# How to model two exponential cones >= a specific value with JuMP?

The model is as follow:
obj: min aexp(b)+cexp(d)
subject to: 1<=a<=2
1<=b<=2
0.5<=c<=2
0.5<=d<=2
aexp(b)+cexp(d)>=0.5 I see the exponential cones in Jump’s example is smaller than one specific value. Is there an idea to model the proposed problem?

With SCS you need a conic formulation so you need to use the `ExponentialCone`.
You see in the doc that `(x, y, z)` is in the cone iff `y exp(x / y) <= z` and `y > 0`.
So for instance `exp(a) <= b` is rewritten as `[a, 1, b] in ExponentialCone()`.
It’s not clear to me how to reformulate your model into a conic program though.
It does not even clear that the problem is convex.
For instance, in `0.5 <= a * exp(b) + c * exp(d)`, for the problem to be convex, you would need `a * exp(b)` to be concave in `a` and `b` while it is convex in the direction `b`.
If you replace `@objective` with `@NLobjective` and `@constraint` by `@NLconstraint`, you can use a nonlinear solver like Ipopt or NLopt.

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