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5 votes
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Which MiniZinc-compatible solvers are best suited for floating decision variables and non-linear constraints?

Some of the coin-or open-source solvers like "couenne" can be used via MiniZn. You can follow the instruction of installation in this link. Info about Couenne: Couenne (Convex Over and Under ...
Oguz Toragay's user avatar
  • 8,667
4 votes
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Can we use continuous variables instead of binary variables in this NLP problem?

Yes, binaries can be replaced by NLP using continuous variables. But it's not necessarily a good idea, and is usually is a bad idea. If it were a good idea, there probably wouldn't be MINLP solvers. ...
Mark L. Stone's user avatar
4 votes

Can we use continuous variables instead of binary variables in this NLP problem?

You can relax integrality of $a_{i2}.$ Due to the "big M" constraints, I do not believe you can relax integrality of the other binary variables. It's a bit hard to be sure, since you did not ...
prubin's user avatar
  • 39.5k
4 votes

Which MiniZinc-compatible solvers are best suited for floating decision variables and non-linear constraints?

Of the constraint based solvers JaCoP (https://github.com/radsz/jacop ) and Gecode (https://www.gecode.org/) has support for float decision variables combined with nonlinear constraints. Choco (https:/...
hakank's user avatar
  • 934
3 votes
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Convex optimization on the unit hypercube with gradients and a bounded minimum

From the looks of it (simple feasible set, convex objective, gradient available), Frank-Wolfe indeed makes a lot of sense here. I can point out that there exist many variants of the algorithm, and ...
mtanneau's user avatar
  • 4,183
3 votes
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Continuous water-filling optimization problem

Using Calculus of Variations as an inspiration we have the lagrangian $$ \mathcal{L}(f,\lambda) = \int_0^{x_{max}}\left(-\ln\left(\alpha(x)+f(x)\right)+\lambda\left(f(x)-\frac{1}{x_{max}}\right)\right)...
Cesareo's user avatar
  • 146
3 votes

Continuous water-filling optimization problem

I can't tell if your path is right (because it depends on that you want to do), but it is sensible. Your problem structure is quite similar to one occurring in the field of optimal control. I'm not ...
worldsmithhelper's user avatar
3 votes

Maximization of a differentiable and nonlinear function over a bounded space

The KKT conditions are necessary conditions for an optimum to your problem, so if you can find all feasible points satisfying them, the one with the best objective function will be your optimum. There ...
prubin's user avatar
  • 39.5k
2 votes

LPs having a 'stable' objective value wrt changes in the constraint right-hand sides

The property that some infinitesimal change in one of the constraints impacts the objective is called "a constraint being active" or "a constraint being in conflict with the objective&...
worldsmithhelper's user avatar
2 votes

Convex optimization on the unit hypercube with gradients and a bounded minimum

I hesitate to suggest it, since gradient methods tend to be faster than non-gradient methods, but the Nelder-Mead "simplex" algorithm is easy to code and might be worth a try.
prubin's user avatar
  • 39.5k
2 votes

Convex optimization on the unit hypercube with gradients and a bounded minimum

When you have only box constraints I don't think Frank Wofle is very efficient. Frank Wolfe can handle more complex constraints. You should try a quasi newton algorithm like l-bfgs-b or a truncated ...
Taw's user avatar
  • 121
2 votes

Armijo Line Search Parameters

You are correct that the optimal choice of parameters for the Armijo line search can vary depending on the problem and the optimization algorithm being used. In practice, there are several common ...
1137h4xor's user avatar
  • 194
2 votes

Assignment Problem with continuous decision variable

Is there even a possibility that the mathematical optimal solution is a continuous value I would say it depends on the parameterization, i.e., the values of c and t and b in your problem. From your ...
Tim Varelmann's user avatar
1 vote

Requesting references about recursive functions where the variables are continuous

If the intent is to optimize $f_N(y)$ for some fixed $N,$ it might be a form of dynamic programming.
prubin's user avatar
  • 39.5k
1 vote

Represent the minimum between two terms as a continuous constraint

As far as i know you will have to resort to a bi-level optimzation problem: $\min_{A,B} x $ subject to ($\max_x$ subject to $x\leq A$ $x \leq B$) solve a series of non linear problems where you ...
worldsmithhelper's user avatar

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