Let $f_1,f_2$ be two smooth quasiconcave functions defined on a convex subset of $\mathbb{R}^d$.

It is known that $f_1+f_2$ is not necessarily quasiconcave.

**Does there always exist monotonically increasing functions $g_1,g_2$ such that the sum $g_1\circ f_1 + g_2\circ f_2$ is quasiconcave?**

The motiavation to this question is economic. In economics, it is often assumed that people have quasiconcave utilities: if they are indifferent between $x$ and $y$, then they prefer $(x+y)/2$ to $x$ and to $y$, which is (approximately) the definition of quasiconcavity.
Given two or more people, we would like to create a *social welfare* function by taking the sum of the utility functions of the agents. In general, such a sum is not guaranteed to be quasiconcave. However, a utility function is only a numeric representation of a preference-relation, so we are allowed to transform it using arbitrary monotone transformations and it will still represent the same preference. The question is: can we always transform the utility functions of the agents such that the resulting social-welfare function be quasiconcave?

There are two cases for which I know the answer.

If $f_1$ and $f_2$ are concavifiable, then the answer is "yes", since we can choose $g_1,g_2$ such that $g_1\circ f_1$ and $g_2\circ f_2$ are concave, which makes their sum concave too, and concavity implies quasic

If $f_1$ and $f_2$ are are only weakly quasiconcave, then the answer is "not always", as shown by the example of Taneli Huuskonen below

So the question now becomes: is this always possible to find such $g_1,g_2$ when $f_1,f_2$ are **strictly** quasiconcave*?

*Reminder: $f$ is quasiconcave iff $\forall x,y: \forall r\in(0,1): f(r x + (1-r) y)\geq \min(f(x),f(y))$.
It is strictly quasiconcave iff $\forall x,y: \forall r\in(0,1): f(r x + (1-r) y)> \min(f(x),f(y))$*.