I am looking for extrema of the function
$$ B(x,y) = \frac{1}{x} \Big[ F(y) - \epsilon [\log(x-y) +1] \Big]$$
limited to the the domain $\Omega = \{y \ge 0, x \geq y\} $
$F$ is a twice differentiable function such that $F(0) = 0$ and having one only stationary point (a maximum) for a $y_0$, $y_0 > 0$.
In general I would like a closed-form solution, but it seems rather unfeasible so I would settle for a characterisation for small $\epsilon$.
If $\epsilon = 0$, setting the partial derivatives to zero yields
\begin{array}{lcl} -\frac{1}{x^2}F(y) & = & 0 \\ \frac{1}{x} F^\prime (y)& = & 0\end{array}
and it can be concluded that no stationary point exists. However, taking a point of the form $ (x, y_0) $, the partial derivatives $\to 0$ for $x\to \infty$, and in this sense one could maybe state there is a stationary point at infinity.
On the other hand, for $\epsilon \neq 0$ a proper stationary point does exist.
I would like to have a characterisation of the stationary point for small $\epsilon$, if not a closed form solution, an asymptotic description or so.
For example, if a function $Y(\epsilon)$ were to be defined, such that it returns the $y$ coordinate of the stationary point for a certain value of the perturbation parameter $\epsilon$, a "Big O" description of the function $Y$ would be very interesting.
I thought something like perturbation theory could be of assistance, but the problem is that the unperturbed problem has not got a solution. I tried to handle the stationary point "at infinity" with the coordinate transformation $z = \frac{1}{x}$, but with little success.
Ths question is related to System of equations and perturbation methods, which regretfully contained multiple errors in its formulation.
Thanks
For the stationary point, you obtain the equations $$ \frac{1}{x}\left(F'(y) + \frac{\epsilon}{x-y}\right) = 0,\\ \frac{1}{x^2}\left(F(y) + \epsilon\frac{y}{x-y}-\epsilon \log(x-y)\right) = 0. $$ You can solve the first equation for $x$ to obtain $$ x = y - \frac{\epsilon}{F'(y)}. $$ Note that the condition $x \geq y$ implies $F'(y)<0$. Substituting the above expression for $x$ in the second equation yields $$ \left(\frac{F'(y)}{\epsilon - y F'(y)}\right)^2\left[-F(y) + y F'(y) + \epsilon \log\left(-\frac{\epsilon}{F'(y)}\right)\right] = 0. $$ Now, there are two distinct possibilities to obtain a solution to this equation for small $\epsilon$.
First, suppose $F'(y)$ is $\mathcal{O}(1)$ for small $\epsilon$. Then, the term $\epsilon \log (-\epsilon/F'(y))$ is small in $\epsilon$, so the leading order equation to satisfy is $- F(y) + y F'(y) = 0$. Suppose we can find a value for $y := \hat{y}$ such that this leading order equation is satisfied (note that, necessarily, $F(\hat{y})<0$). Then, we have $$ x = \hat{y} - \epsilon \frac{1}{F'(\hat{y})} + \text{higher order terms} $$ and $$ y = \hat{y} - \frac{\epsilon}{\hat{y} F''(\hat{y})} \log\left(-\frac{\epsilon}{F'(\hat{y})}\right). $$
However, given your comments, I suspect that the example functions $F$ that you tried numerically are such that we cannot find a solution to $- F(y) + y F'(y) = 0$. So, let's assume that this equation does not have a solution. In that case, we see that the term $\epsilon \log \left(-\frac{\epsilon}{F'(y)}\right)$ must be of the same order as $-F(y) + y F'(y)$. This means in particular that $F'(y)$ must be small. This inspires us to focus on a neighbourhood of the local maximum $y_0$, where $F'(y_0) = 0$. Writing $y = y_0 + \eta$, we obtain to leading order (check this!) the equation $$ -F(y_0) + \epsilon \log \left(-\frac{\epsilon}{F''(y_0) \eta}\right) = 0 $$ (note that the argument of the logarithm is positive as $F''(y_0) < 0$ since $y_0$ is a local maximum, and $\eta > 0$ since $F'(y) < 0$, i.e. we are at the right side of the local maximum), which we can solve to obtain to leading order $$ y = y_0 - \frac{\epsilon}{F''(y_0)} \exp\left(-\frac{F(y_0)}{\epsilon}\right), $$ so $$ x = \exp\left(\frac{F(y_0)}{\epsilon}\right) $$ to leading order. The latter confirms your idea that there is a solution of the unperturbed equation `for $x$ at infinity', in some sense.