How do the Linear Program and Genetic Algorithm solution generators come up with portfolio alternatives?
In the case of the Linear Program solution generator, a system of equations representing the business problem is solved and both feasible and optimal solutions are generated. The GA solution generator uses an iterative approach, along with sophisticated sampling algorithms, to guide it towards a set of optimal solutions. The Genetic Algorithm solution generator requires an initial portfolio as a starting point, and thus is designed for use in conjunction with the Rank and Cut or Linear Program solution generators to yield an improved alternative.
