?;
/* Set the bounds on variable j.
blx[j] <= x_j <= bux[j] */
task.put_var_bound(j, *bk, *bl, *bu)?;
/* Input column j of A */
task.put_a_col(j, /* Variable (column) index.*/
&asub[ptrb[j as usize]..ptre[j as usize]], /* Row index of non-zeros in column j.*/
&aval[ptrb[j as usize]..ptre[j as usize]])?; /* Non-zero Values of column j. */
}
// Set the bounds on constraints.
// for i=1, ...,numcon : blc[i] <= constraint i <= buc[i]
for (((i,bk),bl),bu) in (0..numcon).zip(bkc.iter()).zip(blc.iter()).zip(buc.iter()) {
task.put_con_bound(i, *bk, *bl, *bu)?;
}
/* Specify integer variables. */
for j in 0..numvar {
task.put_var_type(j, Variabletype::TYPE_INT)?;
}
/* Set max solution time */
task.put_dou_param(Dparam::MIO_MAX_TIME, 60.0)?;
/* A maximization problem */
task.put_obj_sense(Objsense::MAXIMIZE)?;
/* Solve the problem */
let _trm = task.optimize()?;
// Print a summary containing information
// about the solution for debugging purposes
task.solution_summary(Streamtype::MSG)?;
let mut xx = vec![0.0; numvar as usize];
task.get_xx(Soltype::ITG, xx.as_mut_slice())?;
/* Get status information about the solution */
match task.get_sol_sta(Soltype::ITG)? {
Solsta::INTEGER_OPTIMAL => {
println!("Optimal solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::PRIM_FEAS => {
println!("Feasible solution");
for (j,xj) in (0..numvar).zip(xx.iter()) {
println!("x[{}]: {}", j,xj);
}
}
Solsta::UNKNOWN => {
match task.get_pro_sta(Soltype::ITG)? {
Prosta::PRIM_INFEAS_OR_UNBOUNDED => {
println!("Problem status Infeasible or unbounded");
}
Prosta::PRIM_INFEAS => {
println!("Problem status Infeasible.");
}
Prosta::UNKNOWN => {
println!("Problem status unknown.");
}
_ => {
println!("Other problem status.");
}
}
}
_ => {
println!("Other solution status");
}
}
Ok(())
}))
}
#[cfg(test)]
mod tests {
#[test]
fn test() {
super::main().unwrap();
}
}