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Nonlinear objectives, nonlinear constraints, non-convex objective, non-convex feasible region.
2
votes
Accepted
A variant of (discrete) optimal transport problem
The minimum here can be found exactly, in a finite number of steps.
Indeed, the target function is concave. So, its minimum on the (compact) (transportation) polytope $P:=\Pi(\alpha,\beta)$ is attaine …
2
votes
Reference for article that introduces and motivates different notions of subdifferentials
Section 1.3 of Chapter Nonsmooth Optimization by V. F. Demyanov in the book Nonlinear Optimization discusses in some detail the Dini, Hadamard, Shor, Clarke, and Michel–Penot notions of the subdiffere …
1
vote
Accepted
Optimization: Determine the categorical pmf that maximizes the objective function
Let $c:=\Phi>0$ and $a:=t_{\max}>0$. For any given value (say $m$) of $ET$, the variance $VT$ of $T$ is maximized when $T$ takes only the endpoint values, $0$ and $a$, so that $P(T=a)=m/a=1-P(T=0)$, a …
7
votes
Prove the function $g(x,y,t)\ge1$
This inequality is not true. E.g.,
$$g\Big(\frac1{10},\frac1{10},\frac\pi4\Big)=-1783.256\ldots\not\ge1.$$
The OP has changed the problem, thus invalidating the previous answer. After the change, the …
2
votes
Accepted
Dual problem with integrals
$\newcommand\R{\mathbb R}$
A convenient way to derive the dual problem from a primal one is by using the minimax duality for the Lagrangian, which is given here by the formula $$L(f,v):=\int_R\big[2| …
4
votes
prove $\log \left[ {\sum\limits_{i = 1}^M {{\varepsilon _i}{{\left[ {Q\left( {{a_i} + {b_i}\...
For $a\ge0$ and $u\ge0$, let
$$q(u):=\ln Q(a+\sqrt u).
$$
Then
$$q_2(t):=q''(u)\frac{8 \sqrt{2 \pi } t^3 e^{\frac{1}{2} (a+t)^2} Q(a+t)^2}{a t+t^2+1}
=2 Q(a+t)-\frac{\sqrt{\frac{2}{\pi }} t e^{-\fr …
13
votes
How to prove $e^x\left|\int_x^{x+1}\sin(e^t) \,\mathrm d t\right|\le 1.4$?
Here is a method that will allow one to find the exact upper and lower bounds on $g(z)$ over $z>0$ with any degree of accuracy.
Take any real $z>0$. Since
\begin{equation*}
\frac1y=\int_0^\infty d …
3
votes
Accepted
Obtaining the "best possible" inequality by tuning hyper-parameters
$\newcommand{\ga}{\gamma}$Letting $\ga\to\infty$ (with $A,B,\lambda,f(0)$ fixed), we see that the left-hand side of your inequality
\begin{equation}
\begin{aligned}
&A + (\lambda + \gamma)^2 + \g …
1
vote
Accepted
Maximizing the ratio of multilinear polynomials
Not in general. E.g., let $n=3$, $A(x_1,x_2,x_3):=1-x_1 x_2+2 x_3 x_2+x_1 x_3$, and $B(x_1,x_2,x_3):=2-x_1 x_2+x_3 x_2+2 x_1 x_3$. Then for $x_3\in(0,2\sqrt2)$
$$G(x_3)=\max_{t\in\mathbb R}\frac{A(t, …
2
votes
Accepted
Clarification about this optimisation problem
Your question is
Find the minimum of $f(x,y)=(x-2)^2+y$ subject to $y-x^3\ge0$, $y+x^3\le0$ and $y\ge0$.
The restrictions $y-x^3\ge0$, $y+x^3\le0$, and $y\ge0$ can be rewritten as $0\le y\le-x^3$ or …
1
vote
Does this non-negative function, with no stationary points, have only descent directions clo...
$\newcommand\R{\mathbb R}\newcommand\ep\epsilon\newcommand\bad{\text{bad}}$One would think that the answer is "of course no, descent does not have to monotonic". However, the no stationary points cond …
1
vote
Solution of nonlinear differential equation $g = c_1 f^2 + c_2 (f')^2$ for function $f$
This ODE is extremely unlikely to have an explicit solution. Mathematica cannot do anything with this ODE even when $g(x)\equiv x$.
Here is an image of the corresponding Mathematica notebook:
And her …
5
votes
Accepted
A (reverse)-Minkowski type inequality for symmetric sums
Rewrite the inequality in question as
\begin{equation*}
f(u+v)\le f(u)+f(v)
\end{equation*}
for $u,v$ in $\mathbb R_+^4$,
where
\begin{equation*}
f(u):=-\left(\left(\frac{1}{\sqrt{u_1}}+\frac{1} …
6
votes
Prove that this expression is greater than 1/2
$\newcommand{\R}{\mathbb{R}}$
An advantage of my previous answer was that, while the computer calculations were pretty heavy there, the logic was extremely simple; virtually no thinking or ingenuity w …
2
votes
Variant of Parthasarathy's minimax theorem
Let $f\colon X\times Y\to\mathbb R$, where $X$ and $Y$ are any sets. Suppose that the function $f$ is generalized concave-convex in the sense that for any $x_0,x_1$ in $X$, any $y_0,y_1$ in $Y$, and a …