Unanswered Questions
46 questions with no upvoted or accepted answers
3
votes
0
answers
235
views
Solving a nonlinear model with constraints of exponential functions and continuous variable multiplications
I have a nonlinearly-constrained model and wonder if a nonlinear solver like Ipopt or Knitro can solve the problem.
Briefly, my objective function is linear. I have the following variables with their ...
- 1,249
3
votes
0
answers
73
views
Optimizing with a logistic function
I have a system in which I want to maximize the value of some function $f(x_T, y_T)$.
The time evolution of the system is described by some functions:
$$
\begin{align}
\frac{dx}{dt}&=\alpha \frac{...
- 543
3
votes
0
answers
62
views
Linearisation using SOS2
I am trying to linearise the following expresssion.
$C(k) = B(k) e^{-d(k)}, B(k) \ge 0 , d(k) \ge 0 $
I am trying to do this by using SOS2 sets.
I set $X(k) = e^{-d(k)}$ and I get $C(k) = B(k) X(...
- 2,252
2
votes
0
answers
63
views
Special Case of Minimum Cost Flow Problem with Variable Cost
I am working on an optimization problem similar to MCF with variable cost, but with an adjustment in the objective function. The cost function $f$ to minimize that is continuous, piece-wise linear and ...
- 59
2
votes
0
answers
98
views
log-log regression as reward function in optimization problem
Consider the model $\hat{y}_t = e^{\text{trend} + \text{seasonality}} \prod_k^K x_{k, t}^{b_k}$
where $K$ denotes different investment alternatives. You can think that trend and seasonality are ...
- 21
2
votes
0
answers
92
views
Branching the product of binary and continuous variable in Gurobi
I have a binary variable (X) multiplying a continuous variable (Y). I know I can linearize by adding an auxiliary variable (I have that model working), but I now want to do my own branching in the ...
- 517
2
votes
0
answers
65
views
Minimizing sum of similar functions with a dependence
Consider an objective function in the form of minimization of maximization that is the sum of $N$ similar functions $f\left(x\right)\ge 0$, $\ \forall x$. The summation of all variables is constant (e....
- 5,874
2
votes
0
answers
318
views
Solving minimax problems with Gurobi
I want to solve a problem of the form $\min_x\max_y f(x,y)$ using Gurobi, where $x,y\in [0,1]$.
Is there a simple way to model this in Gurobi? I've seen examples where the domain of $y$ is finite, but ...
- 5,442
2
votes
0
answers
100
views
Two-stage stochastic with non-linear recourse
I am working on a two-stage facility location problem as I described in this question.
I am solving it with the L-shaped method (Benders decomposition). The cost value between each $(i,j)$ is a ...
- 5,442
2
votes
0
answers
308
views
Gurobi is unable to give an optimal solution even when it exists
I am trying to solve Logarithmic Fuzzy Preference Programming (LFPP) for criteria weight evaluation, based on fuzzy comparisons between criteria, and I am solving it with Gurobi in Python 2.7. It is a ...
- 1,895
1
vote
0
answers
87
views
volume-weighted mean equality constraints
I have the following optimization objective function for a dynamic pricing problem:
\begin{align*}
sum\_profit = \sum_{i \in sales\_point} \Bigg( constant[i] + {elasticity[i]} \cdot (movement[i] + ...
- 133
1
vote
0
answers
101
views
Converting a Linear Program with TU Constraint Matrix to a Nonlinear Convex Model: Solver Performance?
I'm currently working on a large Mixed Integer Program (MIP) where the constraint matrix is Totally Unimodular (TU), allowing me to model it as a Linear Program (LP) for efficiency, as total ...
- 33.1k
1
vote
0
answers
94
views
Numerical infeasibility for moving numbers along some specific conversion edges to get maximal number on target node from some starter node
I have a problem that can be represented as an optimization problem.
Sometimes, solver engines report infeasible depending on the parameters I have at hand.
The root cause is numeric ranges.
...
- 111
1
vote
1
answer
124
views
Maximizing sum of probabilities with variable distributions
Suppose $\\{X_i\\}$ are binary decision variables and $\\{A_j\\}$ are Skellam random variables with $(\mu_1, \mu_2) = (\sum_i b_{i} X_i, c_j)$. Here, $b_i, c_j \in \mathbb{R}^{\geq 0}$ are constants. ...
CommunityBot
- 1
1
vote
0
answers
28
views
Steepest ascent vector at a point of a constrained nonlinear problem
I'm looking at this article:
"Packing unequal circles into a strip of minimal length with a jump algorithm" (Stoyan et Yaskov, 2014) DOI
In section 5, a nonlinear constrained model is ...
- 2,623