Hello!

I have the following non linear objective function. How can I convert this maximization objective function to a minimization problem?

I have read conflicting material online, some say to multiple the problem by -1 others say to multiply by the reciprocal.

Overall, I like the decision variable not to be in the denominator as well.

Represented in Julia as

```
@NLobjective(model, Max, sum(b_dict[r] * (p_dict[r] * l_star[r] / l_[r]) for r in od))
```

where `b_dict[r]`

, `p_dict[r]`

and `l_star[r]`

are lists of integers (representing demand, priority, and known arc length)

and `l_[r]`

is a decision variable defined as `@variable(model,l_[od] >= 0) `