w.r.t x,
s.t. x>=0, 1'*x=1
Here a and b are given vectors, " ' " denotes the vector
transposition, x is our search variable which is a vector, 1 is also a
vector above. It means the element of x should sum up to 1.
Any thoughts?
Thanks a lot!
There is an old idea by Charnes and Cooper that can be used on this
problem I think. However, I would take a look at
S. Boyd and L. Vanderberghe, Convex Optimization, page 151.
which tell you how to convert your problem to an LP.
Erling
if you make Xi=1 for the max ai/bi that will do(?)
if you still want to do an LP may be you can max sum((ai/bi)*Xi), with
the same constraints
Assuming b'*x> 0:
Given any feasible solution with objective value z,
max a'*x - z*b'*x
If the new objective function is greater than 0,
the new x is an improved solution to the original problem.