Part 3 Linear Programming 3 3 Theoretical Analysis
- Slides: 37
Part 3 Linear Programming 3. 3 Theoretical Analysis
Matrix Form of the Linear Programming Problem
Feasible Solution in Matrix Form
Tableau in Matrix Form (without the objective column)
Criteria for Determining A Minimum Feasible Solution
Theorem (Improvement of Basic Feasible Solution) • Given a non-degenerate basic feasible solution with corresponding objective function f 0, suppose for some j there holds cj-fj<0. Then there is a feasible solution with objective value f<f 0. • If the column aj can be substituted for some vector in the original basis to yield a new basic feasible solution, this new solution will have f<f 0. • If aj cannot be substituted to yield a basic feasible solution, then the solution set K is unbounded and the objective function can be made arbitrarily small (negative) toward minus infinity.
Optimality Condition for a Minimum! •
Symmetric Form of Duality (1)
Symmetric Form of Duality (2) •
Alternative Form of Duality
Example Batch Reactor B Batch Reactor A Batch Reactor C Raw materials R 1, R 2, R 3, R 4 Products P 1, P 2, P 3, P 4 P 1 P 2 P 3 P 4 capacity time A 1. 5 1. 0 2. 4 1. 0 2000 B 1. 0 5. 0 1. 0 3. 5 8000 C 1. 5 3. 0 3. 5 1. 0 5000 profit /batch $5. 24 $7. 30 $8. 34 $4. 18 time/batch
Example: Primal Problem
Example: Dual Problem
Property 1 For any feasible solution to the primal problem and any feasible solution to the dual problem, the value of the primal objective function being maximized is always equal to or less than the value of the dual objective function being minimized.
Proof
Property 2
Proof
Duality Theorem If either the primal or dual problem has a finite optimal solution, so does the other, and the corresponding values of objective functions are equal. If either problem has an unbounded objective, the other problem has no feasible solution.
Alternative Form of Duality
Additional Insights Shadow Prices!
Matrix Form of the Linear Programming Problem
Feasible Solution in Matrix Form
Tableau in Matrix Form (without the objective column!)
Relations associated with the Optimal Feasible Solution of the Primal (Minimization) Problem This is the optimality condition of the primal minimization problem! Property 2 is satisfied!
Example PRIMAL DUAL
Tableau in Matrix Form of Primal Problem
Example: The Primal Diet Problem •
Primal Formulation
Alternative Form of Duality
The Dual Diet Problem •
Dual Formulation
Shadow Prices How does the minimum cost in the primal problem change if we change the right hand side b (lower limits of nutrient j)? If the changes are small, then the corner which was optimal remains optimal, i. e. – The choice of basic variables does not change. – At the end of simplex method, the corresponding m columns of A make up the basis matrix B.
- Perbedaan linear programming dan integer programming
- Integer programming vs linear programming
- Perbedaan linear programming dan integer programming
- Sensitivity range linear programming
- Simplex method sensitivity analysis
- Greedy programming vs dynamic programming
- What is in system programming
- Theoretical analysis of time efficiency
- Theoretical analysis of culture
- Define part program
- Linux kernel hacking
- Simplex method
- Difference constraints and shortest paths
- Canonical form of linear programming problem
- Linear programming case study
- Non negativity constraints
- Scope of linear programming
- Network model linear programming
- Management science linear programming
- Pengertian linear programming
- Linear programming word problems
- Characteristics of
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- Pengertian linear programming
- Lp model formulation
- Linear vs integer programming
- Scope of linear programming
- Goal programming example
- Linear programming powerpoint
- The zj row in a simplex table for maximization represents
- Operations management linear programming
- Cj - zj
- Linear programming graphical calculator
- Operation research linear programming
- 3-3 optimization with linear programming
- Saba neyshabouri
- Linear programming relaxation
- Linear programming models graphical and computer methods