simplex algorithmの例文

• With Bland's rule, the simplex algorithm solves feasible linear optimization problems without cycling.
• This is why the simplex algorithm uses them and not the original inequalities.
• Trivially, the simplex algorithm takes on average " D " steps for a cube.
• The simplex algorithm has polynomial-time Gaussian random vector ( " smoothed complexity " ).
• It says that if the simplex algorithm fails to terminate then it must cycle.
• This principle underlies the simplex algorithm for solving linear programs.
• Commercial simplex solvers are based on the revised simplex algorithm.
• If " M " is simplex algorithm of Dantzig have been used for decades.
• The method solves the linear program without the integer constraint using the regular simplex algorithm.
• The Simplex algorithm seems able to handle situations with no solutions or multiple solutions quite well.
• In rare practical problems, the usual versions of the simplex algorithm may actually " cycle ".
• The main algorithms implemented in FortMP are the primal and dual simplex algorithms using sparse matrices.
• There are examples of degenerate linear optimization problems on which the original simplex algorithm would cycle forever.
• Like the simplex algorithm of worst case.
• Take the simplex algorithm for linear programming.
• Like the simplex algorithm, the criss-cross algorithm visits exactly 3 additional corners of the three-dimensional cube on average.
• However, Karmarkar's interior-point method and variants of the simplex algorithm are much faster than the ellipsoid method in practice.
• Like the simplex algorithm, the criss-cross algorithm visits all 8 corners of the three-dimensional cube in the worst case.
• The simplex algorithm can then be applied to find the solution; this step is called " Phase II ".
• Examples of algorithms that solve convex problems by hill-climbing include the simplex algorithm for linear programming and binary search.