The objective function, e.
The objective function, e.g., c x.
the coordinate values of the current point
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.
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.
Determine whether the current solution is correct.
Determine whether the current solution is correct.
the primal solution vector x
the dual solution vector y
the minimum value of the objective function
Show the flaw by printing the error message.
Show the flaw by printing the error message.
the method where the error occurred
the error message
This trait sets the pattern for optimization algorithms for solving Linear Programming (NLP) 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.