Using
f[s_] := Log[(s/r)^α ((α - 2) n0 r^α + 2 π Pmax ρ r^2)
/((α - 2) n0 s^α + 2 π Pmax ρ s^2)]/s
When I run the following line:
Assuming[ s > r && r > 1 && Pmax > n0 && n0 > 0 && ρ > 1 && α > 2,
Maximize[f[s],s]]
I get the following output:
Maximize[Log[((s/r)^α (n0 r^α (-2 + α) + 2 π Pmax r^2 ρ))
/(n0 s^α (-2 + α) + 2 π Pmax s^2 ρ)]/s, s]
Actually, Mathematica ignores the assumptions and outputs the function only. That is, nothing is done by Mathematica. I know that Assuming[.] works with Refine, Simplify, and Integrate. But, is there any way to use Maximize with assumptions? What do you think about the given function? Is it analytically solvable at all?
EDIT:
Let g[x]=n0 β + 2 π ρ Pmax x^(-β), where β = α - 2. We can rewrite f[s] as:
f[s_] := Log[g[r]/g[s]]/s
for β>0. Therefore, the optimal point is found by maximizing Log[(g[r]/g[s])^(1/s)] or
equivalently maximizing (g[r]/g[s])^(1/s). Mathematica cannot solve the latter optimization problem as well. Even with some more simplification, r=1 and n0=1, which results in the following problem, it cannot be solved:
Maximize[{((β + 2 π Pmax ρ)/(β + 2 π Pmax s^-β ρ))^(1/s), β > 0, Pmax > 1, ρ > 1}, s]



Solve[f'[s] == 0, s]says it cannot solve the system. – FJRA Apr 17 '12 at 1:27