**“Of two variables x and y, exactly one should be positive”**: how to model this constraint? This is a stricter condition that in the previous Tip #1.

For the new MP Library-based drivers (e.g., gurobi, highs, cbc, copt, xpress), as well as for Constraint Programming solvers (ilogcp, gecode, jacop), this goes via AMPL logical operators:

`x > 0 <==> y <= 0`

We can ask what `x > 0`

means for non-integer variables. It will be replaced by a non-strict inequality with a small tolerance: `x >= eps`

.

If a specific “gap” is desired, for example if we want to exclude numbers in the interval (0, 3), use a disjunctive normal form (DNF):

`(x <= 0 and y >= 3) or (x >= 3 and y <= 0)`

#### Small complete examples:

- With MP, using the
`<==>`

operator:

```
var x >= -1000 <= 1000;
var y >= -1000 <= 1000;
minimize total: 5 * x + 2 * y;
s.t. exactly_one_positive: x > 0 <==> y <= 0;
```

- With MP, using DNF to exclude a gap interval:

```
var x >= -1000 <= 1000;
var y >= -1000 <= 1000;
minimize total: 5 * x + 2 * y;
s.t. exactly_one_positive_with_gap:
(x <= 0 and y >= 3) or (x >= 3 and y <= 0);
```

- Without MP you would need to linearize the logic using big-M:

```
var x >= -1000 <= 1000;
var y >= -1000 <= 1000;
var b binary;
minimize total: 5 * x + 2 * y;
s.t. big_m_1_x: x <= b * 1000;
s.t. big_m_1_y: y >= 3 - b * 1003;
s.t. big_m_2_x: x >= -1000 + b * 1003;
s.t. big_m_2_y: y <= (1-b) * 1000;
```

Solving the first model with an MP driver produces the following:

```
ampl: option solver copt; solve; display x, y, total;
x-COPT 5.0.1: optimal solution; objective -4999.9998
x = -1000
y = 0.0001
total = -5000
```

Solving the 2nd or 3rd model above produces the following:

```
ampl: option solver highs; solve; display x, y, total;
HiGHS 1.4.0: optimal solution; objective -4994
0 branching nodes
x = -1000
y = 3
total = -4994
```

More examples and documentation are in the MP Modeling Guide.