The MinimizerLP trait sets the pattern for optimization algorithms for solving Linear Programming (LP) problems of the form:
minimize c x subject to a x <= b, x >= 0
where a is the constraint matrix b is the limit/RHS vector c is the cost vector
Classes mixing in this trait must implement an objective function objF an iterative method (solve) that searches for improved solutions x-vectors with lower objective function values.
Run the simplex algorithm starting from an initial BFS and iteratively find a non-basic variable to replace a variable in the current basis so long as the objective function improves. Return the optimal solution vector.
Run the simplex algorithm starting from an initial BFS and iteratively find a non-basic variable to replace a variable in the current basis so long as the objective function improves. Return the optimal solution vector.