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Part 3 Linear Programming 3.4 Transportation Problem.

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Presentation on theme: "Part 3 Linear Programming 3.4 Transportation Problem."— Presentation transcript:

1 Part 3 Linear Programming 3.4 Transportation Problem

2

3 The Transportation Model

4 Theorem A transportation problem always has a solution, but there is exactly one redundant equality constraint. When any one of the equality constraints is dropped, the remaining system of n+m-1 equality constraints is linearly independent.

5 Constraint Structure

6 Problem Structure

7 Model Parameters

8 Transformation of Standard Form of Transportation Problem into the Primal Form

9 Asymmetric Form of Duality

10 Dual Transportation Problem

11 Interpretation of the Dual Transportation Problem Let us imagine an entrepreneur who, feeling that he can ship more efficiently, come to the manufacturer with the offer to buy his product at origins and sell it at the destinations. The entrepreneur must pay -u1, -u2, …, -um for the product at the m origins and then receive v1, v2, …, vn at the n destinations. To be competitive with the usual transportation modes, his prices must satisfy ui+vj<=cij for all ij, since ui+vj represents the net amount the manufacturer must pay to sell a unit of product at origin i and but it back again at the destination j.

12 Example 12 x11 3 x12 8 x13 4 x14 7 x21 4 x22 6 x23 9 x24 8 x31 7 x32 3 x33 6 x34 D1 D2 D3 D4 O1 O2 O3 Amount required Amount Available a1=7 a2=10 a3=12 b1=4 b2=8 b3=11 b4=6

13

14 Solution Procedure Step 1: Set up the solution table. Step 2: “Northwest Corner Rule” – when a cell is selected for assignment, the maximum possible value must be assigned in order to have a basic feasible solution for the primal problem.

15 Northwest Corner Rule 12 4 3333 84 74545 6565 9 873636 6666 7 10 12 4 8 11 6

16 Triangular Matrix Definition: A nonsingular square matrix M is said to be triangular if by a permutation of its rows and columns it can be put in the form of a lower triangular matrix. Clearly a nonsingular lower triangular matrix is triangular according to the above definition. A nonsingular upper triangular matrix is also triangular, since by reversing the order of its rows and columns it becomes lower triangular.

17 How to determine if a given matrix is triangular? 1.Find a row with exactly one nonzero entry. 2.Form a submatrix of the matrix used in Step 1 by crossing out the row found in Step 1 and the column corresponding to the nonzero entry in that row. Return to step 1 with this submatrix. If this procedure can be continued until all rows have been eliminated, then the matrix is triangular.

18 The importance of triangularity is the associated method of back substitution in solving

19 Basis Triangularity Basis Triangularity Theorem: Every basis of the transportation problem is triangular.

20

21 Step 3: Find a basic feasible solution of the dual problem – initial guess Due to one of the constraints in the primal problem is redundant!

22 Step 3 12 4 3 5 8 OK 8 4 VIOLATION 13 7 VIOLATION 4 5 6 5 9 OK 10 8 VIOLATION 1 7 OK 3 6 7 10 12 4 8 11 6 v1=12 v2=3 v3=5 v4=8 u1 = 0 u2 = 1 u3 = -2

23 Cycle of Change -1 c11 x11 +1 c12 x12 c13 0 c14 0 +1 c21 0 -1 c22 x22 c23 x23 c24 0 c31 0 c32 0 c33 x33 c34 x34 v1 v2 v3 v4 u1 u2 u3 a1 a2 a3 b1 b2 b3 b4

24 Selection of the New Basic Variable

25 Step 4: Find a basic feasible solution of the dual problem – Loop identification

26 Step 4: Move 4 unit around loop 1 6 12 0 3 7 5 8 0 8 4 0 7 4 1 6 5 9 0 4 8 0 1 7 0 3 6 7 10 12 4 8 11 6 v1=6 v2=3 v3=5 v4=8 u1 = 0 u2 = 1 u3 = -2

27 Repeat Step 3 Violation: Cell 14

28 Repeat Step 4: Move 5 unit around the loop 6 12 0 3 2 5 8 0 8 4 5 7 4 6 0 9 0 4 8 0 1 7 0 3 11 6 1 7 10 12 4 8 11 6 u1 = 0 u2 = 1 u3 = 2 v1=6 v2=3 v3=1 v4=4 NO VIOLATION!!!

29 Solution

30 Application – Minimum Utility Consumption Rates and Pinch Points Cerda, J., and Westerberg, A. W., “Synthesizing Heat Exchanger Networks Having Restricted Stream/Stream Matches Using Transportation Formulation,” Chemical Engineering Science, 38, 10, pp. 1723 – 1740 (1983).

31 Example - Given Data

32 Temperature Partition

33 Definitions

34 Transportation Formulation

35 Cost Coefficients

36 Additional Constraints

37 Solution


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