Questions tagged [nonconvex-programming]
For questions about non-convex optimization problems where the objective or any of the constraints are non-convex.
20
questions
3
votes
0answers
19 views
Local optimum of dual of non-linear program
In general, suppose you have a non-convex optimization problem with constraints and you form the dual problem. If you find a local optimum for the dual problem, will the corresponding primal solution ...
4
votes
1answer
48 views
Maximizing 1-norm: using binary variables to relax non-convexity
It is well-known that when we maximize a 1-norm, e.g., $\|Ax\|_1$, we can use binary variables and obtain a mixed-integer convex problem (otherwise maximizing 1-norm is non-convex). I am mentioning ...
3
votes
0answers
112 views
SDP relaxation with greater-than and less-than inequalities at the same time
I am dealing with the following nonconvex fractional quadratic optimization problem
\begin{align}
& \min_{\boldsymbol{x}} && \max_{t \in \mathcal{T}} \frac{\boldsymbol{a}_t^T \boldsymbol{...
3
votes
1answer
64 views
Supported pyomo free solvers for (non-convex) quadratic programming
Any one had the chance to use pyomo with free/open-source solvers that handle quadratic optimization problems, which they could be convex or not, but preferably as general as possible.
3
votes
1answer
131 views
Approximation methods for a mixed integer convex optimization problem
I have a convex objective function, e.g., minimizing the negative entropy function. My constraints are also linear. The only issue is that I also have binary variables.
I am currently aware of AIMMS'...
4
votes
1answer
79 views
Minimize a convex function over a sphere
Problem description
Let $\mathcal{C} = \{X \in \mathbb{R}^n \mid g(X) \leq 0\}$ with $g(X)$ a convex function. Suppose I need to solve the feasibility problem, for a given $r>0$
$$ \exists ^?X \...
3
votes
0answers
56 views
Strong Duality and Slater Condition
I am studying the Duality Chapter of Convex Optimization by Boyd. Is it possible that strong duality holds for non-convex optimization? If yes, is there any specific condition? And, what is the ...
4
votes
1answer
67 views
Dealing with a non-convex problem
I have the following objective function. The variables: $h_p$, $e_{trs}\left(h_p\right), w_{trs}\left(h_p\right)$ are all non-negative continuous. $T,R,S,\pi_{trs}$ are polynomially-sized sets. All ...
6
votes
1answer
112 views
Linearizing the square root of binary summations
My question is similar to this one and almost identical with this. I am so confused due to indexing and could not make sure if I could apply the solution in here to this indexed version as shown below....
6
votes
1answer
53 views
Linearizing the square root of two binary summations
My question is similar to this one though a bit more complicated. Though my question also includes indices, I am removing them to ease readability.
Let binary variables $x,y\in\{0,1\}$, non-negative ...
13
votes
2answers
918 views
Is This Constraint Convex?
I have a constraint that I believe to be convex and not affine which I think means that I can implement a relaxation. I will first define the full constraint, and then build up my (informal) reasoning ...
11
votes
1answer
399 views
Solvers and saddle points
It seems like most solvers that can tackle nonlinear nonconvex optimization problems (e.g. IPOPT) operate on ultimately solving for the first-order optimality conditions. Can it therefore be assumed ...
9
votes
3answers
464 views
Examples of problems with non-convex constraint functions but convex feasible region
I'm looking for examples of (classes of) problems with a non-convex, non-linear formulation, but convex feasible region.
That is, a problem of the sort:
$$
\begin{array}{lll}
\text{minimize} & ...
15
votes
1answer
359 views
IPOPT with HSL vs MUMPS
What are the advantages (if any) of using IPOPT with HSL vs MUMPS? HSL has a reputation of being faster, but does it walk the walk? In particular, does HSL scale better for large-scale problems?
We ...
11
votes
0answers
117 views
Characterizing the solution of a (non) linear maximization program
I have the following maximization program
\begin{align}
\max\limits_{\{q_i\}}&\quad\sum\limits_{i=1}^nq_i \\
\text{s.t.}&\quad\begin{cases} k_j \geq \sum\limits_{i=1}^n q_i^{1 \over \...
9
votes
1answer
131 views
Rules of thumb for using classic methods (e.g. branch and bound) vs. meta-heuristics (G.A, S.A, etc..) for non-convex problems?
Are there any rules of thumb for when to use classical methods like branch and bound, branch and cut, etc...for non-convex problems, vs using meta-heuristic methods like genetic algorithms, ...
14
votes
1answer
228 views
Convexity of Variance Minimization
$X$ is a discrete random variable taking value $x_n$ with probability $1/N$ for $n=1,
\ldots,N$. I would like to set the $x_n$ values in an optimization problem. My objective is to minimize the ...
12
votes
2answers
215 views
Convex vs Strictly Quasiconvex Functions in Optimization
I have read/heard quite a few time that in the old days, it was considered that linear programs constitute the class of optimization problems that can be solved efficiently in practice (as a rule of ...
14
votes
1answer
418 views
How to formulate a problem to prove/disprove convexity?
Given a general non-linear problem:
\begin{align}P:\qquad&\min_{x\in X} f(x)\\\text{s.t.}\qquad&g(x)\leq 0\end{align}
where $f$ is a non-linear function, $g$ is a vector of non-linear ...
10
votes
2answers
133 views
Global optimality condition of non-convex quadratic programs
We know that a convex quadratic maximization (not minimization!) on a polyhedron has its global optimal value on a vertex.
Also, I have read in some papers that checking whether a vertex is globally ...
