Test the Simplex2P Algorithm for solving Linear Programming problems.
Test the Simplex2P Algorithm for solving Linear Programming problems.
the constraint matrix
the limit/RHS vector
the cost vector
Test case 1: Phase I solution - not needed Phase II solution x = (1/3, 0, 13/3), x_B = (0, 2, 4), f = -17
Test case 1: Phase I solution - not needed Phase II solution x = (1/3, 0, 13/3), x_B = (0, 2, 4), f = -17
Linear Programming and Network Flows, Example 3.9
Test case 2: Phase I solution x = (.5, 1.5), x_B = (0, 1, 4), f = 0 Phase II solution x = (0, 3), x_B = (1, 2, 3), f = -6
Test case 2: Phase I solution x = (.5, 1.5), x_B = (0, 1, 4), f = 0 Phase II solution x = (0, 3), x_B = (1, 2, 3), f = -6
Linear Programming and Network Flows, Example 4.3 Negative values for b indicate a '>=' constraint.
Test case 3: Phase I solution x = (2, 0, 4), x_B = (0, 2, 5), f = 0 Phase II solution x = (2, 0, 4), x_B = (0, 2, 5), f = 36
Test case 3: Phase I solution x = (2, 0, 4), x_B = (0, 2, 5), f = 0 Phase II solution x = (2, 0, 4), x_B = (0, 2, 5), f = 36
college.cengage.com/mathematics/larson/elementary_linear/4e/shared/downloads/c09s4.pdf Negative values for b indicate a '>=' constraint.
Test case 4: Phase I solution - not needed Phase II solution x = (2/3, 10/3, 0), x_B = (0, 1, 5), f = -22/3
Test case 4: Phase I solution - not needed Phase II solution x = (2/3, 10/3, 0), x_B = (0, 1, 5), f = -22/3
Linear Programming and Network Flows, Example 5.2
Test case 5: Phase I solution x = (4/5, 8/5), x_B = (0, 1), f = 0 Phase II solution x = (4/5, 8/5), x_B = (0, 1), f = 8.8
Test case 5: Phase I solution x = (4/5, 8/5), x_B = (0, 1), f = 0 Phase II solution x = (4/5, 8/5), x_B = (0, 1), f = 8.8
Linear Programming and Network Flows, Example 6.14
This object is used to test the Simplex2P class.