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The concepts of duality theory in operations research, including the weak and strong duality properties, complementary solutions property, and symmetry property. The document also covers the complementary basic solutions property, complementary slackness property, and relationships between primal and dual solutions. Examples and problem-solving techniques, as well as applications of duality theory in various fields.
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http://www-scf.usc.edu/~ise Read: H&L chapter 6.3-6. Review: Duality Theory Weak duality property: If x is a feasible solution for the primal problem and y is a feasible solution for the dual problem, then cx ≤ yb. Strong duality property: If x * is an optimal solution for the primal problem and y * is an optimal solution for the dual problem, then cx * = y * b. Complementary solutions property: At each iteration, the simplex method simultaneously identifies a CPF solution x for the primal "roblem and a complementary solution y for the dual problem (found in row 0, the coeff of the slack variables), where cx = yb. If x is not optimal for the primal, y is infeasible. Complementary optimal solutions property: At the final iteration, the simplex method simultaneously identifies an optimal solution x * for the primal problem and a complementary optimal solution y * for the dual problem (found in row 0, the coeff of the slack variables), where cx * = y * b. In this solution, y * gives the shadow prices for the primal problem. Symmetry property: The dual of the dual is the primal. Find the corresponding complementary basic solutions based on the simplex tableaux: Final Basic Coeff Tableaux Var Z original slack RHS Z 1 cBB-1A – c cBB-1^ cBB -1 b x B 0 B-1A B-1^ B-1b
Complementary basic solutions property: Each basic solution in the primal problem has a complementary basic solution in the dual problem , where their respective objective function values (Z and W) are equal. Complementary optimal basic solutions property: Each optimal basic solution in the primal problem has a complementary optimal basic solution in the dual problem, where their respective objective function values (Z and W ) are equal. Complementary slackness property: The variables in the primal basic solution and the complementary dual basic solution satisfy the complementary slackness as shown: Primal variable Dual variable Basic Non-basic (m variables) Non-basic Basic (n variables) Futhermore, the relationship is symmetric. Check for the complementary slackness property: Basic Coeff Iteration Var Z x 1 x 2 x 3 x 4 x 5 RHS 0 Z 1 -30 -15 0 0 0 0 x 3 0 1 0 1 0 0 4 x 4 0 0 2 0 1 0 12 x 5 0 3 2 0 0 1 18 1 Z 1 0 -15 30 0 0 120 x 1 0 1 0 1 0 0 4 x 4 0 0 2 0 1 0 12 x 5 0 0 2 -3 0 1 6 2 Z 1 0 0 7.5 0 7.5 165 x 1 0 1 0 1 0 0 4 x 4 0 0 0 3 1 -1 6 x 2 0 0 1 -1.5 0 0.5 3
Shortcut for conversion between primal and dual: Primal Dual Max Z Min W constraint i: ≤ = ≥ variable i: yi ≥ 0 variable xj: xj ≥ 0 constraint j: Examle: Quidditch Problem Max – Z = – 0.4 x 1 – 0.5 x 2 s.t. 0.3 x 1 + 0.1 x 2 ≤ 2. 0.5 x 1 + 0.5 x 2 = 6 0.6 x 1 + 0.4 x 2 ≥ 6 x 1 ≥ 0, x 2 ≥ 0